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Type 'q()' to quit R. > x <- array(list(235.1 + ,0 + ,280.7 + ,0 + ,264.6 + ,0 + ,240.7 + ,0 + ,201.4 + ,0 + ,240.8 + ,0 + ,241.1 + ,0 + ,223.8 + ,0 + ,206.1 + ,0 + ,174.7 + ,0 + ,203.3 + ,0 + ,220.5 + ,0 + ,299.5 + ,0 + ,347.4 + ,0 + ,338.3 + ,0 + ,327.7 + ,0 + ,351.6 + ,0 + ,396.6 + ,0 + ,438.8 + ,0 + ,395.6 + ,0 + ,363.5 + ,0 + ,378.8 + ,0 + ,357 + ,0 + ,369 + ,0 + ,464.8 + ,0 + ,479.1 + ,0 + ,431.3 + ,0 + ,366.5 + ,0 + ,326.3 + ,0 + ,355.1 + ,0 + ,331.6 + ,0 + ,261.3 + ,0 + ,249 + ,0 + ,205.5 + ,0 + ,235.6 + ,0 + ,240.9 + ,0 + ,264.9 + ,0 + ,253.8 + ,0 + ,232.3 + ,0 + ,193.8 + ,0 + ,177 + ,0 + ,213.2 + ,0 + ,207.2 + ,0 + ,180.6 + ,0 + ,188.6 + ,0 + ,175.4 + ,0 + ,199 + ,0 + ,179.6 + ,0 + ,225.8 + ,0 + ,234 + ,0 + ,200.2 + ,0 + ,183.6 + ,0 + ,178.2 + ,0 + ,203.2 + ,0 + ,208.5 + ,0 + ,191.8 + ,0 + ,172.8 + ,0 + ,148 + ,0 + ,159.4 + ,0 + ,154.5 + ,0 + ,213.2 + ,0 + ,196.4 + ,0 + ,182.8 + ,0 + ,176.4 + ,0 + ,153.6 + ,0 + ,173.2 + ,0 + ,171 + ,0 + ,151.2 + ,0 + ,161.9 + ,0 + ,157.2 + ,0 + ,201.7 + ,0 + ,236.4 + ,0 + ,356.1 + ,0 + ,398.3 + ,0 + ,403.7 + ,0 + ,384.6 + ,0 + ,365.8 + ,0 + ,368.1 + ,0 + ,367.9 + ,0 + ,347 + ,0 + ,343.3 + ,0 + ,292.9 + ,0 + ,311.5 + ,0 + ,300.9 + ,0 + ,366.9 + ,0 + ,356.9 + ,0 + ,329.7 + ,0 + ,316.2 + ,0 + ,269 + ,0 + ,289.3 + ,0 + ,266.2 + ,0 + ,253.6 + ,0 + ,233.8 + ,0 + ,228.4 + ,0 + ,253.6 + ,0 + ,260.1 + ,0 + ,306.6 + ,0 + ,309.2 + ,0 + ,309.5 + ,0 + ,271 + ,0 + ,279.9 + ,0 + ,317.9 + ,0 + ,298.4 + ,0 + ,246.7 + ,0 + ,227.3 + ,0 + ,209.1 + ,0 + ,259.9 + ,0 + ,266 + ,0 + ,320.6 + ,0 + ,308.5 + ,0 + ,282.2 + ,0 + ,262.7 + ,0 + ,263.5 + ,0 + ,313.1 + ,0 + ,284.3 + ,0 + ,252.6 + ,0 + ,250.3 + ,0 + ,246.5 + ,0 + ,312.7 + ,0 + ,333.2 + ,0 + ,446.4 + ,0 + ,511.6 + ,0 + ,515.5 + ,0 + ,506.4 + ,0 + ,483.2 + ,0 + ,522.3 + ,0 + ,509.8 + ,0 + ,460.7 + ,0 + ,405.8 + ,0 + ,375 + ,0 + ,378.5 + ,0 + ,406.8 + ,0 + ,467.8 + ,0 + ,469.8 + ,0 + ,429.8 + ,0 + ,355.8 + ,0 + ,332.7 + ,0 + ,378 + ,0 + ,360.5 + ,0 + ,334.7 + ,0 + ,319.5 + ,0 + ,323.1 + ,0 + 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+ ,0 + ,278.8 + ,0 + ,324.4 + ,0 + ,310.9 + ,0 + ,299 + ,0 + ,273 + ,0 + ,279.3 + ,0 + ,359.2 + ,0 + ,305 + ,0 + ,282.1 + ,0 + ,250.3 + ,0 + ,246.5 + ,0 + ,257.9 + ,0 + ,266.5 + ,0 + ,315.9 + ,0 + ,318.4 + ,0 + ,295.4 + ,0 + ,266.4 + ,0 + ,245.8 + ,0 + ,362.8 + ,0 + ,324.9 + ,0 + ,294.2 + ,0 + ,289.5 + ,0 + ,295.2 + ,0 + ,290.3 + ,0 + ,272 + ,0 + ,307.4 + ,0 + ,328.7 + ,0 + ,292.9 + ,0 + ,249.1 + ,0 + ,230.4 + ,0 + ,361.5 + ,0 + ,321.7 + ,0 + ,277.2 + ,0 + ,260.7 + ,0 + ,251 + ,0 + ,257.6 + ,0 + ,241.8 + ,0 + ,287.5 + ,0 + ,292.3 + ,0 + ,274.7 + ,0 + ,254.2 + ,0 + ,230 + ,0 + ,339 + ,0 + ,318.2 + ,0 + ,287 + ,0 + ,295.8 + ,0 + ,284 + ,0 + ,271 + ,0 + ,262.7 + ,0 + ,340.6 + ,0 + ,379.4 + ,0 + ,373.3 + ,0 + ,355.2 + ,0 + ,338.4 + ,0 + ,466.9 + ,0 + ,451 + ,0 + ,422 + ,0 + ,429.2 + ,0 + ,425.9 + ,0 + ,460.7 + ,0 + ,463.6 + ,0 + ,541.4 + ,0 + ,544.2 + ,0 + ,517.5 + ,0 + ,469.4 + ,0 + ,439.4 + ,0 + ,549 + ,0 + ,533 + ,0 + ,506.1 + ,0 + ,484 + ,0 + ,457 + ,0 + ,481.5 + ,0 + ,469.5 + ,0 + ,544.7 + ,0 + ,541.2 + ,0 + ,521.5 + ,0 + ,469.7 + ,0 + ,434.4 + ,0 + ,542.6 + ,0 + ,517.3 + ,0 + ,485.7 + ,0 + ,465.8 + ,0 + ,447 + ,0 + ,426.6 + ,0 + ,411.6 + ,0 + ,467.5 + ,0 + ,484.5 + ,0 + ,451.2 + ,0 + ,417.4 + ,0 + ,379.9 + ,0 + ,484.7 + ,0 + ,455 + ,0 + ,420.8 + ,0 + ,416.5 + ,0 + ,376.3 + ,0 + ,405.6 + ,0 + ,405.8 + ,0 + ,500.8 + ,1 + ,514 + ,1 + ,475.5 + ,1 + ,430.1 + ,1 + ,414.4 + ,1 + ,538 + ,1 + ,526 + ,1 + ,488.5 + ,1 + ,520.2 + ,1 + ,504.4 + ,1 + ,568.5 + ,1 + ,610.6 + ,1 + ,818 + ,1 + ,830.9 + ,1 + ,835.9 + ,1 + ,782 + ,1 + ,762.3 + ,1 + ,856.9 + ,1 + ,820.9 + ,1 + ,769.6 + ,1 + ,752.2 + ,1 + ,724.4 + ,1 + ,723.1 + ,1 + ,719.5 + ,1 + ,817.4 + ,1 + ,803.3 + ,1 + ,752.5 + ,1 + ,689 + ,1 + ,630.4 + ,1 + ,765.5 + ,1 + ,757.7 + ,1 + ,732.2 + ,1 + ,702.6 + ,1 + ,683.3 + ,1 + ,709.5 + ,1 + ,702.2 + ,1 + ,784.8 + ,1 + ,810.9 + ,1 + ,755.6 + ,1 + ,656.8 + ,1 + ,615.1 + ,1 + ,745.3 + ,1 + ,694.1 + ,1 + ,675.7 + ,1 + ,643.7 + ,1 + ,622.1 + ,1 + ,634.6 + ,1 + ,588 + ,1 + ,689.7 + ,1 + ,673.9 + ,1 + ,647.9 + ,1 + ,568.8 + ,1 + ,545.7 + ,1 + ,632.6 + ,1 + ,643.8 + ,1 + ,593.1 + ,1 + ,579.7 + ,1 + ,546 + ,1 + ,562.9 + ,1 + ,572.5 + ,1) + ,dim=c(2 + ,372) + ,dimnames=list(c('Maandelijkse_werkloosheid' + ,'Dummy') + ,1:372)) > y <- array(NA,dim=c(2,372),dimnames=list(c('Maandelijkse_werkloosheid','Dummy'),1:372)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Maandelijkse_werkloosheid Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 235.1 0 1 0 0 0 0 0 0 0 0 0 0 1 2 280.7 0 0 1 0 0 0 0 0 0 0 0 0 2 3 264.6 0 0 0 1 0 0 0 0 0 0 0 0 3 4 240.7 0 0 0 0 1 0 0 0 0 0 0 0 4 5 201.4 0 0 0 0 0 1 0 0 0 0 0 0 5 6 240.8 0 0 0 0 0 0 1 0 0 0 0 0 6 7 241.1 0 0 0 0 0 0 0 1 0 0 0 0 7 8 223.8 0 0 0 0 0 0 0 0 1 0 0 0 8 9 206.1 0 0 0 0 0 0 0 0 0 1 0 0 9 10 174.7 0 0 0 0 0 0 0 0 0 0 1 0 10 11 203.3 0 0 0 0 0 0 0 0 0 0 0 1 11 12 220.5 0 0 0 0 0 0 0 0 0 0 0 0 12 13 299.5 0 1 0 0 0 0 0 0 0 0 0 0 13 14 347.4 0 0 1 0 0 0 0 0 0 0 0 0 14 15 338.3 0 0 0 1 0 0 0 0 0 0 0 0 15 16 327.7 0 0 0 0 1 0 0 0 0 0 0 0 16 17 351.6 0 0 0 0 0 1 0 0 0 0 0 0 17 18 396.6 0 0 0 0 0 0 1 0 0 0 0 0 18 19 438.8 0 0 0 0 0 0 0 1 0 0 0 0 19 20 395.6 0 0 0 0 0 0 0 0 1 0 0 0 20 21 363.5 0 0 0 0 0 0 0 0 0 1 0 0 21 22 378.8 0 0 0 0 0 0 0 0 0 0 1 0 22 23 357.0 0 0 0 0 0 0 0 0 0 0 0 1 23 24 369.0 0 0 0 0 0 0 0 0 0 0 0 0 24 25 464.8 0 1 0 0 0 0 0 0 0 0 0 0 25 26 479.1 0 0 1 0 0 0 0 0 0 0 0 0 26 27 431.3 0 0 0 1 0 0 0 0 0 0 0 0 27 28 366.5 0 0 0 0 1 0 0 0 0 0 0 0 28 29 326.3 0 0 0 0 0 1 0 0 0 0 0 0 29 30 355.1 0 0 0 0 0 0 1 0 0 0 0 0 30 31 331.6 0 0 0 0 0 0 0 1 0 0 0 0 31 32 261.3 0 0 0 0 0 0 0 0 1 0 0 0 32 33 249.0 0 0 0 0 0 0 0 0 0 1 0 0 33 34 205.5 0 0 0 0 0 0 0 0 0 0 1 0 34 35 235.6 0 0 0 0 0 0 0 0 0 0 0 1 35 36 240.9 0 0 0 0 0 0 0 0 0 0 0 0 36 37 264.9 0 1 0 0 0 0 0 0 0 0 0 0 37 38 253.8 0 0 1 0 0 0 0 0 0 0 0 0 38 39 232.3 0 0 0 1 0 0 0 0 0 0 0 0 39 40 193.8 0 0 0 0 1 0 0 0 0 0 0 0 40 41 177.0 0 0 0 0 0 1 0 0 0 0 0 0 41 42 213.2 0 0 0 0 0 0 1 0 0 0 0 0 42 43 207.2 0 0 0 0 0 0 0 1 0 0 0 0 43 44 180.6 0 0 0 0 0 0 0 0 1 0 0 0 44 45 188.6 0 0 0 0 0 0 0 0 0 1 0 0 45 46 175.4 0 0 0 0 0 0 0 0 0 0 1 0 46 47 199.0 0 0 0 0 0 0 0 0 0 0 0 1 47 48 179.6 0 0 0 0 0 0 0 0 0 0 0 0 48 49 225.8 0 1 0 0 0 0 0 0 0 0 0 0 49 50 234.0 0 0 1 0 0 0 0 0 0 0 0 0 50 51 200.2 0 0 0 1 0 0 0 0 0 0 0 0 51 52 183.6 0 0 0 0 1 0 0 0 0 0 0 0 52 53 178.2 0 0 0 0 0 1 0 0 0 0 0 0 53 54 203.2 0 0 0 0 0 0 1 0 0 0 0 0 54 55 208.5 0 0 0 0 0 0 0 1 0 0 0 0 55 56 191.8 0 0 0 0 0 0 0 0 1 0 0 0 56 57 172.8 0 0 0 0 0 0 0 0 0 1 0 0 57 58 148.0 0 0 0 0 0 0 0 0 0 0 1 0 58 59 159.4 0 0 0 0 0 0 0 0 0 0 0 1 59 60 154.5 0 0 0 0 0 0 0 0 0 0 0 0 60 61 213.2 0 1 0 0 0 0 0 0 0 0 0 0 61 62 196.4 0 0 1 0 0 0 0 0 0 0 0 0 62 63 182.8 0 0 0 1 0 0 0 0 0 0 0 0 63 64 176.4 0 0 0 0 1 0 0 0 0 0 0 0 64 65 153.6 0 0 0 0 0 1 0 0 0 0 0 0 65 66 173.2 0 0 0 0 0 0 1 0 0 0 0 0 66 67 171.0 0 0 0 0 0 0 0 1 0 0 0 0 67 68 151.2 0 0 0 0 0 0 0 0 1 0 0 0 68 69 161.9 0 0 0 0 0 0 0 0 0 1 0 0 69 70 157.2 0 0 0 0 0 0 0 0 0 0 1 0 70 71 201.7 0 0 0 0 0 0 0 0 0 0 0 1 71 72 236.4 0 0 0 0 0 0 0 0 0 0 0 0 72 73 356.1 0 1 0 0 0 0 0 0 0 0 0 0 73 74 398.3 0 0 1 0 0 0 0 0 0 0 0 0 74 75 403.7 0 0 0 1 0 0 0 0 0 0 0 0 75 76 384.6 0 0 0 0 1 0 0 0 0 0 0 0 76 77 365.8 0 0 0 0 0 1 0 0 0 0 0 0 77 78 368.1 0 0 0 0 0 0 1 0 0 0 0 0 78 79 367.9 0 0 0 0 0 0 0 1 0 0 0 0 79 80 347.0 0 0 0 0 0 0 0 0 1 0 0 0 80 81 343.3 0 0 0 0 0 0 0 0 0 1 0 0 81 82 292.9 0 0 0 0 0 0 0 0 0 0 1 0 82 83 311.5 0 0 0 0 0 0 0 0 0 0 0 1 83 84 300.9 0 0 0 0 0 0 0 0 0 0 0 0 84 85 366.9 0 1 0 0 0 0 0 0 0 0 0 0 85 86 356.9 0 0 1 0 0 0 0 0 0 0 0 0 86 87 329.7 0 0 0 1 0 0 0 0 0 0 0 0 87 88 316.2 0 0 0 0 1 0 0 0 0 0 0 0 88 89 269.0 0 0 0 0 0 1 0 0 0 0 0 0 89 90 289.3 0 0 0 0 0 0 1 0 0 0 0 0 90 91 266.2 0 0 0 0 0 0 0 1 0 0 0 0 91 92 253.6 0 0 0 0 0 0 0 0 1 0 0 0 92 93 233.8 0 0 0 0 0 0 0 0 0 1 0 0 93 94 228.4 0 0 0 0 0 0 0 0 0 0 1 0 94 95 253.6 0 0 0 0 0 0 0 0 0 0 0 1 95 96 260.1 0 0 0 0 0 0 0 0 0 0 0 0 96 97 306.6 0 1 0 0 0 0 0 0 0 0 0 0 97 98 309.2 0 0 1 0 0 0 0 0 0 0 0 0 98 99 309.5 0 0 0 1 0 0 0 0 0 0 0 0 99 100 271.0 0 0 0 0 1 0 0 0 0 0 0 0 100 101 279.9 0 0 0 0 0 1 0 0 0 0 0 0 101 102 317.9 0 0 0 0 0 0 1 0 0 0 0 0 102 103 298.4 0 0 0 0 0 0 0 1 0 0 0 0 103 104 246.7 0 0 0 0 0 0 0 0 1 0 0 0 104 105 227.3 0 0 0 0 0 0 0 0 0 1 0 0 105 106 209.1 0 0 0 0 0 0 0 0 0 0 1 0 106 107 259.9 0 0 0 0 0 0 0 0 0 0 0 1 107 108 266.0 0 0 0 0 0 0 0 0 0 0 0 0 108 109 320.6 0 1 0 0 0 0 0 0 0 0 0 0 109 110 308.5 0 0 1 0 0 0 0 0 0 0 0 0 110 111 282.2 0 0 0 1 0 0 0 0 0 0 0 0 111 112 262.7 0 0 0 0 1 0 0 0 0 0 0 0 112 113 263.5 0 0 0 0 0 1 0 0 0 0 0 0 113 114 313.1 0 0 0 0 0 0 1 0 0 0 0 0 114 115 284.3 0 0 0 0 0 0 0 1 0 0 0 0 115 116 252.6 0 0 0 0 0 0 0 0 1 0 0 0 116 117 250.3 0 0 0 0 0 0 0 0 0 1 0 0 117 118 246.5 0 0 0 0 0 0 0 0 0 0 1 0 118 119 312.7 0 0 0 0 0 0 0 0 0 0 0 1 119 120 333.2 0 0 0 0 0 0 0 0 0 0 0 0 120 121 446.4 0 1 0 0 0 0 0 0 0 0 0 0 121 122 511.6 0 0 1 0 0 0 0 0 0 0 0 0 122 123 515.5 0 0 0 1 0 0 0 0 0 0 0 0 123 124 506.4 0 0 0 0 1 0 0 0 0 0 0 0 124 125 483.2 0 0 0 0 0 1 0 0 0 0 0 0 125 126 522.3 0 0 0 0 0 0 1 0 0 0 0 0 126 127 509.8 0 0 0 0 0 0 0 1 0 0 0 0 127 128 460.7 0 0 0 0 0 0 0 0 1 0 0 0 128 129 405.8 0 0 0 0 0 0 0 0 0 1 0 0 129 130 375.0 0 0 0 0 0 0 0 0 0 0 1 0 130 131 378.5 0 0 0 0 0 0 0 0 0 0 0 1 131 132 406.8 0 0 0 0 0 0 0 0 0 0 0 0 132 133 467.8 0 1 0 0 0 0 0 0 0 0 0 0 133 134 469.8 0 0 1 0 0 0 0 0 0 0 0 0 134 135 429.8 0 0 0 1 0 0 0 0 0 0 0 0 135 136 355.8 0 0 0 0 1 0 0 0 0 0 0 0 136 137 332.7 0 0 0 0 0 1 0 0 0 0 0 0 137 138 378.0 0 0 0 0 0 0 1 0 0 0 0 0 138 139 360.5 0 0 0 0 0 0 0 1 0 0 0 0 139 140 334.7 0 0 0 0 0 0 0 0 1 0 0 0 140 141 319.5 0 0 0 0 0 0 0 0 0 1 0 0 141 142 323.1 0 0 0 0 0 0 0 0 0 0 1 0 142 143 363.6 0 0 0 0 0 0 0 0 0 0 0 1 143 144 352.1 0 0 0 0 0 0 0 0 0 0 0 0 144 145 411.9 0 1 0 0 0 0 0 0 0 0 0 0 145 146 388.6 0 0 1 0 0 0 0 0 0 0 0 0 146 147 416.4 0 0 0 1 0 0 0 0 0 0 0 0 147 148 360.7 0 0 0 0 1 0 0 0 0 0 0 0 148 149 338.0 0 0 0 0 0 1 0 0 0 0 0 0 149 150 417.2 0 0 0 0 0 0 1 0 0 0 0 0 150 151 388.4 0 0 0 0 0 0 0 1 0 0 0 0 151 152 371.1 0 0 0 0 0 0 0 0 1 0 0 0 152 153 331.5 0 0 0 0 0 0 0 0 0 1 0 0 153 154 353.7 0 0 0 0 0 0 0 0 0 0 1 0 154 155 396.7 0 0 0 0 0 0 0 0 0 0 0 1 155 156 447.0 0 0 0 0 0 0 0 0 0 0 0 0 156 157 533.5 0 1 0 0 0 0 0 0 0 0 0 0 157 158 565.4 0 0 1 0 0 0 0 0 0 0 0 0 158 159 542.3 0 0 0 1 0 0 0 0 0 0 0 0 159 160 488.7 0 0 0 0 1 0 0 0 0 0 0 0 160 161 467.1 0 0 0 0 0 1 0 0 0 0 0 0 161 162 531.3 0 0 0 0 0 0 1 0 0 0 0 0 162 163 496.1 0 0 0 0 0 0 0 1 0 0 0 0 163 164 444.0 0 0 0 0 0 0 0 0 1 0 0 0 164 165 403.4 0 0 0 0 0 0 0 0 0 1 0 0 165 166 386.3 0 0 0 0 0 0 0 0 0 0 1 0 166 167 394.1 0 0 0 0 0 0 0 0 0 0 0 1 167 168 404.1 0 0 0 0 0 0 0 0 0 0 0 0 168 169 462.1 0 1 0 0 0 0 0 0 0 0 0 0 169 170 448.1 0 0 1 0 0 0 0 0 0 0 0 0 170 171 432.3 0 0 0 1 0 0 0 0 0 0 0 0 171 172 386.3 0 0 0 0 1 0 0 0 0 0 0 0 172 173 395.2 0 0 0 0 0 1 0 0 0 0 0 0 173 174 421.9 0 0 0 0 0 0 1 0 0 0 0 0 174 175 382.9 0 0 0 0 0 0 0 1 0 0 0 0 175 176 384.2 0 0 0 0 0 0 0 0 1 0 0 0 176 177 345.5 0 0 0 0 0 0 0 0 0 1 0 0 177 178 323.4 0 0 0 0 0 0 0 0 0 0 1 0 178 179 372.6 0 0 0 0 0 0 0 0 0 0 0 1 179 180 376.0 0 0 0 0 0 0 0 0 0 0 0 0 180 181 462.7 0 1 0 0 0 0 0 0 0 0 0 0 181 182 487.0 0 0 1 0 0 0 0 0 0 0 0 0 182 183 444.2 0 0 0 1 0 0 0 0 0 0 0 0 183 184 399.3 0 0 0 0 1 0 0 0 0 0 0 0 184 185 394.9 0 0 0 0 0 1 0 0 0 0 0 0 185 186 455.4 0 0 0 0 0 0 1 0 0 0 0 0 186 187 414.0 0 0 0 0 0 0 0 1 0 0 0 0 187 188 375.5 0 0 0 0 0 0 0 0 1 0 0 0 188 189 347.0 0 0 0 0 0 0 0 0 0 1 0 0 189 190 339.4 0 0 0 0 0 0 0 0 0 0 1 0 190 191 385.8 0 0 0 0 0 0 0 0 0 0 0 1 191 192 378.8 0 0 0 0 0 0 0 0 0 0 0 0 192 193 451.8 0 1 0 0 0 0 0 0 0 0 0 0 193 194 446.1 0 0 1 0 0 0 0 0 0 0 0 0 194 195 422.5 0 0 0 1 0 0 0 0 0 0 0 0 195 196 383.1 0 0 0 0 1 0 0 0 0 0 0 0 196 197 352.8 0 0 0 0 0 1 0 0 0 0 0 0 197 198 445.3 0 0 0 0 0 0 1 0 0 0 0 0 198 199 367.5 0 0 0 0 0 0 0 1 0 0 0 0 199 200 355.1 0 0 0 0 0 0 0 0 1 0 0 0 200 201 326.2 0 0 0 0 0 0 0 0 0 1 0 0 201 202 319.8 0 0 0 0 0 0 0 0 0 0 1 0 202 203 331.8 0 0 0 0 0 0 0 0 0 0 0 1 203 204 340.9 0 0 0 0 0 0 0 0 0 0 0 0 204 205 394.1 0 1 0 0 0 0 0 0 0 0 0 0 205 206 417.2 0 0 1 0 0 0 0 0 0 0 0 0 206 207 369.9 0 0 0 1 0 0 0 0 0 0 0 0 207 208 349.2 0 0 0 0 1 0 0 0 0 0 0 0 208 209 321.4 0 0 0 0 0 1 0 0 0 0 0 0 209 210 405.7 0 0 0 0 0 0 1 0 0 0 0 0 210 211 342.9 0 0 0 0 0 0 0 1 0 0 0 0 211 212 316.5 0 0 0 0 0 0 0 0 1 0 0 0 212 213 284.2 0 0 0 0 0 0 0 0 0 1 0 0 213 214 270.9 0 0 0 0 0 0 0 0 0 0 1 0 214 215 288.8 0 0 0 0 0 0 0 0 0 0 0 1 215 216 278.8 0 0 0 0 0 0 0 0 0 0 0 0 216 217 324.4 0 1 0 0 0 0 0 0 0 0 0 0 217 218 310.9 0 0 1 0 0 0 0 0 0 0 0 0 218 219 299.0 0 0 0 1 0 0 0 0 0 0 0 0 219 220 273.0 0 0 0 0 1 0 0 0 0 0 0 0 220 221 279.3 0 0 0 0 0 1 0 0 0 0 0 0 221 222 359.2 0 0 0 0 0 0 1 0 0 0 0 0 222 223 305.0 0 0 0 0 0 0 0 1 0 0 0 0 223 224 282.1 0 0 0 0 0 0 0 0 1 0 0 0 224 225 250.3 0 0 0 0 0 0 0 0 0 1 0 0 225 226 246.5 0 0 0 0 0 0 0 0 0 0 1 0 226 227 257.9 0 0 0 0 0 0 0 0 0 0 0 1 227 228 266.5 0 0 0 0 0 0 0 0 0 0 0 0 228 229 315.9 0 1 0 0 0 0 0 0 0 0 0 0 229 230 318.4 0 0 1 0 0 0 0 0 0 0 0 0 230 231 295.4 0 0 0 1 0 0 0 0 0 0 0 0 231 232 266.4 0 0 0 0 1 0 0 0 0 0 0 0 232 233 245.8 0 0 0 0 0 1 0 0 0 0 0 0 233 234 362.8 0 0 0 0 0 0 1 0 0 0 0 0 234 235 324.9 0 0 0 0 0 0 0 1 0 0 0 0 235 236 294.2 0 0 0 0 0 0 0 0 1 0 0 0 236 237 289.5 0 0 0 0 0 0 0 0 0 1 0 0 237 238 295.2 0 0 0 0 0 0 0 0 0 0 1 0 238 239 290.3 0 0 0 0 0 0 0 0 0 0 0 1 239 240 272.0 0 0 0 0 0 0 0 0 0 0 0 0 240 241 307.4 0 1 0 0 0 0 0 0 0 0 0 0 241 242 328.7 0 0 1 0 0 0 0 0 0 0 0 0 242 243 292.9 0 0 0 1 0 0 0 0 0 0 0 0 243 244 249.1 0 0 0 0 1 0 0 0 0 0 0 0 244 245 230.4 0 0 0 0 0 1 0 0 0 0 0 0 245 246 361.5 0 0 0 0 0 0 1 0 0 0 0 0 246 247 321.7 0 0 0 0 0 0 0 1 0 0 0 0 247 248 277.2 0 0 0 0 0 0 0 0 1 0 0 0 248 249 260.7 0 0 0 0 0 0 0 0 0 1 0 0 249 250 251.0 0 0 0 0 0 0 0 0 0 0 1 0 250 251 257.6 0 0 0 0 0 0 0 0 0 0 0 1 251 252 241.8 0 0 0 0 0 0 0 0 0 0 0 0 252 253 287.5 0 1 0 0 0 0 0 0 0 0 0 0 253 254 292.3 0 0 1 0 0 0 0 0 0 0 0 0 254 255 274.7 0 0 0 1 0 0 0 0 0 0 0 0 255 256 254.2 0 0 0 0 1 0 0 0 0 0 0 0 256 257 230.0 0 0 0 0 0 1 0 0 0 0 0 0 257 258 339.0 0 0 0 0 0 0 1 0 0 0 0 0 258 259 318.2 0 0 0 0 0 0 0 1 0 0 0 0 259 260 287.0 0 0 0 0 0 0 0 0 1 0 0 0 260 261 295.8 0 0 0 0 0 0 0 0 0 1 0 0 261 262 284.0 0 0 0 0 0 0 0 0 0 0 1 0 262 263 271.0 0 0 0 0 0 0 0 0 0 0 0 1 263 264 262.7 0 0 0 0 0 0 0 0 0 0 0 0 264 265 340.6 0 1 0 0 0 0 0 0 0 0 0 0 265 266 379.4 0 0 1 0 0 0 0 0 0 0 0 0 266 267 373.3 0 0 0 1 0 0 0 0 0 0 0 0 267 268 355.2 0 0 0 0 1 0 0 0 0 0 0 0 268 269 338.4 0 0 0 0 0 1 0 0 0 0 0 0 269 270 466.9 0 0 0 0 0 0 1 0 0 0 0 0 270 271 451.0 0 0 0 0 0 0 0 1 0 0 0 0 271 272 422.0 0 0 0 0 0 0 0 0 1 0 0 0 272 273 429.2 0 0 0 0 0 0 0 0 0 1 0 0 273 274 425.9 0 0 0 0 0 0 0 0 0 0 1 0 274 275 460.7 0 0 0 0 0 0 0 0 0 0 0 1 275 276 463.6 0 0 0 0 0 0 0 0 0 0 0 0 276 277 541.4 0 1 0 0 0 0 0 0 0 0 0 0 277 278 544.2 0 0 1 0 0 0 0 0 0 0 0 0 278 279 517.5 0 0 0 1 0 0 0 0 0 0 0 0 279 280 469.4 0 0 0 0 1 0 0 0 0 0 0 0 280 281 439.4 0 0 0 0 0 1 0 0 0 0 0 0 281 282 549.0 0 0 0 0 0 0 1 0 0 0 0 0 282 283 533.0 0 0 0 0 0 0 0 1 0 0 0 0 283 284 506.1 0 0 0 0 0 0 0 0 1 0 0 0 284 285 484.0 0 0 0 0 0 0 0 0 0 1 0 0 285 286 457.0 0 0 0 0 0 0 0 0 0 0 1 0 286 287 481.5 0 0 0 0 0 0 0 0 0 0 0 1 287 288 469.5 0 0 0 0 0 0 0 0 0 0 0 0 288 289 544.7 0 1 0 0 0 0 0 0 0 0 0 0 289 290 541.2 0 0 1 0 0 0 0 0 0 0 0 0 290 291 521.5 0 0 0 1 0 0 0 0 0 0 0 0 291 292 469.7 0 0 0 0 1 0 0 0 0 0 0 0 292 293 434.4 0 0 0 0 0 1 0 0 0 0 0 0 293 294 542.6 0 0 0 0 0 0 1 0 0 0 0 0 294 295 517.3 0 0 0 0 0 0 0 1 0 0 0 0 295 296 485.7 0 0 0 0 0 0 0 0 1 0 0 0 296 297 465.8 0 0 0 0 0 0 0 0 0 1 0 0 297 298 447.0 0 0 0 0 0 0 0 0 0 0 1 0 298 299 426.6 0 0 0 0 0 0 0 0 0 0 0 1 299 300 411.6 0 0 0 0 0 0 0 0 0 0 0 0 300 301 467.5 0 1 0 0 0 0 0 0 0 0 0 0 301 302 484.5 0 0 1 0 0 0 0 0 0 0 0 0 302 303 451.2 0 0 0 1 0 0 0 0 0 0 0 0 303 304 417.4 0 0 0 0 1 0 0 0 0 0 0 0 304 305 379.9 0 0 0 0 0 1 0 0 0 0 0 0 305 306 484.7 0 0 0 0 0 0 1 0 0 0 0 0 306 307 455.0 0 0 0 0 0 0 0 1 0 0 0 0 307 308 420.8 0 0 0 0 0 0 0 0 1 0 0 0 308 309 416.5 0 0 0 0 0 0 0 0 0 1 0 0 309 310 376.3 0 0 0 0 0 0 0 0 0 0 1 0 310 311 405.6 0 0 0 0 0 0 0 0 0 0 0 1 311 312 405.8 0 0 0 0 0 0 0 0 0 0 0 0 312 313 500.8 1 1 0 0 0 0 0 0 0 0 0 0 313 314 514.0 1 0 1 0 0 0 0 0 0 0 0 0 314 315 475.5 1 0 0 1 0 0 0 0 0 0 0 0 315 316 430.1 1 0 0 0 1 0 0 0 0 0 0 0 316 317 414.4 1 0 0 0 0 1 0 0 0 0 0 0 317 318 538.0 1 0 0 0 0 0 1 0 0 0 0 0 318 319 526.0 1 0 0 0 0 0 0 1 0 0 0 0 319 320 488.5 1 0 0 0 0 0 0 0 1 0 0 0 320 321 520.2 1 0 0 0 0 0 0 0 0 1 0 0 321 322 504.4 1 0 0 0 0 0 0 0 0 0 1 0 322 323 568.5 1 0 0 0 0 0 0 0 0 0 0 1 323 324 610.6 1 0 0 0 0 0 0 0 0 0 0 0 324 325 818.0 1 1 0 0 0 0 0 0 0 0 0 0 325 326 830.9 1 0 1 0 0 0 0 0 0 0 0 0 326 327 835.9 1 0 0 1 0 0 0 0 0 0 0 0 327 328 782.0 1 0 0 0 1 0 0 0 0 0 0 0 328 329 762.3 1 0 0 0 0 1 0 0 0 0 0 0 329 330 856.9 1 0 0 0 0 0 1 0 0 0 0 0 330 331 820.9 1 0 0 0 0 0 0 1 0 0 0 0 331 332 769.6 1 0 0 0 0 0 0 0 1 0 0 0 332 333 752.2 1 0 0 0 0 0 0 0 0 1 0 0 333 334 724.4 1 0 0 0 0 0 0 0 0 0 1 0 334 335 723.1 1 0 0 0 0 0 0 0 0 0 0 1 335 336 719.5 1 0 0 0 0 0 0 0 0 0 0 0 336 337 817.4 1 1 0 0 0 0 0 0 0 0 0 0 337 338 803.3 1 0 1 0 0 0 0 0 0 0 0 0 338 339 752.5 1 0 0 1 0 0 0 0 0 0 0 0 339 340 689.0 1 0 0 0 1 0 0 0 0 0 0 0 340 341 630.4 1 0 0 0 0 1 0 0 0 0 0 0 341 342 765.5 1 0 0 0 0 0 1 0 0 0 0 0 342 343 757.7 1 0 0 0 0 0 0 1 0 0 0 0 343 344 732.2 1 0 0 0 0 0 0 0 1 0 0 0 344 345 702.6 1 0 0 0 0 0 0 0 0 1 0 0 345 346 683.3 1 0 0 0 0 0 0 0 0 0 1 0 346 347 709.5 1 0 0 0 0 0 0 0 0 0 0 1 347 348 702.2 1 0 0 0 0 0 0 0 0 0 0 0 348 349 784.8 1 1 0 0 0 0 0 0 0 0 0 0 349 350 810.9 1 0 1 0 0 0 0 0 0 0 0 0 350 351 755.6 1 0 0 1 0 0 0 0 0 0 0 0 351 352 656.8 1 0 0 0 1 0 0 0 0 0 0 0 352 353 615.1 1 0 0 0 0 1 0 0 0 0 0 0 353 354 745.3 1 0 0 0 0 0 1 0 0 0 0 0 354 355 694.1 1 0 0 0 0 0 0 1 0 0 0 0 355 356 675.7 1 0 0 0 0 0 0 0 1 0 0 0 356 357 643.7 1 0 0 0 0 0 0 0 0 1 0 0 357 358 622.1 1 0 0 0 0 0 0 0 0 0 1 0 358 359 634.6 1 0 0 0 0 0 0 0 0 0 0 1 359 360 588.0 1 0 0 0 0 0 0 0 0 0 0 0 360 361 689.7 1 1 0 0 0 0 0 0 0 0 0 0 361 362 673.9 1 0 1 0 0 0 0 0 0 0 0 0 362 363 647.9 1 0 0 1 0 0 0 0 0 0 0 0 363 364 568.8 1 0 0 0 1 0 0 0 0 0 0 0 364 365 545.7 1 0 0 0 0 1 0 0 0 0 0 0 365 366 632.6 1 0 0 0 0 0 1 0 0 0 0 0 366 367 643.8 1 0 0 0 0 0 0 1 0 0 0 0 367 368 593.1 1 0 0 0 0 0 0 0 1 0 0 0 368 369 579.7 1 0 0 0 0 0 0 0 0 1 0 0 369 370 546.0 1 0 0 0 0 0 0 0 0 0 1 0 370 371 562.9 1 0 0 0 0 0 0 0 0 0 0 1 371 372 572.5 1 0 0 0 0 0 0 0 0 0 0 0 372 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy M1 M2 M3 M4 233.3034 220.7212 66.9386 76.2985 53.4938 14.0343 M5 M6 M7 M8 M9 M10 -7.0414 65.1475 41.8396 10.1575 -7.4859 -23.4648 M11 t -1.9308 0.5369 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -207.633 -66.837 0.889 67.453 192.481 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 233.3034 17.8153 13.096 < 2e-16 *** Dummy 220.7212 15.7009 14.058 < 2e-16 *** M1 66.9386 21.8073 3.070 0.002307 ** M2 76.2985 21.8059 3.499 0.000526 *** M3 53.4938 21.8047 2.453 0.014631 * M4 14.0343 21.8036 0.644 0.520203 M5 -7.0414 21.8026 -0.323 0.746913 M6 65.1475 21.8017 2.988 0.003000 ** M7 41.8396 21.8010 1.919 0.055759 . M8 10.1575 21.8004 0.466 0.641549 M9 -7.4859 21.7999 -0.343 0.731504 M10 -23.4648 21.7996 -1.076 0.282478 M11 -1.9308 21.7994 -0.089 0.929472 t 0.5369 0.0538 9.980 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 85.82 on 358 degrees of freedom Multiple R-squared: 0.7043, Adjusted R-squared: 0.6936 F-statistic: 65.61 on 13 and 358 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.0464826590 9.296532e-02 9.535173e-01 [2,] 0.0350947806 7.018956e-02 9.649052e-01 [3,] 0.0488802980 9.776060e-02 9.511197e-01 [4,] 0.0304648235 6.092965e-02 9.695352e-01 [5,] 0.0151727827 3.034557e-02 9.848272e-01 [6,] 0.0138799756 2.775995e-02 9.861200e-01 [7,] 0.0063946690 1.278934e-02 9.936053e-01 [8,] 0.0027784968 5.556994e-03 9.972215e-01 [9,] 0.0011624522 2.324904e-03 9.988375e-01 [10,] 0.0006274904 1.254981e-03 9.993725e-01 [11,] 0.0006083021 1.216604e-03 9.993917e-01 [12,] 0.0015672672 3.134534e-03 9.984327e-01 [13,] 0.0048581359 9.716272e-03 9.951419e-01 [14,] 0.0104076781 2.081536e-02 9.895923e-01 [15,] 0.0313730161 6.274603e-02 9.686270e-01 [16,] 0.0921643280 1.843287e-01 9.078357e-01 [17,] 0.1440019216 2.880038e-01 8.559981e-01 [18,] 0.2394871326 4.789743e-01 7.605129e-01 [19,] 0.2797138188 5.594276e-01 7.202862e-01 [20,] 0.3190864066 6.381728e-01 6.809136e-01 [21,] 0.4148126041 8.296252e-01 5.851874e-01 [22,] 0.5601704245 8.796592e-01 4.398296e-01 [23,] 0.6485772649 7.028455e-01 3.514227e-01 [24,] 0.7102131157 5.795738e-01 2.897869e-01 [25,] 0.7462418060 5.075164e-01 2.537582e-01 [26,] 0.7720408974 4.559182e-01 2.279591e-01 [27,] 0.7959565913 4.080868e-01 2.040434e-01 [28,] 0.7987435147 4.025130e-01 2.012565e-01 [29,] 0.7800679161 4.398642e-01 2.199321e-01 [30,] 0.7555940659 4.888119e-01 2.444059e-01 [31,] 0.7241235305 5.517529e-01 2.758765e-01 [32,] 0.7059934953 5.880130e-01 2.940065e-01 [33,] 0.6825545190 6.348910e-01 3.174455e-01 [34,] 0.6649123018 6.701754e-01 3.350877e-01 [35,] 0.6520959883 6.958080e-01 3.479040e-01 [36,] 0.6241662743 7.516675e-01 3.758337e-01 [37,] 0.5879342247 8.241316e-01 4.120658e-01 [38,] 0.5631661027 8.736678e-01 4.368339e-01 [39,] 0.5316280028 9.367440e-01 4.683720e-01 [40,] 0.4916070241 9.832140e-01 5.083930e-01 [41,] 0.4532477168 9.064954e-01 5.467523e-01 [42,] 0.4184958957 8.369918e-01 5.815041e-01 [43,] 0.3874203676 7.748407e-01 6.125796e-01 [44,] 0.3611074651 7.222149e-01 6.388925e-01 [45,] 0.3327248010 6.654496e-01 6.672752e-01 [46,] 0.3207565678 6.415131e-01 6.792434e-01 [47,] 0.3032032467 6.064065e-01 6.967968e-01 [48,] 0.2757632908 5.515266e-01 7.242367e-01 [49,] 0.2510359970 5.020720e-01 7.489640e-01 [50,] 0.2433003660 4.866007e-01 7.566996e-01 [51,] 0.2318942469 4.637885e-01 7.681058e-01 [52,] 0.2164845273 4.329691e-01 7.835155e-01 [53,] 0.1963750403 3.927501e-01 8.036250e-01 [54,] 0.1777811887 3.555624e-01 8.222188e-01 [55,] 0.1643147751 3.286296e-01 8.356852e-01 [56,] 0.1602549776 3.205100e-01 8.397450e-01 [57,] 0.2117291112 4.234582e-01 7.882709e-01 [58,] 0.2926461922 5.852924e-01 7.073538e-01 [59,] 0.4119211895 8.238424e-01 5.880788e-01 [60,] 0.5321458195 9.357084e-01 4.678542e-01 [61,] 0.6290882046 7.418236e-01 3.709118e-01 [62,] 0.6693010111 6.613980e-01 3.306990e-01 [63,] 0.6987168411 6.025663e-01 3.012832e-01 [64,] 0.7312276546 5.375447e-01 2.687723e-01 [65,] 0.7627624970 4.744750e-01 2.372375e-01 [66,] 0.7650962250 4.698075e-01 2.349038e-01 [67,] 0.7646764968 4.706470e-01 2.353235e-01 [68,] 0.7537389879 4.925220e-01 2.462610e-01 [69,] 0.7449932158 5.100136e-01 2.550068e-01 [70,] 0.7239157666 5.521685e-01 2.760842e-01 [71,] 0.6994078803 6.011842e-01 3.005921e-01 [72,] 0.6765000553 6.469999e-01 3.234999e-01 [73,] 0.6454743146 7.090514e-01 3.545257e-01 [74,] 0.6208888656 7.582223e-01 3.791111e-01 [75,] 0.5939926875 8.120146e-01 4.060073e-01 [76,] 0.5638692768 8.722614e-01 4.361307e-01 [77,] 0.5333850257 9.332299e-01 4.666150e-01 [78,] 0.5025878162 9.948244e-01 4.974122e-01 [79,] 0.4723732804 9.447466e-01 5.276267e-01 [80,] 0.4420544086 8.841088e-01 5.579456e-01 [81,] 0.4144385062 8.288770e-01 5.855615e-01 [82,] 0.3884457550 7.768915e-01 6.115542e-01 [83,] 0.3601847017 7.203694e-01 6.398153e-01 [84,] 0.3312692413 6.625385e-01 6.687308e-01 [85,] 0.3036290081 6.072580e-01 6.963710e-01 [86,] 0.2852060130 5.704120e-01 7.147940e-01 [87,] 0.2624934415 5.249869e-01 7.375066e-01 [88,] 0.2429413751 4.858828e-01 7.570586e-01 [89,] 0.2248675766 4.497352e-01 7.751324e-01 [90,] 0.2086538083 4.173076e-01 7.913462e-01 [91,] 0.1902390699 3.804781e-01 8.097609e-01 [92,] 0.1725840594 3.451681e-01 8.274159e-01 [93,] 0.1575466656 3.150933e-01 8.424533e-01 [94,] 0.1460400856 2.920802e-01 8.539599e-01 [95,] 0.1361994552 2.723989e-01 8.638005e-01 [96,] 0.1234974941 2.469950e-01 8.765025e-01 [97,] 0.1096755817 2.193512e-01 8.903244e-01 [98,] 0.1027201468 2.054403e-01 8.972799e-01 [99,] 0.0947996590 1.895993e-01 9.052003e-01 [100,] 0.0876955120 1.753910e-01 9.123045e-01 [101,] 0.0796512690 1.593025e-01 9.203487e-01 [102,] 0.0722550850 1.445102e-01 9.277449e-01 [103,] 0.0674951020 1.349902e-01 9.325049e-01 [104,] 0.0646855819 1.293712e-01 9.353144e-01 [105,] 0.0749772057 1.499544e-01 9.250228e-01 [106,] 0.1126013715 2.252027e-01 8.873986e-01 [107,] 0.1781697876 3.563396e-01 8.218302e-01 [108,] 0.2822484237 5.644968e-01 7.177516e-01 [109,] 0.3898623467 7.797247e-01 6.101377e-01 [110,] 0.4879254993 9.758510e-01 5.120745e-01 [111,] 0.5767708776 8.464582e-01 4.232291e-01 [112,] 0.6344895315 7.310209e-01 3.655105e-01 [113,] 0.6474125492 7.051749e-01 3.525875e-01 [114,] 0.6488180683 7.023639e-01 3.511819e-01 [115,] 0.6363518013 7.272964e-01 3.636482e-01 [116,] 0.6365423283 7.269153e-01 3.634577e-01 [117,] 0.6322588383 7.354823e-01 3.677412e-01 [118,] 0.6207405391 7.585189e-01 3.792595e-01 [119,] 0.5993075311 8.013849e-01 4.006925e-01 [120,] 0.5685181850 8.629636e-01 4.314818e-01 [121,] 0.5374081653 9.251837e-01 4.625918e-01 [122,] 0.5079353097 9.841294e-01 4.920647e-01 [123,] 0.4769895050 9.539790e-01 5.230105e-01 [124,] 0.4459890117 8.919780e-01 5.540110e-01 [125,] 0.4151924733 8.303849e-01 5.848075e-01 [126,] 0.3862424330 7.724849e-01 6.137576e-01 [127,] 0.3609818315 7.219637e-01 6.390182e-01 [128,] 0.3329308341 6.658617e-01 6.670692e-01 [129,] 0.3051483948 6.102968e-01 6.948516e-01 [130,] 0.2802537238 5.605074e-01 7.197463e-01 [131,] 0.2562633821 5.125268e-01 7.437366e-01 [132,] 0.2320328447 4.640657e-01 7.679672e-01 [133,] 0.2093574067 4.187148e-01 7.906426e-01 [134,] 0.1895484340 3.790969e-01 8.104516e-01 [135,] 0.1692718578 3.385437e-01 8.307281e-01 [136,] 0.1515728436 3.031457e-01 8.484272e-01 [137,] 0.1339281042 2.678562e-01 8.660719e-01 [138,] 0.1207473832 2.414948e-01 8.792526e-01 [139,] 0.1120437176 2.240874e-01 8.879563e-01 [140,] 0.1184625973 2.369252e-01 8.815374e-01 [141,] 0.1350208392 2.700417e-01 8.649792e-01 [142,] 0.1676343801 3.352688e-01 8.323656e-01 [143,] 0.2033944754 4.067890e-01 7.966055e-01 [144,] 0.2308843121 4.617686e-01 7.691157e-01 [145,] 0.2608620465 5.217241e-01 7.391380e-01 [146,] 0.2895959557 5.791919e-01 7.104040e-01 [147,] 0.3076947595 6.153895e-01 6.923052e-01 [148,] 0.3114964023 6.229928e-01 6.885036e-01 [149,] 0.3025217363 6.050435e-01 6.974783e-01 [150,] 0.2935820625 5.871641e-01 7.064179e-01 [151,] 0.2801681834 5.603364e-01 7.198318e-01 [152,] 0.2717728525 5.435457e-01 7.282271e-01 [153,] 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3.180069e-01 8.409965e-01 [197,] 0.1565048241 3.130096e-01 8.434952e-01 [198,] 0.1542521192 3.085042e-01 8.457479e-01 [199,] 0.1550741088 3.101482e-01 8.449259e-01 [200,] 0.1602153201 3.204306e-01 8.397847e-01 [201,] 0.1675417533 3.350835e-01 8.324582e-01 [202,] 0.1836534218 3.673068e-01 8.163466e-01 [203,] 0.1955618994 3.911238e-01 8.044381e-01 [204,] 0.2052075852 4.104152e-01 7.947924e-01 [205,] 0.2121080919 4.242162e-01 7.878919e-01 [206,] 0.2019461116 4.038922e-01 7.980539e-01 [207,] 0.1982625163 3.965250e-01 8.017375e-01 [208,] 0.1925499873 3.851000e-01 8.074500e-01 [209,] 0.1887610062 3.775220e-01 8.112390e-01 [210,] 0.1818081179 3.636162e-01 8.181919e-01 [211,] 0.1787427938 3.574856e-01 8.212572e-01 [212,] 0.1755998364 3.511997e-01 8.244002e-01 [213,] 0.1758255338 3.516511e-01 8.241745e-01 [214,] 0.1781502164 3.563004e-01 8.218498e-01 [215,] 0.1805046686 3.610093e-01 8.194953e-01 [216,] 0.1801997540 3.603995e-01 8.198002e-01 [217,] 0.1807622479 3.615245e-01 8.192378e-01 [218,] 0.1654172638 3.308345e-01 8.345827e-01 [219,] 0.1527425050 3.054850e-01 8.472575e-01 [220,] 0.1407507343 2.815015e-01 8.592493e-01 [221,] 0.1271642568 2.543285e-01 8.728357e-01 [222,] 0.1141597510 2.283195e-01 8.858402e-01 [223,] 0.1036894031 2.073788e-01 8.963106e-01 [224,] 0.0966989070 1.933978e-01 9.033011e-01 [225,] 0.0976468136 1.952936e-01 9.023532e-01 [226,] 0.0950859038 1.901718e-01 9.049141e-01 [227,] 0.0960098721 1.920197e-01 9.039901e-01 [228,] 0.0978245713 1.956491e-01 9.021754e-01 [229,] 0.0986679118 1.973358e-01 9.013321e-01 [230,] 0.0878824125 1.757648e-01 9.121176e-01 [231,] 0.0804478698 1.608957e-01 9.195521e-01 [232,] 0.0758266300 1.516533e-01 9.241734e-01 [233,] 0.0719177340 1.438355e-01 9.280823e-01 [234,] 0.0668428556 1.336857e-01 9.331571e-01 [235,] 0.0647481391 1.294963e-01 9.352519e-01 [236,] 0.0666245254 1.332491e-01 9.333755e-01 [237,] 0.0810369498 1.620739e-01 9.189631e-01 [238,] 0.1010990014 2.021980e-01 8.989010e-01 [239,] 0.1217111061 2.434222e-01 8.782889e-01 [240,] 0.1314525901 2.629052e-01 8.685474e-01 [241,] 0.1419330867 2.838662e-01 8.580669e-01 [242,] 0.1471884029 2.943768e-01 8.528116e-01 [243,] 0.1540579405 3.081159e-01 8.459421e-01 [244,] 0.1620539933 3.241080e-01 8.379460e-01 [245,] 0.1618226447 3.236453e-01 8.381774e-01 [246,] 0.1590537931 3.181076e-01 8.409462e-01 [247,] 0.1756447376 3.512895e-01 8.243553e-01 [248,] 0.2019039685 4.038079e-01 7.980960e-01 [249,] 0.2393619872 4.787240e-01 7.606380e-01 [250,] 0.2565730962 5.131462e-01 7.434269e-01 [251,] 0.2610919272 5.221839e-01 7.389081e-01 [252,] 0.2474863633 4.949727e-01 7.525136e-01 [253,] 0.2298038954 4.596078e-01 7.701961e-01 [254,] 0.2132119791 4.264240e-01 7.867880e-01 [255,] 0.1974780229 3.949560e-01 8.025220e-01 [256,] 0.1817145520 3.634291e-01 8.182854e-01 [257,] 0.1680693231 3.361386e-01 8.319307e-01 [258,] 0.1555630374 3.111261e-01 8.444370e-01 [259,] 0.1459494320 2.918989e-01 8.540506e-01 [260,] 0.1366876875 2.733754e-01 8.633123e-01 [261,] 0.1295042166 2.590084e-01 8.704958e-01 [262,] 0.1207209432 2.414419e-01 8.792791e-01 [263,] 0.1113863634 2.227727e-01 8.886136e-01 [264,] 0.1016804884 2.033610e-01 8.983195e-01 [265,] 0.0917034700 1.834069e-01 9.082965e-01 [266,] 0.0869963825 1.739928e-01 9.130036e-01 [267,] 0.0837441927 1.674884e-01 9.162558e-01 [268,] 0.0818716292 1.637433e-01 9.181284e-01 [269,] 0.0783414979 1.566830e-01 9.216585e-01 [270,] 0.0732312346 1.464625e-01 9.267688e-01 [271,] 0.0692070940 1.384142e-01 9.307929e-01 [272,] 0.0632425341 1.264851e-01 9.367575e-01 [273,] 0.0574063195 1.148126e-01 9.425937e-01 [274,] 0.0505402513 1.010805e-01 9.494597e-01 [275,] 0.0450575854 9.011517e-02 9.549424e-01 [276,] 0.0401210757 8.024215e-02 9.598789e-01 [277,] 0.0351106809 7.022136e-02 9.648893e-01 [278,] 0.0317911964 6.358239e-02 9.682088e-01 [279,] 0.0284971075 5.699422e-02 9.715029e-01 [280,] 0.0257816144 5.156323e-02 9.742184e-01 [281,] 0.0229065878 4.581318e-02 9.770934e-01 [282,] 0.0206382484 4.127650e-02 9.793618e-01 [283,] 0.0166384099 3.327682e-02 9.833616e-01 [284,] 0.0130780387 2.615608e-02 9.869220e-01 [285,] 0.0102428518 2.048570e-02 9.897571e-01 [286,] 0.0078958995 1.579180e-02 9.921041e-01 [287,] 0.0060207331 1.204147e-02 9.939793e-01 [288,] 0.0045610769 9.122154e-03 9.954389e-01 [289,] 0.0034188288 6.837658e-03 9.965812e-01 [290,] 0.0025329454 5.065891e-03 9.974671e-01 [291,] 0.0018495379 3.699076e-03 9.981505e-01 [292,] 0.0013342687 2.668537e-03 9.986657e-01 [293,] 0.0009591962 1.918392e-03 9.990408e-01 [294,] 0.0006758950 1.351790e-03 9.993241e-01 [295,] 0.0004706901 9.413803e-04 9.995293e-01 [296,] 0.0003237508 6.475016e-04 9.996762e-01 [297,] 0.0011417145 2.283429e-03 9.988583e-01 [298,] 0.0039480447 7.896089e-03 9.960520e-01 [299,] 0.0163116121 3.262322e-02 9.836884e-01 [300,] 0.0514235184 1.028470e-01 9.485765e-01 [301,] 0.1353553367 2.707107e-01 8.646447e-01 [302,] 0.3131888107 6.263776e-01 6.868112e-01 [303,] 0.6045383893 7.909232e-01 3.954616e-01 [304,] 0.9071633167 1.856734e-01 9.283668e-02 [305,] 0.9890880912 2.182382e-02 1.091191e-02 [306,] 0.9998823591 2.352817e-04 1.176409e-04 [307,] 0.9999998980 2.040957e-07 1.020478e-07 [308,] 1.0000000000 6.767502e-12 3.383751e-12 [309,] 1.0000000000 1.387793e-12 6.938964e-13 [310,] 1.0000000000 5.710319e-13 2.855160e-13 [311,] 1.0000000000 1.420972e-12 7.104858e-13 [312,] 1.0000000000 2.879773e-12 1.439886e-12 [313,] 1.0000000000 1.996379e-12 9.981897e-13 [314,] 1.0000000000 3.786885e-12 1.893442e-12 [315,] 1.0000000000 1.201861e-11 6.009307e-12 [316,] 1.0000000000 3.688055e-11 1.844027e-11 [317,] 0.9999999999 1.253157e-10 6.265785e-11 [318,] 0.9999999998 4.173305e-10 2.086653e-10 [319,] 0.9999999996 7.931007e-10 3.965504e-10 [320,] 0.9999999990 2.042188e-09 1.021094e-09 [321,] 0.9999999967 6.671870e-09 3.335935e-09 [322,] 0.9999999935 1.290970e-08 6.454848e-09 [323,] 0.9999999933 1.347304e-08 6.736522e-09 [324,] 0.9999999814 3.726277e-08 1.863138e-08 [325,] 0.9999999890 2.190908e-08 1.095454e-08 [326,] 0.9999999772 4.569210e-08 2.284605e-08 [327,] 0.9999999302 1.395425e-07 6.977124e-08 [328,] 0.9999997429 5.142548e-07 2.571274e-07 [329,] 0.9999992717 1.456689e-06 7.283444e-07 [330,] 0.9999975728 4.854355e-06 2.427178e-06 [331,] 0.9999904882 1.902355e-05 9.511775e-06 [332,] 0.9999617310 7.653809e-05 3.826904e-05 [333,] 0.9998654620 2.690759e-04 1.345380e-04 [334,] 0.9998971499 2.057003e-04 1.028501e-04 [335,] 0.9997733630 4.532741e-04 2.266370e-04 [336,] 0.9991589806 1.682039e-03 8.410194e-04 [337,] 0.9963897746 7.220451e-03 3.610225e-03 [338,] 0.9953037555 9.392489e-03 4.696245e-03 [339,] 0.9787022526 4.259549e-02 2.129775e-02 > postscript(file="/var/www/html/rcomp/tmp/1vwe31291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2vwe31291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 372 Frequency = 1 1 2 3 4 5 -65.67900831 -29.97578251 -23.80804057 -8.78545993 -27.54675025 6 7 8 9 10 -60.87255670 -37.80158896 -23.95642767 -24.54997606 -40.50804057 11 12 13 14 15 -33.97900831 -19.24675025 -7.72233033 30.28089548 43.44863741 16 17 18 19 20 71.77121806 116.20992773 88.48412128 153.45508903 141.40025032 21 22 23 24 25 126.40670193 157.14863741 113.27766967 122.80992773 151.13434766 26 27 28 29 30 155.53757346 130.00531540 104.12789604 84.46660572 40.54079927 31 32 33 34 35 39.81176701 0.65692830 5.46337991 -22.59468460 -14.56565234 36 37 38 39 40 -11.73339428 -55.20897436 -76.20574855 -75.43800662 -75.01542597 41 42 43 44 45 -71.27671629 -107.80252275 -91.03155500 -86.48639371 -61.37994210 46 47 48 49 50 -59.13800662 -57.60897436 -79.47671629 -100.75229637 -102.44907057 51 52 53 54 55 -113.98132863 -91.65874799 -76.52003831 -124.24584476 -96.17487702 56 57 58 59 60 -81.72971573 -83.62326412 -92.98132863 -103.65229637 -111.02003831 61 62 63 64 65 -119.79561839 -146.49239258 -137.82465065 -105.30207000 -107.56336032 66 67 68 69 70 -160.68916678 -140.11819903 -128.77303774 -100.96658613 -90.22465065 71 72 73 74 75 -67.79561839 -35.56336032 16.66105960 48.96428540 76.63202734 76 77 78 79 80 96.45460798 98.19331766 27.76751121 50.33847895 60.58364024 81 82 83 84 85 73.99009185 39.03202734 35.56105960 22.49331766 21.01773758 86 87 88 89 90 1.12096339 -3.81129468 21.61128597 -5.05000435 -57.47581080 91 92 93 94 95 -57.80484306 -39.25968177 -41.95323016 -31.91129468 -28.78226242 96 97 98 99 100 -24.75000435 -45.72558443 -53.02235863 -30.45461669 -30.03203605 101 102 103 104 105 -0.59332637 -35.31913282 -32.04816508 -52.60300379 -54.89655217 106 107 108 109 110 -57.65461669 -28.92558443 -25.29332637 -38.16890645 -60.16568064 111 112 113 114 115 -64.19793871 -44.77535806 -23.43664838 -46.56245483 -52.59148709 116 117 118 119 120 -53.14632580 -38.33987419 -26.69793871 17.43109355 35.46335162 121 122 123 124 125 81.18777154 136.49099734 162.65873928 192.48131993 189.82002960 126 127 128 129 130 156.19422315 166.46519089 148.51035218 110.71680380 95.35873928 131 132 133 134 135 76.78777154 102.62002960 96.14444952 88.24767533 70.51541727 136 137 138 139 140 35.43799791 32.87670759 5.45090114 10.72186888 16.06703017 141 142 143 144 145 17.97348178 37.01541727 55.44444952 41.47670759 33.80112751 146 147 148 149 150 0.60435332 50.67209525 33.89467590 31.73338557 38.20757912 151 152 153 154 155 32.17854686 46.02370815 23.53015977 61.17209525 82.10112751 156 157 158 159 160 129.93338557 148.95780549 170.96103130 170.12877324 155.45135388 161 162 163 164 165 154.39006356 145.86425711 133.43522485 112.48038614 88.98683775 166 167 168 169 170 87.32877324 73.05780549 80.59006356 71.11448348 47.21770929 171 172 173 174 175 53.68545122 46.60803187 76.04674154 30.02093509 13.79190283 176 177 178 179 180 46.23706412 24.64351574 17.98545122 45.11448348 46.04674154 181 182 183 184 185 65.27116146 79.67438727 59.14212921 53.16470985 69.30341953 186 187 188 189 190 57.07761308 38.44858082 31.09374211 19.70019372 27.54212921 191 192 193 194 195 51.87116146 42.40341953 47.92783945 32.33106526 30.99880719 196 197 198 199 200 30.52138784 20.76009751 40.53429106 -14.49474120 4.25042009 201 202 203 204 205 -7.54312829 1.49880719 -8.57216055 -1.93990249 -16.21548256 206 207 208 209 210 -3.01225676 -28.04451482 -9.82193418 -17.08322450 -5.50903095 211 212 213 214 215 -45.53806321 -40.79290192 -55.98645031 -53.84451482 -58.01548256 216 217 218 219 220 -70.48322450 -92.35880458 -115.75557877 -105.38783684 -92.46525619 221 222 223 224 225 -65.62654652 -58.45235297 -89.88138522 -81.63622393 -96.32977232 226 227 228 229 230 -84.68783684 -95.35880458 -89.22654652 -107.30212659 -114.69890079 231 232 233 234 235 -115.43115885 -105.50857821 -105.56986853 -61.29567498 -76.42470724 236 237 238 239 240 -75.97954595 -63.57309434 -42.43115885 -69.40212659 -90.16986853 241 242 243 244 245 -122.24544861 -110.84222280 -124.37448087 -129.25190022 -127.41319054 246 247 248 249 250 -69.03899700 -86.06802925 -99.42286796 -98.81641635 -93.07448087 251 252 253 254 255 -108.54544861 -126.81319054 -148.58877062 -153.68554482 -149.01780288 256 257 258 259 260 -130.59522224 -134.25651256 -97.98231901 -96.01135127 -96.06618998 261 262 263 264 265 -70.15973837 -66.51780288 -101.58877062 -112.35651256 -101.93209264 266 267 268 269 270 -73.02886683 -56.86112490 -36.03854425 -32.29983457 23.47435897 271 272 273 274 275 30.34532672 32.49048801 56.79693962 68.93887510 81.66790736 276 277 278 279 280 82.10016543 92.42458535 85.32781115 80.89555309 71.71813373 281 282 283 284 285 62.25684341 99.13103696 105.90200470 110.14716599 105.15361760 286 287 288 289 290 93.59555309 96.02458535 81.55684341 89.28126333 75.88448914 291 292 293 294 295 78.45223107 65.57481172 50.81352140 86.28771494 83.75868269 296 297 298 299 300 83.30384398 80.51029559 77.15223107 34.68126333 17.21352140 301 302 303 304 305 5.63794132 12.74116712 1.70890906 6.83148970 -10.12980062 306 307 308 309 310 21.94439293 15.01536067 11.96052196 24.76697358 0.00890906 311 312 313 314 315 7.23794132 4.97019938 -188.22658178 -184.92335597 -201.15561404 316 317 318 319 320 -207.63303339 -202.79432371 -151.92013016 -141.14916242 -147.50400113 321 322 323 324 325 -98.69754952 -99.05561404 -57.02658178 -17.39432371 122.53009621 326 327 328 329 330 125.53332201 152.80106395 137.82364460 138.66235427 160.53654782 331 332 333 334 335 147.30751556 127.15267685 126.85912847 114.50106395 91.13009621 336 337 338 339 340 85.06235427 115.48677419 91.49000000 62.95774194 38.38032258 341 342 343 344 345 0.31903226 62.69322581 77.66419355 83.30935484 70.81580645 346 347 348 349 350 66.95774194 71.08677419 61.31903226 76.44345218 92.64667799 351 352 353 354 355 59.61441992 -0.26299943 -21.42428976 36.04990379 7.62087153 356 357 358 359 360 20.36603282 5.47248444 -0.68558008 -10.25654782 -59.32428976 361 362 363 364 365 -25.09986984 -50.79664403 -54.52890209 -94.70632145 -97.26761177 366 367 368 369 370 -83.09341822 -49.12245048 -68.67728919 -64.97083758 -83.22890209 371 372 -88.39986984 -81.26761177 > postscript(file="/var/www/html/rcomp/tmp/6m0kx1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 372 Frequency = 1 lag(myerror, k = 1) myerror 0 -65.67900831 NA 1 -29.97578251 -65.67900831 2 -23.80804057 -29.97578251 3 -8.78545993 -23.80804057 4 -27.54675025 -8.78545993 5 -60.87255670 -27.54675025 6 -37.80158896 -60.87255670 7 -23.95642767 -37.80158896 8 -24.54997606 -23.95642767 9 -40.50804057 -24.54997606 10 -33.97900831 -40.50804057 11 -19.24675025 -33.97900831 12 -7.72233033 -19.24675025 13 30.28089548 -7.72233033 14 43.44863741 30.28089548 15 71.77121806 43.44863741 16 116.20992773 71.77121806 17 88.48412128 116.20992773 18 153.45508903 88.48412128 19 141.40025032 153.45508903 20 126.40670193 141.40025032 21 157.14863741 126.40670193 22 113.27766967 157.14863741 23 122.80992773 113.27766967 24 151.13434766 122.80992773 25 155.53757346 151.13434766 26 130.00531540 155.53757346 27 104.12789604 130.00531540 28 84.46660572 104.12789604 29 40.54079927 84.46660572 30 39.81176701 40.54079927 31 0.65692830 39.81176701 32 5.46337991 0.65692830 33 -22.59468460 5.46337991 34 -14.56565234 -22.59468460 35 -11.73339428 -14.56565234 36 -55.20897436 -11.73339428 37 -76.20574855 -55.20897436 38 -75.43800662 -76.20574855 39 -75.01542597 -75.43800662 40 -71.27671629 -75.01542597 41 -107.80252275 -71.27671629 42 -91.03155500 -107.80252275 43 -86.48639371 -91.03155500 44 -61.37994210 -86.48639371 45 -59.13800662 -61.37994210 46 -57.60897436 -59.13800662 47 -79.47671629 -57.60897436 48 -100.75229637 -79.47671629 49 -102.44907057 -100.75229637 50 -113.98132863 -102.44907057 51 -91.65874799 -113.98132863 52 -76.52003831 -91.65874799 53 -124.24584476 -76.52003831 54 -96.17487702 -124.24584476 55 -81.72971573 -96.17487702 56 -83.62326412 -81.72971573 57 -92.98132863 -83.62326412 58 -103.65229637 -92.98132863 59 -111.02003831 -103.65229637 60 -119.79561839 -111.02003831 61 -146.49239258 -119.79561839 62 -137.82465065 -146.49239258 63 -105.30207000 -137.82465065 64 -107.56336032 -105.30207000 65 -160.68916678 -107.56336032 66 -140.11819903 -160.68916678 67 -128.77303774 -140.11819903 68 -100.96658613 -128.77303774 69 -90.22465065 -100.96658613 70 -67.79561839 -90.22465065 71 -35.56336032 -67.79561839 72 16.66105960 -35.56336032 73 48.96428540 16.66105960 74 76.63202734 48.96428540 75 96.45460798 76.63202734 76 98.19331766 96.45460798 77 27.76751121 98.19331766 78 50.33847895 27.76751121 79 60.58364024 50.33847895 80 73.99009185 60.58364024 81 39.03202734 73.99009185 82 35.56105960 39.03202734 83 22.49331766 35.56105960 84 21.01773758 22.49331766 85 1.12096339 21.01773758 86 -3.81129468 1.12096339 87 21.61128597 -3.81129468 88 -5.05000435 21.61128597 89 -57.47581080 -5.05000435 90 -57.80484306 -57.47581080 91 -39.25968177 -57.80484306 92 -41.95323016 -39.25968177 93 -31.91129468 -41.95323016 94 -28.78226242 -31.91129468 95 -24.75000435 -28.78226242 96 -45.72558443 -24.75000435 97 -53.02235863 -45.72558443 98 -30.45461669 -53.02235863 99 -30.03203605 -30.45461669 100 -0.59332637 -30.03203605 101 -35.31913282 -0.59332637 102 -32.04816508 -35.31913282 103 -52.60300379 -32.04816508 104 -54.89655217 -52.60300379 105 -57.65461669 -54.89655217 106 -28.92558443 -57.65461669 107 -25.29332637 -28.92558443 108 -38.16890645 -25.29332637 109 -60.16568064 -38.16890645 110 -64.19793871 -60.16568064 111 -44.77535806 -64.19793871 112 -23.43664838 -44.77535806 113 -46.56245483 -23.43664838 114 -52.59148709 -46.56245483 115 -53.14632580 -52.59148709 116 -38.33987419 -53.14632580 117 -26.69793871 -38.33987419 118 17.43109355 -26.69793871 119 35.46335162 17.43109355 120 81.18777154 35.46335162 121 136.49099734 81.18777154 122 162.65873928 136.49099734 123 192.48131993 162.65873928 124 189.82002960 192.48131993 125 156.19422315 189.82002960 126 166.46519089 156.19422315 127 148.51035218 166.46519089 128 110.71680380 148.51035218 129 95.35873928 110.71680380 130 76.78777154 95.35873928 131 102.62002960 76.78777154 132 96.14444952 102.62002960 133 88.24767533 96.14444952 134 70.51541727 88.24767533 135 35.43799791 70.51541727 136 32.87670759 35.43799791 137 5.45090114 32.87670759 138 10.72186888 5.45090114 139 16.06703017 10.72186888 140 17.97348178 16.06703017 141 37.01541727 17.97348178 142 55.44444952 37.01541727 143 41.47670759 55.44444952 144 33.80112751 41.47670759 145 0.60435332 33.80112751 146 50.67209525 0.60435332 147 33.89467590 50.67209525 148 31.73338557 33.89467590 149 38.20757912 31.73338557 150 32.17854686 38.20757912 151 46.02370815 32.17854686 152 23.53015977 46.02370815 153 61.17209525 23.53015977 154 82.10112751 61.17209525 155 129.93338557 82.10112751 156 148.95780549 129.93338557 157 170.96103130 148.95780549 158 170.12877324 170.96103130 159 155.45135388 170.12877324 160 154.39006356 155.45135388 161 145.86425711 154.39006356 162 133.43522485 145.86425711 163 112.48038614 133.43522485 164 88.98683775 112.48038614 165 87.32877324 88.98683775 166 73.05780549 87.32877324 167 80.59006356 73.05780549 168 71.11448348 80.59006356 169 47.21770929 71.11448348 170 53.68545122 47.21770929 171 46.60803187 53.68545122 172 76.04674154 46.60803187 173 30.02093509 76.04674154 174 13.79190283 30.02093509 175 46.23706412 13.79190283 176 24.64351574 46.23706412 177 17.98545122 24.64351574 178 45.11448348 17.98545122 179 46.04674154 45.11448348 180 65.27116146 46.04674154 181 79.67438727 65.27116146 182 59.14212921 79.67438727 183 53.16470985 59.14212921 184 69.30341953 53.16470985 185 57.07761308 69.30341953 186 38.44858082 57.07761308 187 31.09374211 38.44858082 188 19.70019372 31.09374211 189 27.54212921 19.70019372 190 51.87116146 27.54212921 191 42.40341953 51.87116146 192 47.92783945 42.40341953 193 32.33106526 47.92783945 194 30.99880719 32.33106526 195 30.52138784 30.99880719 196 20.76009751 30.52138784 197 40.53429106 20.76009751 198 -14.49474120 40.53429106 199 4.25042009 -14.49474120 200 -7.54312829 4.25042009 201 1.49880719 -7.54312829 202 -8.57216055 1.49880719 203 -1.93990249 -8.57216055 204 -16.21548256 -1.93990249 205 -3.01225676 -16.21548256 206 -28.04451482 -3.01225676 207 -9.82193418 -28.04451482 208 -17.08322450 -9.82193418 209 -5.50903095 -17.08322450 210 -45.53806321 -5.50903095 211 -40.79290192 -45.53806321 212 -55.98645031 -40.79290192 213 -53.84451482 -55.98645031 214 -58.01548256 -53.84451482 215 -70.48322450 -58.01548256 216 -92.35880458 -70.48322450 217 -115.75557877 -92.35880458 218 -105.38783684 -115.75557877 219 -92.46525619 -105.38783684 220 -65.62654652 -92.46525619 221 -58.45235297 -65.62654652 222 -89.88138522 -58.45235297 223 -81.63622393 -89.88138522 224 -96.32977232 -81.63622393 225 -84.68783684 -96.32977232 226 -95.35880458 -84.68783684 227 -89.22654652 -95.35880458 228 -107.30212659 -89.22654652 229 -114.69890079 -107.30212659 230 -115.43115885 -114.69890079 231 -105.50857821 -115.43115885 232 -105.56986853 -105.50857821 233 -61.29567498 -105.56986853 234 -76.42470724 -61.29567498 235 -75.97954595 -76.42470724 236 -63.57309434 -75.97954595 237 -42.43115885 -63.57309434 238 -69.40212659 -42.43115885 239 -90.16986853 -69.40212659 240 -122.24544861 -90.16986853 241 -110.84222280 -122.24544861 242 -124.37448087 -110.84222280 243 -129.25190022 -124.37448087 244 -127.41319054 -129.25190022 245 -69.03899700 -127.41319054 246 -86.06802925 -69.03899700 247 -99.42286796 -86.06802925 248 -98.81641635 -99.42286796 249 -93.07448087 -98.81641635 250 -108.54544861 -93.07448087 251 -126.81319054 -108.54544861 252 -148.58877062 -126.81319054 253 -153.68554482 -148.58877062 254 -149.01780288 -153.68554482 255 -130.59522224 -149.01780288 256 -134.25651256 -130.59522224 257 -97.98231901 -134.25651256 258 -96.01135127 -97.98231901 259 -96.06618998 -96.01135127 260 -70.15973837 -96.06618998 261 -66.51780288 -70.15973837 262 -101.58877062 -66.51780288 263 -112.35651256 -101.58877062 264 -101.93209264 -112.35651256 265 -73.02886683 -101.93209264 266 -56.86112490 -73.02886683 267 -36.03854425 -56.86112490 268 -32.29983457 -36.03854425 269 23.47435897 -32.29983457 270 30.34532672 23.47435897 271 32.49048801 30.34532672 272 56.79693962 32.49048801 273 68.93887510 56.79693962 274 81.66790736 68.93887510 275 82.10016543 81.66790736 276 92.42458535 82.10016543 277 85.32781115 92.42458535 278 80.89555309 85.32781115 279 71.71813373 80.89555309 280 62.25684341 71.71813373 281 99.13103696 62.25684341 282 105.90200470 99.13103696 283 110.14716599 105.90200470 284 105.15361760 110.14716599 285 93.59555309 105.15361760 286 96.02458535 93.59555309 287 81.55684341 96.02458535 288 89.28126333 81.55684341 289 75.88448914 89.28126333 290 78.45223107 75.88448914 291 65.57481172 78.45223107 292 50.81352140 65.57481172 293 86.28771494 50.81352140 294 83.75868269 86.28771494 295 83.30384398 83.75868269 296 80.51029559 83.30384398 297 77.15223107 80.51029559 298 34.68126333 77.15223107 299 17.21352140 34.68126333 300 5.63794132 17.21352140 301 12.74116712 5.63794132 302 1.70890906 12.74116712 303 6.83148970 1.70890906 304 -10.12980062 6.83148970 305 21.94439293 -10.12980062 306 15.01536067 21.94439293 307 11.96052196 15.01536067 308 24.76697358 11.96052196 309 0.00890906 24.76697358 310 7.23794132 0.00890906 311 4.97019938 7.23794132 312 -188.22658178 4.97019938 313 -184.92335597 -188.22658178 314 -201.15561404 -184.92335597 315 -207.63303339 -201.15561404 316 -202.79432371 -207.63303339 317 -151.92013016 -202.79432371 318 -141.14916242 -151.92013016 319 -147.50400113 -141.14916242 320 -98.69754952 -147.50400113 321 -99.05561404 -98.69754952 322 -57.02658178 -99.05561404 323 -17.39432371 -57.02658178 324 122.53009621 -17.39432371 325 125.53332201 122.53009621 326 152.80106395 125.53332201 327 137.82364460 152.80106395 328 138.66235427 137.82364460 329 160.53654782 138.66235427 330 147.30751556 160.53654782 331 127.15267685 147.30751556 332 126.85912847 127.15267685 333 114.50106395 126.85912847 334 91.13009621 114.50106395 335 85.06235427 91.13009621 336 115.48677419 85.06235427 337 91.49000000 115.48677419 338 62.95774194 91.49000000 339 38.38032258 62.95774194 340 0.31903226 38.38032258 341 62.69322581 0.31903226 342 77.66419355 62.69322581 343 83.30935484 77.66419355 344 70.81580645 83.30935484 345 66.95774194 70.81580645 346 71.08677419 66.95774194 347 61.31903226 71.08677419 348 76.44345218 61.31903226 349 92.64667799 76.44345218 350 59.61441992 92.64667799 351 -0.26299943 59.61441992 352 -21.42428976 -0.26299943 353 36.04990379 -21.42428976 354 7.62087153 36.04990379 355 20.36603282 7.62087153 356 5.47248444 20.36603282 357 -0.68558008 5.47248444 358 -10.25654782 -0.68558008 359 -59.32428976 -10.25654782 360 -25.09986984 -59.32428976 361 -50.79664403 -25.09986984 362 -54.52890209 -50.79664403 363 -94.70632145 -54.52890209 364 -97.26761177 -94.70632145 365 -83.09341822 -97.26761177 366 -49.12245048 -83.09341822 367 -68.67728919 -49.12245048 368 -64.97083758 -68.67728919 369 -83.22890209 -64.97083758 370 -88.39986984 -83.22890209 371 -81.26761177 -88.39986984 372 NA -81.26761177 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -29.97578251 -65.67900831 [2,] -23.80804057 -29.97578251 [3,] -8.78545993 -23.80804057 [4,] -27.54675025 -8.78545993 [5,] -60.87255670 -27.54675025 [6,] -37.80158896 -60.87255670 [7,] -23.95642767 -37.80158896 [8,] -24.54997606 -23.95642767 [9,] -40.50804057 -24.54997606 [10,] -33.97900831 -40.50804057 [11,] -19.24675025 -33.97900831 [12,] -7.72233033 -19.24675025 [13,] 30.28089548 -7.72233033 [14,] 43.44863741 30.28089548 [15,] 71.77121806 43.44863741 [16,] 116.20992773 71.77121806 [17,] 88.48412128 116.20992773 [18,] 153.45508903 88.48412128 [19,] 141.40025032 153.45508903 [20,] 126.40670193 141.40025032 [21,] 157.14863741 126.40670193 [22,] 113.27766967 157.14863741 [23,] 122.80992773 113.27766967 [24,] 151.13434766 122.80992773 [25,] 155.53757346 151.13434766 [26,] 130.00531540 155.53757346 [27,] 104.12789604 130.00531540 [28,] 84.46660572 104.12789604 [29,] 40.54079927 84.46660572 [30,] 39.81176701 40.54079927 [31,] 0.65692830 39.81176701 [32,] 5.46337991 0.65692830 [33,] -22.59468460 5.46337991 [34,] -14.56565234 -22.59468460 [35,] -11.73339428 -14.56565234 [36,] -55.20897436 -11.73339428 [37,] -76.20574855 -55.20897436 [38,] -75.43800662 -76.20574855 [39,] -75.01542597 -75.43800662 [40,] -71.27671629 -75.01542597 [41,] -107.80252275 -71.27671629 [42,] -91.03155500 -107.80252275 [43,] -86.48639371 -91.03155500 [44,] -61.37994210 -86.48639371 [45,] -59.13800662 -61.37994210 [46,] -57.60897436 -59.13800662 [47,] -79.47671629 -57.60897436 [48,] -100.75229637 -79.47671629 [49,] -102.44907057 -100.75229637 [50,] -113.98132863 -102.44907057 [51,] -91.65874799 -113.98132863 [52,] -76.52003831 -91.65874799 [53,] -124.24584476 -76.52003831 [54,] -96.17487702 -124.24584476 [55,] -81.72971573 -96.17487702 [56,] -83.62326412 -81.72971573 [57,] -92.98132863 -83.62326412 [58,] -103.65229637 -92.98132863 [59,] -111.02003831 -103.65229637 [60,] -119.79561839 -111.02003831 [61,] -146.49239258 -119.79561839 [62,] -137.82465065 -146.49239258 [63,] -105.30207000 -137.82465065 [64,] -107.56336032 -105.30207000 [65,] -160.68916678 -107.56336032 [66,] -140.11819903 -160.68916678 [67,] -128.77303774 -140.11819903 [68,] -100.96658613 -128.77303774 [69,] -90.22465065 -100.96658613 [70,] -67.79561839 -90.22465065 [71,] -35.56336032 -67.79561839 [72,] 16.66105960 -35.56336032 [73,] 48.96428540 16.66105960 [74,] 76.63202734 48.96428540 [75,] 96.45460798 76.63202734 [76,] 98.19331766 96.45460798 [77,] 27.76751121 98.19331766 [78,] 50.33847895 27.76751121 [79,] 60.58364024 50.33847895 [80,] 73.99009185 60.58364024 [81,] 39.03202734 73.99009185 [82,] 35.56105960 39.03202734 [83,] 22.49331766 35.56105960 [84,] 21.01773758 22.49331766 [85,] 1.12096339 21.01773758 [86,] -3.81129468 1.12096339 [87,] 21.61128597 -3.81129468 [88,] -5.05000435 21.61128597 [89,] -57.47581080 -5.05000435 [90,] -57.80484306 -57.47581080 [91,] -39.25968177 -57.80484306 [92,] -41.95323016 -39.25968177 [93,] -31.91129468 -41.95323016 [94,] -28.78226242 -31.91129468 [95,] -24.75000435 -28.78226242 [96,] -45.72558443 -24.75000435 [97,] -53.02235863 -45.72558443 [98,] -30.45461669 -53.02235863 [99,] -30.03203605 -30.45461669 [100,] -0.59332637 -30.03203605 [101,] -35.31913282 -0.59332637 [102,] -32.04816508 -35.31913282 [103,] -52.60300379 -32.04816508 [104,] -54.89655217 -52.60300379 [105,] -57.65461669 -54.89655217 [106,] -28.92558443 -57.65461669 [107,] -25.29332637 -28.92558443 [108,] -38.16890645 -25.29332637 [109,] -60.16568064 -38.16890645 [110,] -64.19793871 -60.16568064 [111,] -44.77535806 -64.19793871 [112,] -23.43664838 -44.77535806 [113,] -46.56245483 -23.43664838 [114,] -52.59148709 -46.56245483 [115,] -53.14632580 -52.59148709 [116,] -38.33987419 -53.14632580 [117,] -26.69793871 -38.33987419 [118,] 17.43109355 -26.69793871 [119,] 35.46335162 17.43109355 [120,] 81.18777154 35.46335162 [121,] 136.49099734 81.18777154 [122,] 162.65873928 136.49099734 [123,] 192.48131993 162.65873928 [124,] 189.82002960 192.48131993 [125,] 156.19422315 189.82002960 [126,] 166.46519089 156.19422315 [127,] 148.51035218 166.46519089 [128,] 110.71680380 148.51035218 [129,] 95.35873928 110.71680380 [130,] 76.78777154 95.35873928 [131,] 102.62002960 76.78777154 [132,] 96.14444952 102.62002960 [133,] 88.24767533 96.14444952 [134,] 70.51541727 88.24767533 [135,] 35.43799791 70.51541727 [136,] 32.87670759 35.43799791 [137,] 5.45090114 32.87670759 [138,] 10.72186888 5.45090114 [139,] 16.06703017 10.72186888 [140,] 17.97348178 16.06703017 [141,] 37.01541727 17.97348178 [142,] 55.44444952 37.01541727 [143,] 41.47670759 55.44444952 [144,] 33.80112751 41.47670759 [145,] 0.60435332 33.80112751 [146,] 50.67209525 0.60435332 [147,] 33.89467590 50.67209525 [148,] 31.73338557 33.89467590 [149,] 38.20757912 31.73338557 [150,] 32.17854686 38.20757912 [151,] 46.02370815 32.17854686 [152,] 23.53015977 46.02370815 [153,] 61.17209525 23.53015977 [154,] 82.10112751 61.17209525 [155,] 129.93338557 82.10112751 [156,] 148.95780549 129.93338557 [157,] 170.96103130 148.95780549 [158,] 170.12877324 170.96103130 [159,] 155.45135388 170.12877324 [160,] 154.39006356 155.45135388 [161,] 145.86425711 154.39006356 [162,] 133.43522485 145.86425711 [163,] 112.48038614 133.43522485 [164,] 88.98683775 112.48038614 [165,] 87.32877324 88.98683775 [166,] 73.05780549 87.32877324 [167,] 80.59006356 73.05780549 [168,] 71.11448348 80.59006356 [169,] 47.21770929 71.11448348 [170,] 53.68545122 47.21770929 [171,] 46.60803187 53.68545122 [172,] 76.04674154 46.60803187 [173,] 30.02093509 76.04674154 [174,] 13.79190283 30.02093509 [175,] 46.23706412 13.79190283 [176,] 24.64351574 46.23706412 [177,] 17.98545122 24.64351574 [178,] 45.11448348 17.98545122 [179,] 46.04674154 45.11448348 [180,] 65.27116146 46.04674154 [181,] 79.67438727 65.27116146 [182,] 59.14212921 79.67438727 [183,] 53.16470985 59.14212921 [184,] 69.30341953 53.16470985 [185,] 57.07761308 69.30341953 [186,] 38.44858082 57.07761308 [187,] 31.09374211 38.44858082 [188,] 19.70019372 31.09374211 [189,] 27.54212921 19.70019372 [190,] 51.87116146 27.54212921 [191,] 42.40341953 51.87116146 [192,] 47.92783945 42.40341953 [193,] 32.33106526 47.92783945 [194,] 30.99880719 32.33106526 [195,] 30.52138784 30.99880719 [196,] 20.76009751 30.52138784 [197,] 40.53429106 20.76009751 [198,] -14.49474120 40.53429106 [199,] 4.25042009 -14.49474120 [200,] -7.54312829 4.25042009 [201,] 1.49880719 -7.54312829 [202,] -8.57216055 1.49880719 [203,] -1.93990249 -8.57216055 [204,] -16.21548256 -1.93990249 [205,] -3.01225676 -16.21548256 [206,] -28.04451482 -3.01225676 [207,] -9.82193418 -28.04451482 [208,] -17.08322450 -9.82193418 [209,] -5.50903095 -17.08322450 [210,] -45.53806321 -5.50903095 [211,] -40.79290192 -45.53806321 [212,] -55.98645031 -40.79290192 [213,] -53.84451482 -55.98645031 [214,] -58.01548256 -53.84451482 [215,] -70.48322450 -58.01548256 [216,] -92.35880458 -70.48322450 [217,] -115.75557877 -92.35880458 [218,] -105.38783684 -115.75557877 [219,] -92.46525619 -105.38783684 [220,] -65.62654652 -92.46525619 [221,] -58.45235297 -65.62654652 [222,] -89.88138522 -58.45235297 [223,] -81.63622393 -89.88138522 [224,] -96.32977232 -81.63622393 [225,] -84.68783684 -96.32977232 [226,] -95.35880458 -84.68783684 [227,] -89.22654652 -95.35880458 [228,] -107.30212659 -89.22654652 [229,] -114.69890079 -107.30212659 [230,] -115.43115885 -114.69890079 [231,] -105.50857821 -115.43115885 [232,] -105.56986853 -105.50857821 [233,] -61.29567498 -105.56986853 [234,] -76.42470724 -61.29567498 [235,] -75.97954595 -76.42470724 [236,] -63.57309434 -75.97954595 [237,] -42.43115885 -63.57309434 [238,] -69.40212659 -42.43115885 [239,] -90.16986853 -69.40212659 [240,] -122.24544861 -90.16986853 [241,] -110.84222280 -122.24544861 [242,] -124.37448087 -110.84222280 [243,] -129.25190022 -124.37448087 [244,] -127.41319054 -129.25190022 [245,] -69.03899700 -127.41319054 [246,] -86.06802925 -69.03899700 [247,] -99.42286796 -86.06802925 [248,] -98.81641635 -99.42286796 [249,] -93.07448087 -98.81641635 [250,] -108.54544861 -93.07448087 [251,] -126.81319054 -108.54544861 [252,] -148.58877062 -126.81319054 [253,] -153.68554482 -148.58877062 [254,] -149.01780288 -153.68554482 [255,] -130.59522224 -149.01780288 [256,] -134.25651256 -130.59522224 [257,] -97.98231901 -134.25651256 [258,] -96.01135127 -97.98231901 [259,] -96.06618998 -96.01135127 [260,] -70.15973837 -96.06618998 [261,] -66.51780288 -70.15973837 [262,] -101.58877062 -66.51780288 [263,] -112.35651256 -101.58877062 [264,] -101.93209264 -112.35651256 [265,] -73.02886683 -101.93209264 [266,] -56.86112490 -73.02886683 [267,] -36.03854425 -56.86112490 [268,] -32.29983457 -36.03854425 [269,] 23.47435897 -32.29983457 [270,] 30.34532672 23.47435897 [271,] 32.49048801 30.34532672 [272,] 56.79693962 32.49048801 [273,] 68.93887510 56.79693962 [274,] 81.66790736 68.93887510 [275,] 82.10016543 81.66790736 [276,] 92.42458535 82.10016543 [277,] 85.32781115 92.42458535 [278,] 80.89555309 85.32781115 [279,] 71.71813373 80.89555309 [280,] 62.25684341 71.71813373 [281,] 99.13103696 62.25684341 [282,] 105.90200470 99.13103696 [283,] 110.14716599 105.90200470 [284,] 105.15361760 110.14716599 [285,] 93.59555309 105.15361760 [286,] 96.02458535 93.59555309 [287,] 81.55684341 96.02458535 [288,] 89.28126333 81.55684341 [289,] 75.88448914 89.28126333 [290,] 78.45223107 75.88448914 [291,] 65.57481172 78.45223107 [292,] 50.81352140 65.57481172 [293,] 86.28771494 50.81352140 [294,] 83.75868269 86.28771494 [295,] 83.30384398 83.75868269 [296,] 80.51029559 83.30384398 [297,] 77.15223107 80.51029559 [298,] 34.68126333 77.15223107 [299,] 17.21352140 34.68126333 [300,] 5.63794132 17.21352140 [301,] 12.74116712 5.63794132 [302,] 1.70890906 12.74116712 [303,] 6.83148970 1.70890906 [304,] -10.12980062 6.83148970 [305,] 21.94439293 -10.12980062 [306,] 15.01536067 21.94439293 [307,] 11.96052196 15.01536067 [308,] 24.76697358 11.96052196 [309,] 0.00890906 24.76697358 [310,] 7.23794132 0.00890906 [311,] 4.97019938 7.23794132 [312,] -188.22658178 4.97019938 [313,] -184.92335597 -188.22658178 [314,] -201.15561404 -184.92335597 [315,] -207.63303339 -201.15561404 [316,] -202.79432371 -207.63303339 [317,] -151.92013016 -202.79432371 [318,] -141.14916242 -151.92013016 [319,] -147.50400113 -141.14916242 [320,] -98.69754952 -147.50400113 [321,] -99.05561404 -98.69754952 [322,] -57.02658178 -99.05561404 [323,] -17.39432371 -57.02658178 [324,] 122.53009621 -17.39432371 [325,] 125.53332201 122.53009621 [326,] 152.80106395 125.53332201 [327,] 137.82364460 152.80106395 [328,] 138.66235427 137.82364460 [329,] 160.53654782 138.66235427 [330,] 147.30751556 160.53654782 [331,] 127.15267685 147.30751556 [332,] 126.85912847 127.15267685 [333,] 114.50106395 126.85912847 [334,] 91.13009621 114.50106395 [335,] 85.06235427 91.13009621 [336,] 115.48677419 85.06235427 [337,] 91.49000000 115.48677419 [338,] 62.95774194 91.49000000 [339,] 38.38032258 62.95774194 [340,] 0.31903226 38.38032258 [341,] 62.69322581 0.31903226 [342,] 77.66419355 62.69322581 [343,] 83.30935484 77.66419355 [344,] 70.81580645 83.30935484 [345,] 66.95774194 70.81580645 [346,] 71.08677419 66.95774194 [347,] 61.31903226 71.08677419 [348,] 76.44345218 61.31903226 [349,] 92.64667799 76.44345218 [350,] 59.61441992 92.64667799 [351,] -0.26299943 59.61441992 [352,] -21.42428976 -0.26299943 [353,] 36.04990379 -21.42428976 [354,] 7.62087153 36.04990379 [355,] 20.36603282 7.62087153 [356,] 5.47248444 20.36603282 [357,] -0.68558008 5.47248444 [358,] -10.25654782 -0.68558008 [359,] -59.32428976 -10.25654782 [360,] -25.09986984 -59.32428976 [361,] -50.79664403 -25.09986984 [362,] -54.52890209 -50.79664403 [363,] -94.70632145 -54.52890209 [364,] -97.26761177 -94.70632145 [365,] -83.09341822 -97.26761177 [366,] -49.12245048 -83.09341822 [367,] -68.67728919 -49.12245048 [368,] -64.97083758 -68.67728919 [369,] -83.22890209 -64.97083758 [370,] -88.39986984 -83.22890209 [371,] -81.26761177 -88.39986984 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -29.97578251 -65.67900831 2 -23.80804057 -29.97578251 3 -8.78545993 -23.80804057 4 -27.54675025 -8.78545993 5 -60.87255670 -27.54675025 6 -37.80158896 -60.87255670 7 -23.95642767 -37.80158896 8 -24.54997606 -23.95642767 9 -40.50804057 -24.54997606 10 -33.97900831 -40.50804057 11 -19.24675025 -33.97900831 12 -7.72233033 -19.24675025 13 30.28089548 -7.72233033 14 43.44863741 30.28089548 15 71.77121806 43.44863741 16 116.20992773 71.77121806 17 88.48412128 116.20992773 18 153.45508903 88.48412128 19 141.40025032 153.45508903 20 126.40670193 141.40025032 21 157.14863741 126.40670193 22 113.27766967 157.14863741 23 122.80992773 113.27766967 24 151.13434766 122.80992773 25 155.53757346 151.13434766 26 130.00531540 155.53757346 27 104.12789604 130.00531540 28 84.46660572 104.12789604 29 40.54079927 84.46660572 30 39.81176701 40.54079927 31 0.65692830 39.81176701 32 5.46337991 0.65692830 33 -22.59468460 5.46337991 34 -14.56565234 -22.59468460 35 -11.73339428 -14.56565234 36 -55.20897436 -11.73339428 37 -76.20574855 -55.20897436 38 -75.43800662 -76.20574855 39 -75.01542597 -75.43800662 40 -71.27671629 -75.01542597 41 -107.80252275 -71.27671629 42 -91.03155500 -107.80252275 43 -86.48639371 -91.03155500 44 -61.37994210 -86.48639371 45 -59.13800662 -61.37994210 46 -57.60897436 -59.13800662 47 -79.47671629 -57.60897436 48 -100.75229637 -79.47671629 49 -102.44907057 -100.75229637 50 -113.98132863 -102.44907057 51 -91.65874799 -113.98132863 52 -76.52003831 -91.65874799 53 -124.24584476 -76.52003831 54 -96.17487702 -124.24584476 55 -81.72971573 -96.17487702 56 -83.62326412 -81.72971573 57 -92.98132863 -83.62326412 58 -103.65229637 -92.98132863 59 -111.02003831 -103.65229637 60 -119.79561839 -111.02003831 61 -146.49239258 -119.79561839 62 -137.82465065 -146.49239258 63 -105.30207000 -137.82465065 64 -107.56336032 -105.30207000 65 -160.68916678 -107.56336032 66 -140.11819903 -160.68916678 67 -128.77303774 -140.11819903 68 -100.96658613 -128.77303774 69 -90.22465065 -100.96658613 70 -67.79561839 -90.22465065 71 -35.56336032 -67.79561839 72 16.66105960 -35.56336032 73 48.96428540 16.66105960 74 76.63202734 48.96428540 75 96.45460798 76.63202734 76 98.19331766 96.45460798 77 27.76751121 98.19331766 78 50.33847895 27.76751121 79 60.58364024 50.33847895 80 73.99009185 60.58364024 81 39.03202734 73.99009185 82 35.56105960 39.03202734 83 22.49331766 35.56105960 84 21.01773758 22.49331766 85 1.12096339 21.01773758 86 -3.81129468 1.12096339 87 21.61128597 -3.81129468 88 -5.05000435 21.61128597 89 -57.47581080 -5.05000435 90 -57.80484306 -57.47581080 91 -39.25968177 -57.80484306 92 -41.95323016 -39.25968177 93 -31.91129468 -41.95323016 94 -28.78226242 -31.91129468 95 -24.75000435 -28.78226242 96 -45.72558443 -24.75000435 97 -53.02235863 -45.72558443 98 -30.45461669 -53.02235863 99 -30.03203605 -30.45461669 100 -0.59332637 -30.03203605 101 -35.31913282 -0.59332637 102 -32.04816508 -35.31913282 103 -52.60300379 -32.04816508 104 -54.89655217 -52.60300379 105 -57.65461669 -54.89655217 106 -28.92558443 -57.65461669 107 -25.29332637 -28.92558443 108 -38.16890645 -25.29332637 109 -60.16568064 -38.16890645 110 -64.19793871 -60.16568064 111 -44.77535806 -64.19793871 112 -23.43664838 -44.77535806 113 -46.56245483 -23.43664838 114 -52.59148709 -46.56245483 115 -53.14632580 -52.59148709 116 -38.33987419 -53.14632580 117 -26.69793871 -38.33987419 118 17.43109355 -26.69793871 119 35.46335162 17.43109355 120 81.18777154 35.46335162 121 136.49099734 81.18777154 122 162.65873928 136.49099734 123 192.48131993 162.65873928 124 189.82002960 192.48131993 125 156.19422315 189.82002960 126 166.46519089 156.19422315 127 148.51035218 166.46519089 128 110.71680380 148.51035218 129 95.35873928 110.71680380 130 76.78777154 95.35873928 131 102.62002960 76.78777154 132 96.14444952 102.62002960 133 88.24767533 96.14444952 134 70.51541727 88.24767533 135 35.43799791 70.51541727 136 32.87670759 35.43799791 137 5.45090114 32.87670759 138 10.72186888 5.45090114 139 16.06703017 10.72186888 140 17.97348178 16.06703017 141 37.01541727 17.97348178 142 55.44444952 37.01541727 143 41.47670759 55.44444952 144 33.80112751 41.47670759 145 0.60435332 33.80112751 146 50.67209525 0.60435332 147 33.89467590 50.67209525 148 31.73338557 33.89467590 149 38.20757912 31.73338557 150 32.17854686 38.20757912 151 46.02370815 32.17854686 152 23.53015977 46.02370815 153 61.17209525 23.53015977 154 82.10112751 61.17209525 155 129.93338557 82.10112751 156 148.95780549 129.93338557 157 170.96103130 148.95780549 158 170.12877324 170.96103130 159 155.45135388 170.12877324 160 154.39006356 155.45135388 161 145.86425711 154.39006356 162 133.43522485 145.86425711 163 112.48038614 133.43522485 164 88.98683775 112.48038614 165 87.32877324 88.98683775 166 73.05780549 87.32877324 167 80.59006356 73.05780549 168 71.11448348 80.59006356 169 47.21770929 71.11448348 170 53.68545122 47.21770929 171 46.60803187 53.68545122 172 76.04674154 46.60803187 173 30.02093509 76.04674154 174 13.79190283 30.02093509 175 46.23706412 13.79190283 176 24.64351574 46.23706412 177 17.98545122 24.64351574 178 45.11448348 17.98545122 179 46.04674154 45.11448348 180 65.27116146 46.04674154 181 79.67438727 65.27116146 182 59.14212921 79.67438727 183 53.16470985 59.14212921 184 69.30341953 53.16470985 185 57.07761308 69.30341953 186 38.44858082 57.07761308 187 31.09374211 38.44858082 188 19.70019372 31.09374211 189 27.54212921 19.70019372 190 51.87116146 27.54212921 191 42.40341953 51.87116146 192 47.92783945 42.40341953 193 32.33106526 47.92783945 194 30.99880719 32.33106526 195 30.52138784 30.99880719 196 20.76009751 30.52138784 197 40.53429106 20.76009751 198 -14.49474120 40.53429106 199 4.25042009 -14.49474120 200 -7.54312829 4.25042009 201 1.49880719 -7.54312829 202 -8.57216055 1.49880719 203 -1.93990249 -8.57216055 204 -16.21548256 -1.93990249 205 -3.01225676 -16.21548256 206 -28.04451482 -3.01225676 207 -9.82193418 -28.04451482 208 -17.08322450 -9.82193418 209 -5.50903095 -17.08322450 210 -45.53806321 -5.50903095 211 -40.79290192 -45.53806321 212 -55.98645031 -40.79290192 213 -53.84451482 -55.98645031 214 -58.01548256 -53.84451482 215 -70.48322450 -58.01548256 216 -92.35880458 -70.48322450 217 -115.75557877 -92.35880458 218 -105.38783684 -115.75557877 219 -92.46525619 -105.38783684 220 -65.62654652 -92.46525619 221 -58.45235297 -65.62654652 222 -89.88138522 -58.45235297 223 -81.63622393 -89.88138522 224 -96.32977232 -81.63622393 225 -84.68783684 -96.32977232 226 -95.35880458 -84.68783684 227 -89.22654652 -95.35880458 228 -107.30212659 -89.22654652 229 -114.69890079 -107.30212659 230 -115.43115885 -114.69890079 231 -105.50857821 -115.43115885 232 -105.56986853 -105.50857821 233 -61.29567498 -105.56986853 234 -76.42470724 -61.29567498 235 -75.97954595 -76.42470724 236 -63.57309434 -75.97954595 237 -42.43115885 -63.57309434 238 -69.40212659 -42.43115885 239 -90.16986853 -69.40212659 240 -122.24544861 -90.16986853 241 -110.84222280 -122.24544861 242 -124.37448087 -110.84222280 243 -129.25190022 -124.37448087 244 -127.41319054 -129.25190022 245 -69.03899700 -127.41319054 246 -86.06802925 -69.03899700 247 -99.42286796 -86.06802925 248 -98.81641635 -99.42286796 249 -93.07448087 -98.81641635 250 -108.54544861 -93.07448087 251 -126.81319054 -108.54544861 252 -148.58877062 -126.81319054 253 -153.68554482 -148.58877062 254 -149.01780288 -153.68554482 255 -130.59522224 -149.01780288 256 -134.25651256 -130.59522224 257 -97.98231901 -134.25651256 258 -96.01135127 -97.98231901 259 -96.06618998 -96.01135127 260 -70.15973837 -96.06618998 261 -66.51780288 -70.15973837 262 -101.58877062 -66.51780288 263 -112.35651256 -101.58877062 264 -101.93209264 -112.35651256 265 -73.02886683 -101.93209264 266 -56.86112490 -73.02886683 267 -36.03854425 -56.86112490 268 -32.29983457 -36.03854425 269 23.47435897 -32.29983457 270 30.34532672 23.47435897 271 32.49048801 30.34532672 272 56.79693962 32.49048801 273 68.93887510 56.79693962 274 81.66790736 68.93887510 275 82.10016543 81.66790736 276 92.42458535 82.10016543 277 85.32781115 92.42458535 278 80.89555309 85.32781115 279 71.71813373 80.89555309 280 62.25684341 71.71813373 281 99.13103696 62.25684341 282 105.90200470 99.13103696 283 110.14716599 105.90200470 284 105.15361760 110.14716599 285 93.59555309 105.15361760 286 96.02458535 93.59555309 287 81.55684341 96.02458535 288 89.28126333 81.55684341 289 75.88448914 89.28126333 290 78.45223107 75.88448914 291 65.57481172 78.45223107 292 50.81352140 65.57481172 293 86.28771494 50.81352140 294 83.75868269 86.28771494 295 83.30384398 83.75868269 296 80.51029559 83.30384398 297 77.15223107 80.51029559 298 34.68126333 77.15223107 299 17.21352140 34.68126333 300 5.63794132 17.21352140 301 12.74116712 5.63794132 302 1.70890906 12.74116712 303 6.83148970 1.70890906 304 -10.12980062 6.83148970 305 21.94439293 -10.12980062 306 15.01536067 21.94439293 307 11.96052196 15.01536067 308 24.76697358 11.96052196 309 0.00890906 24.76697358 310 7.23794132 0.00890906 311 4.97019938 7.23794132 312 -188.22658178 4.97019938 313 -184.92335597 -188.22658178 314 -201.15561404 -184.92335597 315 -207.63303339 -201.15561404 316 -202.79432371 -207.63303339 317 -151.92013016 -202.79432371 318 -141.14916242 -151.92013016 319 -147.50400113 -141.14916242 320 -98.69754952 -147.50400113 321 -99.05561404 -98.69754952 322 -57.02658178 -99.05561404 323 -17.39432371 -57.02658178 324 122.53009621 -17.39432371 325 125.53332201 122.53009621 326 152.80106395 125.53332201 327 137.82364460 152.80106395 328 138.66235427 137.82364460 329 160.53654782 138.66235427 330 147.30751556 160.53654782 331 127.15267685 147.30751556 332 126.85912847 127.15267685 333 114.50106395 126.85912847 334 91.13009621 114.50106395 335 85.06235427 91.13009621 336 115.48677419 85.06235427 337 91.49000000 115.48677419 338 62.95774194 91.49000000 339 38.38032258 62.95774194 340 0.31903226 38.38032258 341 62.69322581 0.31903226 342 77.66419355 62.69322581 343 83.30935484 77.66419355 344 70.81580645 83.30935484 345 66.95774194 70.81580645 346 71.08677419 66.95774194 347 61.31903226 71.08677419 348 76.44345218 61.31903226 349 92.64667799 76.44345218 350 59.61441992 92.64667799 351 -0.26299943 59.61441992 352 -21.42428976 -0.26299943 353 36.04990379 -21.42428976 354 7.62087153 36.04990379 355 20.36603282 7.62087153 356 5.47248444 20.36603282 357 -0.68558008 5.47248444 358 -10.25654782 -0.68558008 359 -59.32428976 -10.25654782 360 -25.09986984 -59.32428976 361 -50.79664403 -25.09986984 362 -54.52890209 -50.79664403 363 -94.70632145 -54.52890209 364 -97.26761177 -94.70632145 365 -83.09341822 -97.26761177 366 -49.12245048 -83.09341822 367 -68.67728919 -49.12245048 368 -64.97083758 -68.67728919 369 -83.22890209 -64.97083758 370 -88.39986984 -83.22890209 371 -81.26761177 -88.39986984 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/79ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/89ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/99ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/102xtf1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11ngrk1291066291.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/129h891291066291.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/13n86z1291066291.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/14qrmn1291066291.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/15urlb1291066291.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/16xajh1291066291.tab") + } > > try(system("convert tmp/1vwe31291066291.ps tmp/1vwe31291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/2vwe31291066291.ps tmp/2vwe31291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/3oodo1291066291.ps tmp/3oodo1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/4oodo1291066291.ps tmp/4oodo1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/5oodo1291066291.ps tmp/5oodo1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/6m0kx1291066291.ps tmp/6m0kx1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/79ouu1291066291.ps tmp/79ouu1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/89ouu1291066291.ps tmp/89ouu1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/99ouu1291066291.ps tmp/99ouu1291066291.png",intern=TRUE)) character(0) > try(system("convert tmp/102xtf1291066291.ps tmp/102xtf1291066291.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 10.241 2.048 21.535