R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(235.1 + ,280.7 + ,264.6 + ,240.7 + ,201.4 + ,240.8 + ,241.1 + ,223.8 + ,206.1 + ,174.7 + ,203.3 + ,220.5 + ,299.5 + ,347.4 + ,338.3 + ,327.7 + ,351.6 + ,396.6 + ,438.8 + ,395.6 + ,363.5 + ,378.8 + ,357 + ,369 + ,464.8 + ,479.1 + ,431.3 + ,366.5 + ,326.3 + ,355.1 + ,331.6 + ,261.3 + ,249 + ,205.5 + ,235.6 + ,240.9 + ,264.9 + ,253.8 + ,232.3 + ,193.8 + ,177 + ,213.2 + ,207.2 + ,180.6 + ,188.6 + ,175.4 + ,199 + ,179.6 + ,225.8 + ,234 + ,200.2 + ,183.6 + ,178.2 + ,203.2 + ,208.5 + ,191.8 + ,172.8 + ,148 + ,159.4 + ,154.5 + ,213.2 + ,196.4 + ,182.8 + ,176.4 + ,153.6 + ,173.2 + ,171 + ,151.2 + ,161.9 + ,157.2 + ,201.7 + ,236.4 + ,356.1 + ,398.3 + ,403.7 + ,384.6 + ,365.8 + ,368.1 + ,367.9 + ,347 + ,343.3 + ,292.9 + ,311.5 + ,300.9 + ,366.9 + ,356.9 + ,329.7 + ,316.2 + ,269 + ,289.3 + ,266.2 + ,253.6 + ,233.8 + ,228.4 + ,253.6 + ,260.1 + ,306.6 + ,309.2 + ,309.5 + ,271 + ,279.9 + ,317.9 + ,298.4 + ,246.7 + ,227.3 + ,209.1 + ,259.9 + ,266 + ,320.6 + ,308.5 + ,282.2 + ,262.7 + ,263.5 + ,313.1 + ,284.3 + ,252.6 + ,250.3 + ,246.5 + ,312.7 + ,333.2 + ,446.4 + ,511.6 + ,515.5 + ,506.4 + ,483.2 + ,522.3 + ,509.8 + ,460.7 + ,405.8 + ,375 + ,378.5 + ,406.8 + ,467.8 + ,469.8 + ,429.8 + ,355.8 + ,332.7 + ,378 + ,360.5 + ,334.7 + ,319.5 + ,323.1 + ,363.6 + ,352.1 + ,411.9 + ,388.6 + ,416.4 + ,360.7 + ,338 + ,417.2 + ,388.4 + ,371.1 + ,331.5 + ,353.7 + ,396.7 + ,447 + ,533.5 + ,565.4 + ,542.3 + ,488.7 + ,467.1 + ,531.3 + ,496.1 + ,444 + ,403.4 + ,386.3 + ,394.1 + ,404.1 + ,462.1 + ,448.1 + ,432.3 + ,386.3 + ,395.2 + ,421.9 + ,382.9 + ,384.2 + ,345.5 + ,323.4 + ,372.6 + ,376 + ,462.7 + ,487 + ,444.2 + ,399.3 + ,394.9 + ,455.4 + ,414 + ,375.5 + ,347 + ,339.4 + ,385.8 + ,378.8 + ,451.8 + ,446.1 + ,422.5 + ,383.1 + ,352.8 + ,445.3 + ,367.5 + ,355.1 + ,326.2 + ,319.8 + ,331.8 + ,340.9 + ,394.1 + ,417.2 + ,369.9 + ,349.2 + ,321.4 + ,405.7 + ,342.9 + ,316.5 + ,284.2 + ,270.9 + ,288.8 + ,278.8 + ,324.4 + ,310.9 + ,299 + ,273 + ,279.3 + ,359.2 + ,305 + ,282.1 + ,250.3 + ,246.5 + ,257.9 + ,266.5 + ,315.9 + ,318.4 + ,295.4 + ,266.4 + ,245.8 + ,362.8 + ,324.9 + ,294.2 + ,289.5 + ,295.2 + ,290.3 + ,272 + ,307.4 + ,328.7 + ,292.9 + ,249.1 + ,230.4 + ,361.5 + ,321.7 + ,277.2 + ,260.7 + ,251 + ,257.6 + ,241.8 + ,287.5 + ,292.3 + ,274.7 + ,254.2 + ,230 + ,339 + ,318.2 + ,287 + ,295.8 + ,284 + ,271 + ,262.7 + ,340.6 + ,379.4 + ,373.3 + ,355.2 + ,338.4 + ,466.9 + ,451 + ,422 + ,429.2 + ,425.9 + ,460.7 + ,463.6 + ,541.4 + ,544.2 + ,517.5 + ,469.4 + ,439.4 + ,549 + ,533 + ,506.1 + ,484 + ,457 + ,481.5 + ,469.5 + ,544.7 + ,541.2 + ,521.5 + ,469.7 + ,434.4 + ,542.6 + ,517.3 + ,485.7 + ,465.8 + ,447 + ,426.6 + ,411.6 + ,467.5 + ,484.5 + ,451.2 + ,417.4 + ,379.9 + ,484.7 + ,455 + ,420.8 + ,416.5 + ,376.3 + ,405.6 + ,405.8 + ,500.8 + ,514 + ,475.5 + ,430.1 + ,414.4 + ,538 + ,526 + ,488.5 + ,520.2 + ,504.4 + ,568.5 + ,610.6 + ,818 + ,830.9 + ,835.9 + ,782 + ,762.3 + ,856.9 + ,820.9 + ,769.6 + ,752.2 + ,724.4 + ,723.1 + ,719.5 + ,817.4 + ,803.3 + ,752.5 + ,689 + ,630.4 + ,765.5 + ,757.7 + ,732.2 + ,702.6 + ,683.3 + ,709.5 + ,702.2 + ,784.8 + ,810.9 + ,755.6 + ,656.8 + ,615.1 + ,745.3 + ,694.1 + ,675.7 + ,643.7 + ,622.1 + ,634.6 + ,588 + ,689.7 + ,673.9 + ,647.9 + ,568.8 + ,545.7 + ,632.6 + ,643.8 + ,593.1 + ,579.7 + ,546 + ,562.9 + ,572.5) + ,dim=c(1 + ,372) + ,dimnames=list(c('Unemployment') + ,1:372)) > y <- array(NA,dim=c(1,372),dimnames=list(c('Unemployment'),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' > 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, 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 Unemployment M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 235.1 1 0 0 0 0 0 0 0 0 0 0 1 2 280.7 0 1 0 0 0 0 0 0 0 0 0 2 3 264.6 0 0 1 0 0 0 0 0 0 0 0 3 4 240.7 0 0 0 1 0 0 0 0 0 0 0 4 5 201.4 0 0 0 0 1 0 0 0 0 0 0 5 6 240.8 0 0 0 0 0 1 0 0 0 0 0 6 7 241.1 0 0 0 0 0 0 1 0 0 0 0 7 8 223.8 0 0 0 0 0 0 0 1 0 0 0 8 9 206.1 0 0 0 0 0 0 0 0 1 0 0 9 10 174.7 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 1 11 12 220.5 0 0 0 0 0 0 0 0 0 0 0 12 13 299.5 1 0 0 0 0 0 0 0 0 0 0 13 14 347.4 0 1 0 0 0 0 0 0 0 0 0 14 15 338.3 0 0 1 0 0 0 0 0 0 0 0 15 16 327.7 0 0 0 1 0 0 0 0 0 0 0 16 17 351.6 0 0 0 0 1 0 0 0 0 0 0 17 18 396.6 0 0 0 0 0 1 0 0 0 0 0 18 19 438.8 0 0 0 0 0 0 1 0 0 0 0 19 20 395.6 0 0 0 0 0 0 0 1 0 0 0 20 21 363.5 0 0 0 0 0 0 0 0 1 0 0 21 22 378.8 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 1 23 24 369.0 0 0 0 0 0 0 0 0 0 0 0 24 25 464.8 1 0 0 0 0 0 0 0 0 0 0 25 26 479.1 0 1 0 0 0 0 0 0 0 0 0 26 27 431.3 0 0 1 0 0 0 0 0 0 0 0 27 28 366.5 0 0 0 1 0 0 0 0 0 0 0 28 29 326.3 0 0 0 0 1 0 0 0 0 0 0 29 30 355.1 0 0 0 0 0 1 0 0 0 0 0 30 31 331.6 0 0 0 0 0 0 1 0 0 0 0 31 32 261.3 0 0 0 0 0 0 0 1 0 0 0 32 33 249.0 0 0 0 0 0 0 0 0 1 0 0 33 34 205.5 0 0 0 0 0 0 0 0 0 1 0 34 35 235.6 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 36 37 264.9 1 0 0 0 0 0 0 0 0 0 0 37 38 253.8 0 1 0 0 0 0 0 0 0 0 0 38 39 232.3 0 0 1 0 0 0 0 0 0 0 0 39 40 193.8 0 0 0 1 0 0 0 0 0 0 0 40 41 177.0 0 0 0 0 1 0 0 0 0 0 0 41 42 213.2 0 0 0 0 0 1 0 0 0 0 0 42 43 207.2 0 0 0 0 0 0 1 0 0 0 0 43 44 180.6 0 0 0 0 0 0 0 1 0 0 0 44 45 188.6 0 0 0 0 0 0 0 0 1 0 0 45 46 175.4 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 1 47 48 179.6 0 0 0 0 0 0 0 0 0 0 0 48 49 225.8 1 0 0 0 0 0 0 0 0 0 0 49 50 234.0 0 1 0 0 0 0 0 0 0 0 0 50 51 200.2 0 0 1 0 0 0 0 0 0 0 0 51 52 183.6 0 0 0 1 0 0 0 0 0 0 0 52 53 178.2 0 0 0 0 1 0 0 0 0 0 0 53 54 203.2 0 0 0 0 0 1 0 0 0 0 0 54 55 208.5 0 0 0 0 0 0 1 0 0 0 0 55 56 191.8 0 0 0 0 0 0 0 1 0 0 0 56 57 172.8 0 0 0 0 0 0 0 0 1 0 0 57 58 148.0 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 1 59 60 154.5 0 0 0 0 0 0 0 0 0 0 0 60 61 213.2 1 0 0 0 0 0 0 0 0 0 0 61 62 196.4 0 1 0 0 0 0 0 0 0 0 0 62 63 182.8 0 0 1 0 0 0 0 0 0 0 0 63 64 176.4 0 0 0 1 0 0 0 0 0 0 0 64 65 153.6 0 0 0 0 1 0 0 0 0 0 0 65 66 173.2 0 0 0 0 0 1 0 0 0 0 0 66 67 171.0 0 0 0 0 0 0 1 0 0 0 0 67 68 151.2 0 0 0 0 0 0 0 1 0 0 0 68 69 161.9 0 0 0 0 0 0 0 0 1 0 0 69 70 157.2 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 1 71 72 236.4 0 0 0 0 0 0 0 0 0 0 0 72 73 356.1 1 0 0 0 0 0 0 0 0 0 0 73 74 398.3 0 1 0 0 0 0 0 0 0 0 0 74 75 403.7 0 0 1 0 0 0 0 0 0 0 0 75 76 384.6 0 0 0 1 0 0 0 0 0 0 0 76 77 365.8 0 0 0 0 1 0 0 0 0 0 0 77 78 368.1 0 0 0 0 0 1 0 0 0 0 0 78 79 367.9 0 0 0 0 0 0 1 0 0 0 0 79 80 347.0 0 0 0 0 0 0 0 1 0 0 0 80 81 343.3 0 0 0 0 0 0 0 0 1 0 0 81 82 292.9 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 1 83 84 300.9 0 0 0 0 0 0 0 0 0 0 0 84 85 366.9 1 0 0 0 0 0 0 0 0 0 0 85 86 356.9 0 1 0 0 0 0 0 0 0 0 0 86 87 329.7 0 0 1 0 0 0 0 0 0 0 0 87 88 316.2 0 0 0 1 0 0 0 0 0 0 0 88 89 269.0 0 0 0 0 1 0 0 0 0 0 0 89 90 289.3 0 0 0 0 0 1 0 0 0 0 0 90 91 266.2 0 0 0 0 0 0 1 0 0 0 0 91 92 253.6 0 0 0 0 0 0 0 1 0 0 0 92 93 233.8 0 0 0 0 0 0 0 0 1 0 0 93 94 228.4 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 1 95 96 260.1 0 0 0 0 0 0 0 0 0 0 0 96 97 306.6 1 0 0 0 0 0 0 0 0 0 0 97 98 309.2 0 1 0 0 0 0 0 0 0 0 0 98 99 309.5 0 0 1 0 0 0 0 0 0 0 0 99 100 271.0 0 0 0 1 0 0 0 0 0 0 0 100 101 279.9 0 0 0 0 1 0 0 0 0 0 0 101 102 317.9 0 0 0 0 0 1 0 0 0 0 0 102 103 298.4 0 0 0 0 0 0 1 0 0 0 0 103 104 246.7 0 0 0 0 0 0 0 1 0 0 0 104 105 227.3 0 0 0 0 0 0 0 0 1 0 0 105 106 209.1 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 1 107 108 266.0 0 0 0 0 0 0 0 0 0 0 0 108 109 320.6 1 0 0 0 0 0 0 0 0 0 0 109 110 308.5 0 1 0 0 0 0 0 0 0 0 0 110 111 282.2 0 0 1 0 0 0 0 0 0 0 0 111 112 262.7 0 0 0 1 0 0 0 0 0 0 0 112 113 263.5 0 0 0 0 1 0 0 0 0 0 0 113 114 313.1 0 0 0 0 0 1 0 0 0 0 0 114 115 284.3 0 0 0 0 0 0 1 0 0 0 0 115 116 252.6 0 0 0 0 0 0 0 1 0 0 0 116 117 250.3 0 0 0 0 0 0 0 0 1 0 0 117 118 246.5 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 1 119 120 333.2 0 0 0 0 0 0 0 0 0 0 0 120 121 446.4 1 0 0 0 0 0 0 0 0 0 0 121 122 511.6 0 1 0 0 0 0 0 0 0 0 0 122 123 515.5 0 0 1 0 0 0 0 0 0 0 0 123 124 506.4 0 0 0 1 0 0 0 0 0 0 0 124 125 483.2 0 0 0 0 1 0 0 0 0 0 0 125 126 522.3 0 0 0 0 0 1 0 0 0 0 0 126 127 509.8 0 0 0 0 0 0 1 0 0 0 0 127 128 460.7 0 0 0 0 0 0 0 1 0 0 0 128 129 405.8 0 0 0 0 0 0 0 0 1 0 0 129 130 375.0 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 1 131 132 406.8 0 0 0 0 0 0 0 0 0 0 0 132 133 467.8 1 0 0 0 0 0 0 0 0 0 0 133 134 469.8 0 1 0 0 0 0 0 0 0 0 0 134 135 429.8 0 0 1 0 0 0 0 0 0 0 0 135 136 355.8 0 0 0 1 0 0 0 0 0 0 0 136 137 332.7 0 0 0 0 1 0 0 0 0 0 0 137 138 378.0 0 0 0 0 0 1 0 0 0 0 0 138 139 360.5 0 0 0 0 0 0 1 0 0 0 0 139 140 334.7 0 0 0 0 0 0 0 1 0 0 0 140 141 319.5 0 0 0 0 0 0 0 0 1 0 0 141 142 323.1 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 1 143 144 352.1 0 0 0 0 0 0 0 0 0 0 0 144 145 411.9 1 0 0 0 0 0 0 0 0 0 0 145 146 388.6 0 1 0 0 0 0 0 0 0 0 0 146 147 416.4 0 0 1 0 0 0 0 0 0 0 0 147 148 360.7 0 0 0 1 0 0 0 0 0 0 0 148 149 338.0 0 0 0 0 1 0 0 0 0 0 0 149 150 417.2 0 0 0 0 0 1 0 0 0 0 0 150 151 388.4 0 0 0 0 0 0 1 0 0 0 0 151 152 371.1 0 0 0 0 0 0 0 1 0 0 0 152 153 331.5 0 0 0 0 0 0 0 0 1 0 0 153 154 353.7 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 1 155 156 447.0 0 0 0 0 0 0 0 0 0 0 0 156 157 533.5 1 0 0 0 0 0 0 0 0 0 0 157 158 565.4 0 1 0 0 0 0 0 0 0 0 0 158 159 542.3 0 0 1 0 0 0 0 0 0 0 0 159 160 488.7 0 0 0 1 0 0 0 0 0 0 0 160 161 467.1 0 0 0 0 1 0 0 0 0 0 0 161 162 531.3 0 0 0 0 0 1 0 0 0 0 0 162 163 496.1 0 0 0 0 0 0 1 0 0 0 0 163 164 444.0 0 0 0 0 0 0 0 1 0 0 0 164 165 403.4 0 0 0 0 0 0 0 0 1 0 0 165 166 386.3 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 1 167 168 404.1 0 0 0 0 0 0 0 0 0 0 0 168 169 462.1 1 0 0 0 0 0 0 0 0 0 0 169 170 448.1 0 1 0 0 0 0 0 0 0 0 0 170 171 432.3 0 0 1 0 0 0 0 0 0 0 0 171 172 386.3 0 0 0 1 0 0 0 0 0 0 0 172 173 395.2 0 0 0 0 1 0 0 0 0 0 0 173 174 421.9 0 0 0 0 0 1 0 0 0 0 0 174 175 382.9 0 0 0 0 0 0 1 0 0 0 0 175 176 384.2 0 0 0 0 0 0 0 1 0 0 0 176 177 345.5 0 0 0 0 0 0 0 0 1 0 0 177 178 323.4 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 1 179 180 376.0 0 0 0 0 0 0 0 0 0 0 0 180 181 462.7 1 0 0 0 0 0 0 0 0 0 0 181 182 487.0 0 1 0 0 0 0 0 0 0 0 0 182 183 444.2 0 0 1 0 0 0 0 0 0 0 0 183 184 399.3 0 0 0 1 0 0 0 0 0 0 0 184 185 394.9 0 0 0 0 1 0 0 0 0 0 0 185 186 455.4 0 0 0 0 0 1 0 0 0 0 0 186 187 414.0 0 0 0 0 0 0 1 0 0 0 0 187 188 375.5 0 0 0 0 0 0 0 1 0 0 0 188 189 347.0 0 0 0 0 0 0 0 0 1 0 0 189 190 339.4 0 0 0 0 0 0 0 0 0 1 0 190 191 385.8 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 0 192 193 451.8 1 0 0 0 0 0 0 0 0 0 0 193 194 446.1 0 1 0 0 0 0 0 0 0 0 0 194 195 422.5 0 0 1 0 0 0 0 0 0 0 0 195 196 383.1 0 0 0 1 0 0 0 0 0 0 0 196 197 352.8 0 0 0 0 1 0 0 0 0 0 0 197 198 445.3 0 0 0 0 0 1 0 0 0 0 0 198 199 367.5 0 0 0 0 0 0 1 0 0 0 0 199 200 355.1 0 0 0 0 0 0 0 1 0 0 0 200 201 326.2 0 0 0 0 0 0 0 0 1 0 0 201 202 319.8 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 1 203 204 340.9 0 0 0 0 0 0 0 0 0 0 0 204 205 394.1 1 0 0 0 0 0 0 0 0 0 0 205 206 417.2 0 1 0 0 0 0 0 0 0 0 0 206 207 369.9 0 0 1 0 0 0 0 0 0 0 0 207 208 349.2 0 0 0 1 0 0 0 0 0 0 0 208 209 321.4 0 0 0 0 1 0 0 0 0 0 0 209 210 405.7 0 0 0 0 0 1 0 0 0 0 0 210 211 342.9 0 0 0 0 0 0 1 0 0 0 0 211 212 316.5 0 0 0 0 0 0 0 1 0 0 0 212 213 284.2 0 0 0 0 0 0 0 0 1 0 0 213 214 270.9 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 1 215 216 278.8 0 0 0 0 0 0 0 0 0 0 0 216 217 324.4 1 0 0 0 0 0 0 0 0 0 0 217 218 310.9 0 1 0 0 0 0 0 0 0 0 0 218 219 299.0 0 0 1 0 0 0 0 0 0 0 0 219 220 273.0 0 0 0 1 0 0 0 0 0 0 0 220 221 279.3 0 0 0 0 1 0 0 0 0 0 0 221 222 359.2 0 0 0 0 0 1 0 0 0 0 0 222 223 305.0 0 0 0 0 0 0 1 0 0 0 0 223 224 282.1 0 0 0 0 0 0 0 1 0 0 0 224 225 250.3 0 0 0 0 0 0 0 0 1 0 0 225 226 246.5 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 1 227 228 266.5 0 0 0 0 0 0 0 0 0 0 0 228 229 315.9 1 0 0 0 0 0 0 0 0 0 0 229 230 318.4 0 1 0 0 0 0 0 0 0 0 0 230 231 295.4 0 0 1 0 0 0 0 0 0 0 0 231 232 266.4 0 0 0 1 0 0 0 0 0 0 0 232 233 245.8 0 0 0 0 1 0 0 0 0 0 0 233 234 362.8 0 0 0 0 0 1 0 0 0 0 0 234 235 324.9 0 0 0 0 0 0 1 0 0 0 0 235 236 294.2 0 0 0 0 0 0 0 1 0 0 0 236 237 289.5 0 0 0 0 0 0 0 0 1 0 0 237 238 295.2 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 1 239 240 272.0 0 0 0 0 0 0 0 0 0 0 0 240 241 307.4 1 0 0 0 0 0 0 0 0 0 0 241 242 328.7 0 1 0 0 0 0 0 0 0 0 0 242 243 292.9 0 0 1 0 0 0 0 0 0 0 0 243 244 249.1 0 0 0 1 0 0 0 0 0 0 0 244 245 230.4 0 0 0 0 1 0 0 0 0 0 0 245 246 361.5 0 0 0 0 0 1 0 0 0 0 0 246 247 321.7 0 0 0 0 0 0 1 0 0 0 0 247 248 277.2 0 0 0 0 0 0 0 1 0 0 0 248 249 260.7 0 0 0 0 0 0 0 0 1 0 0 249 250 251.0 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 1 251 252 241.8 0 0 0 0 0 0 0 0 0 0 0 252 253 287.5 1 0 0 0 0 0 0 0 0 0 0 253 254 292.3 0 1 0 0 0 0 0 0 0 0 0 254 255 274.7 0 0 1 0 0 0 0 0 0 0 0 255 256 254.2 0 0 0 1 0 0 0 0 0 0 0 256 257 230.0 0 0 0 0 1 0 0 0 0 0 0 257 258 339.0 0 0 0 0 0 1 0 0 0 0 0 258 259 318.2 0 0 0 0 0 0 1 0 0 0 0 259 260 287.0 0 0 0 0 0 0 0 1 0 0 0 260 261 295.8 0 0 0 0 0 0 0 0 1 0 0 261 262 284.0 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 1 263 264 262.7 0 0 0 0 0 0 0 0 0 0 0 264 265 340.6 1 0 0 0 0 0 0 0 0 0 0 265 266 379.4 0 1 0 0 0 0 0 0 0 0 0 266 267 373.3 0 0 1 0 0 0 0 0 0 0 0 267 268 355.2 0 0 0 1 0 0 0 0 0 0 0 268 269 338.4 0 0 0 0 1 0 0 0 0 0 0 269 270 466.9 0 0 0 0 0 1 0 0 0 0 0 270 271 451.0 0 0 0 0 0 0 1 0 0 0 0 271 272 422.0 0 0 0 0 0 0 0 1 0 0 0 272 273 429.2 0 0 0 0 0 0 0 0 1 0 0 273 274 425.9 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 1 275 276 463.6 0 0 0 0 0 0 0 0 0 0 0 276 277 541.4 1 0 0 0 0 0 0 0 0 0 0 277 278 544.2 0 1 0 0 0 0 0 0 0 0 0 278 279 517.5 0 0 1 0 0 0 0 0 0 0 0 279 280 469.4 0 0 0 1 0 0 0 0 0 0 0 280 281 439.4 0 0 0 0 1 0 0 0 0 0 0 281 282 549.0 0 0 0 0 0 1 0 0 0 0 0 282 283 533.0 0 0 0 0 0 0 1 0 0 0 0 283 284 506.1 0 0 0 0 0 0 0 1 0 0 0 284 285 484.0 0 0 0 0 0 0 0 0 1 0 0 285 286 457.0 0 0 0 0 0 0 0 0 0 1 0 286 287 481.5 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 0 288 289 544.7 1 0 0 0 0 0 0 0 0 0 0 289 290 541.2 0 1 0 0 0 0 0 0 0 0 0 290 291 521.5 0 0 1 0 0 0 0 0 0 0 0 291 292 469.7 0 0 0 1 0 0 0 0 0 0 0 292 293 434.4 0 0 0 0 1 0 0 0 0 0 0 293 294 542.6 0 0 0 0 0 1 0 0 0 0 0 294 295 517.3 0 0 0 0 0 0 1 0 0 0 0 295 296 485.7 0 0 0 0 0 0 0 1 0 0 0 296 297 465.8 0 0 0 0 0 0 0 0 1 0 0 297 298 447.0 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 1 299 300 411.6 0 0 0 0 0 0 0 0 0 0 0 300 301 467.5 1 0 0 0 0 0 0 0 0 0 0 301 302 484.5 0 1 0 0 0 0 0 0 0 0 0 302 303 451.2 0 0 1 0 0 0 0 0 0 0 0 303 304 417.4 0 0 0 1 0 0 0 0 0 0 0 304 305 379.9 0 0 0 0 1 0 0 0 0 0 0 305 306 484.7 0 0 0 0 0 1 0 0 0 0 0 306 307 455.0 0 0 0 0 0 0 1 0 0 0 0 307 308 420.8 0 0 0 0 0 0 0 1 0 0 0 308 309 416.5 0 0 0 0 0 0 0 0 1 0 0 309 310 376.3 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 1 311 312 405.8 0 0 0 0 0 0 0 0 0 0 0 312 313 500.8 1 0 0 0 0 0 0 0 0 0 0 313 314 514.0 0 1 0 0 0 0 0 0 0 0 0 314 315 475.5 0 0 1 0 0 0 0 0 0 0 0 315 316 430.1 0 0 0 1 0 0 0 0 0 0 0 316 317 414.4 0 0 0 0 1 0 0 0 0 0 0 317 318 538.0 0 0 0 0 0 1 0 0 0 0 0 318 319 526.0 0 0 0 0 0 0 1 0 0 0 0 319 320 488.5 0 0 0 0 0 0 0 1 0 0 0 320 321 520.2 0 0 0 0 0 0 0 0 1 0 0 321 322 504.4 0 0 0 0 0 0 0 0 0 1 0 322 323 568.5 0 0 0 0 0 0 0 0 0 0 1 323 324 610.6 0 0 0 0 0 0 0 0 0 0 0 324 325 818.0 1 0 0 0 0 0 0 0 0 0 0 325 326 830.9 0 1 0 0 0 0 0 0 0 0 0 326 327 835.9 0 0 1 0 0 0 0 0 0 0 0 327 328 782.0 0 0 0 1 0 0 0 0 0 0 0 328 329 762.3 0 0 0 0 1 0 0 0 0 0 0 329 330 856.9 0 0 0 0 0 1 0 0 0 0 0 330 331 820.9 0 0 0 0 0 0 1 0 0 0 0 331 332 769.6 0 0 0 0 0 0 0 1 0 0 0 332 333 752.2 0 0 0 0 0 0 0 0 1 0 0 333 334 724.4 0 0 0 0 0 0 0 0 0 1 0 334 335 723.1 0 0 0 0 0 0 0 0 0 0 1 335 336 719.5 0 0 0 0 0 0 0 0 0 0 0 336 337 817.4 1 0 0 0 0 0 0 0 0 0 0 337 338 803.3 0 1 0 0 0 0 0 0 0 0 0 338 339 752.5 0 0 1 0 0 0 0 0 0 0 0 339 340 689.0 0 0 0 1 0 0 0 0 0 0 0 340 341 630.4 0 0 0 0 1 0 0 0 0 0 0 341 342 765.5 0 0 0 0 0 1 0 0 0 0 0 342 343 757.7 0 0 0 0 0 0 1 0 0 0 0 343 344 732.2 0 0 0 0 0 0 0 1 0 0 0 344 345 702.6 0 0 0 0 0 0 0 0 1 0 0 345 346 683.3 0 0 0 0 0 0 0 0 0 1 0 346 347 709.5 0 0 0 0 0 0 0 0 0 0 1 347 348 702.2 0 0 0 0 0 0 0 0 0 0 0 348 349 784.8 1 0 0 0 0 0 0 0 0 0 0 349 350 810.9 0 1 0 0 0 0 0 0 0 0 0 350 351 755.6 0 0 1 0 0 0 0 0 0 0 0 351 352 656.8 0 0 0 1 0 0 0 0 0 0 0 352 353 615.1 0 0 0 0 1 0 0 0 0 0 0 353 354 745.3 0 0 0 0 0 1 0 0 0 0 0 354 355 694.1 0 0 0 0 0 0 1 0 0 0 0 355 356 675.7 0 0 0 0 0 0 0 1 0 0 0 356 357 643.7 0 0 0 0 0 0 0 0 1 0 0 357 358 622.1 0 0 0 0 0 0 0 0 0 1 0 358 359 634.6 0 0 0 0 0 0 0 0 0 0 1 359 360 588.0 0 0 0 0 0 0 0 0 0 0 0 360 361 689.7 1 0 0 0 0 0 0 0 0 0 0 361 362 673.9 0 1 0 0 0 0 0 0 0 0 0 362 363 647.9 0 0 1 0 0 0 0 0 0 0 0 363 364 568.8 0 0 0 1 0 0 0 0 0 0 0 364 365 545.7 0 0 0 0 1 0 0 0 0 0 0 365 366 632.6 0 0 0 0 0 1 0 0 0 0 0 366 367 643.8 0 0 0 0 0 0 1 0 0 0 0 367 368 593.1 0 0 0 0 0 0 0 1 0 0 0 368 369 579.7 0 0 0 0 0 0 0 0 1 0 0 369 370 546.0 0 0 0 0 0 0 0 0 0 1 0 370 371 562.9 0 0 0 0 0 0 0 0 0 0 1 371 372 572.5 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) M1 M2 M3 M4 M5 176.343 72.242 81.119 57.833 17.891 -3.667 M6 M7 M8 M9 M10 M11 68.040 44.250 12.086 -6.040 -22.501 -1.449 t 1.019 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -223.996 -68.016 -2.822 49.924 276.237 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 176.34312 21.58250 8.171 5.3e-15 *** M1 72.24158 27.12567 2.663 0.00809 ** M2 81.11933 27.12464 2.991 0.00298 ** M3 57.83256 27.12371 2.132 0.03367 * M4 17.89095 27.12288 0.660 0.50992 M5 -3.66679 27.12214 -0.135 0.89253 M6 68.03998 27.12150 2.509 0.01256 * M7 44.24999 27.12096 1.632 0.10365 M8 12.08580 27.12052 0.446 0.65613 M9 -6.03969 27.12018 -0.223 0.82390 M10 -22.50065 27.11993 -0.830 0.40728 M11 -1.44871 27.11979 -0.053 0.95743 t 1.01903 0.05158 19.758 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 106.8 on 359 degrees of freedom Multiple R-squared: 0.5411, Adjusted R-squared: 0.5258 F-statistic: 35.28 on 12 and 359 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,] 3.991785e-04 7.983570e-04 9.996008e-01 [2,] 5.459917e-03 1.091983e-02 9.945401e-01 [3,] 4.117538e-03 8.235076e-03 9.958825e-01 [4,] 6.375702e-03 1.275140e-02 9.936243e-01 [5,] 3.381282e-03 6.762564e-03 9.966187e-01 [6,] 1.357249e-03 2.714499e-03 9.986428e-01 [7,] 1.146449e-03 2.292899e-03 9.988536e-01 [8,] 4.207208e-04 8.414415e-04 9.995793e-01 [9,] 1.456653e-04 2.913306e-04 9.998543e-01 [10,] 4.856151e-05 9.712302e-05 9.999514e-01 [11,] 2.187073e-05 4.374147e-05 9.999781e-01 [12,] 1.938237e-05 3.876475e-05 9.999806e-01 [13,] 5.353466e-05 1.070693e-04 9.999465e-01 [14,] 1.894436e-04 3.788872e-04 9.998106e-01 [15,] 4.447664e-04 8.895327e-04 9.995552e-01 [16,] 1.680611e-03 3.361221e-03 9.983194e-01 [17,] 6.762854e-03 1.352571e-02 9.932371e-01 [18,] 1.221292e-02 2.442584e-02 9.877871e-01 [19,] 2.547334e-02 5.094667e-02 9.745267e-01 [20,] 3.140855e-02 6.281710e-02 9.685914e-01 [21,] 3.771295e-02 7.542591e-02 9.622870e-01 [22,] 5.800570e-02 1.160114e-01 9.419943e-01 [23,] 1.024910e-01 2.049820e-01 8.975090e-01 [24,] 1.387263e-01 2.774525e-01 8.612737e-01 [25,] 1.695035e-01 3.390069e-01 8.304965e-01 [26,] 1.886705e-01 3.773410e-01 8.113295e-01 [27,] 2.005142e-01 4.010284e-01 7.994858e-01 [28,] 2.135317e-01 4.270635e-01 7.864683e-01 [29,] 2.082083e-01 4.164167e-01 7.917917e-01 [30,] 1.857450e-01 3.714900e-01 8.142550e-01 [31,] 1.615205e-01 3.230411e-01 8.384795e-01 [32,] 1.361637e-01 2.723274e-01 8.638363e-01 [33,] 1.206461e-01 2.412923e-01 8.793539e-01 [34,] 1.033167e-01 2.066333e-01 8.966833e-01 [35,] 9.043246e-02 1.808649e-01 9.095675e-01 [36,] 8.017690e-02 1.603538e-01 9.198231e-01 [37,] 6.677307e-02 1.335461e-01 9.332269e-01 [38,] 5.357611e-02 1.071522e-01 9.464239e-01 [39,] 4.385962e-02 8.771924e-02 9.561404e-01 [40,] 3.508238e-02 7.016475e-02 9.649176e-01 [41,] 2.681128e-02 5.362256e-02 9.731887e-01 [42,] 2.038222e-02 4.076444e-02 9.796178e-01 [43,] 1.548414e-02 3.096829e-02 9.845159e-01 [44,] 1.173797e-02 2.347594e-02 9.882620e-01 [45,] 8.971493e-03 1.794299e-02 9.910285e-01 [46,] 6.598154e-03 1.319631e-02 9.934018e-01 [47,] 5.225848e-03 1.045170e-02 9.947742e-01 [48,] 3.953849e-03 7.907699e-03 9.960462e-01 [49,] 2.817605e-03 5.635211e-03 9.971824e-01 [50,] 2.002056e-03 4.004113e-03 9.979979e-01 [51,] 1.505017e-03 3.010033e-03 9.984950e-01 [52,] 1.114071e-03 2.228142e-03 9.988859e-01 [53,] 7.896167e-04 1.579233e-03 9.992104e-01 [54,] 5.406139e-04 1.081228e-03 9.994594e-01 [55,] 3.712143e-04 7.424287e-04 9.996288e-01 [56,] 2.727382e-04 5.454765e-04 9.997273e-01 [57,] 2.331913e-04 4.663825e-04 9.997668e-01 [58,] 4.118396e-04 8.236793e-04 9.995882e-01 [59,] 8.765142e-04 1.753028e-03 9.991235e-01 [60,] 2.194295e-03 4.388590e-03 9.978057e-01 [61,] 4.899728e-03 9.799456e-03 9.951003e-01 [62,] 9.050974e-03 1.810195e-02 9.909490e-01 [63,] 1.137394e-02 2.274787e-02 9.886261e-01 [64,] 1.358488e-02 2.716976e-02 9.864151e-01 [65,] 1.672882e-02 3.345763e-02 9.832712e-01 [66,] 2.073804e-02 4.147608e-02 9.792620e-01 [67,] 2.082970e-02 4.165940e-02 9.791703e-01 [68,] 2.050928e-02 4.101855e-02 9.794907e-01 [69,] 1.866329e-02 3.732658e-02 9.813367e-01 [70,] 1.718755e-02 3.437509e-02 9.828125e-01 [71,] 1.440515e-02 2.881031e-02 9.855948e-01 [72,] 1.177998e-02 2.355996e-02 9.882200e-01 [73,] 9.928386e-03 1.985677e-02 9.900716e-01 [74,] 7.809531e-03 1.561906e-02 9.921905e-01 [75,] 6.022653e-03 1.204531e-02 9.939773e-01 [76,] 4.580369e-03 9.160739e-03 9.954196e-01 [77,] 3.458107e-03 6.916213e-03 9.965419e-01 [78,] 2.585248e-03 5.170496e-03 9.974148e-01 [79,] 1.931430e-03 3.862860e-03 9.980686e-01 [80,] 1.440476e-03 2.880951e-03 9.985595e-01 [81,] 1.069195e-03 2.138391e-03 9.989308e-01 [82,] 7.791116e-04 1.558223e-03 9.992209e-01 [83,] 5.631928e-04 1.126386e-03 9.994368e-01 [84,] 4.067110e-04 8.134219e-04 9.995933e-01 [85,] 2.895536e-04 5.791072e-04 9.997104e-01 [86,] 2.126651e-04 4.253303e-04 9.997873e-01 [87,] 1.571402e-04 3.142804e-04 9.998429e-01 [88,] 1.112534e-04 2.225067e-04 9.998887e-01 [89,] 7.728686e-05 1.545737e-04 9.999227e-01 [90,] 5.349691e-05 1.069938e-04 9.999465e-01 [91,] 3.678746e-05 7.357491e-05 9.999632e-01 [92,] 2.539373e-05 5.078747e-05 9.999746e-01 [93,] 1.743979e-05 3.487957e-05 9.999826e-01 [94,] 1.184134e-05 2.368269e-05 9.999882e-01 [95,] 7.966191e-06 1.593238e-05 9.999920e-01 [96,] 5.367555e-06 1.073511e-05 9.999946e-01 [97,] 3.541271e-06 7.082543e-06 9.999965e-01 [98,] 2.321893e-06 4.643787e-06 9.999977e-01 [99,] 1.571963e-06 3.143926e-06 9.999984e-01 [100,] 1.021049e-06 2.042098e-06 9.999990e-01 [101,] 6.591092e-07 1.318218e-06 9.999993e-01 [102,] 4.227043e-07 8.454087e-07 9.999996e-01 [103,] 2.759551e-07 5.519102e-07 9.999997e-01 [104,] 2.153307e-07 4.306614e-07 9.999998e-01 [105,] 1.860487e-07 3.720973e-07 9.999998e-01 [106,] 2.706025e-07 5.412050e-07 9.999997e-01 [107,] 8.081169e-07 1.616234e-06 9.999992e-01 [108,] 3.062428e-06 6.124856e-06 9.999969e-01 [109,] 1.343201e-05 2.686403e-05 9.999866e-01 [110,] 4.466555e-05 8.933110e-05 9.999553e-01 [111,] 1.197760e-04 2.395520e-04 9.998802e-01 [112,] 2.800730e-04 5.601461e-04 9.997199e-01 [113,] 4.963992e-04 9.927983e-04 9.995036e-01 [114,] 5.936114e-04 1.187223e-03 9.994064e-01 [115,] 6.388656e-04 1.277731e-03 9.993611e-01 [116,] 6.048981e-04 1.209796e-03 9.993951e-01 [117,] 6.531668e-04 1.306334e-03 9.993468e-01 [118,] 6.652422e-04 1.330484e-03 9.993348e-01 [119,] 6.376682e-04 1.275336e-03 9.993623e-01 [120,] 5.591770e-04 1.118354e-03 9.994408e-01 [121,] 4.445372e-04 8.890744e-04 9.995555e-01 [122,] 3.529306e-04 7.058612e-04 9.996471e-01 [123,] 2.651718e-04 5.303437e-04 9.997348e-01 [124,] 2.003351e-04 4.006703e-04 9.997997e-01 [125,] 1.514782e-04 3.029564e-04 9.998485e-01 [126,] 1.145221e-04 2.290443e-04 9.998855e-01 [127,] 8.970276e-05 1.794055e-04 9.999103e-01 [128,] 7.435573e-05 1.487115e-04 9.999256e-01 [129,] 5.874408e-05 1.174882e-04 9.999413e-01 [130,] 4.476399e-05 8.952797e-05 9.999552e-01 [131,] 3.316804e-05 6.633608e-05 9.999668e-01 [132,] 2.636723e-05 5.273446e-05 9.999736e-01 [133,] 2.035122e-05 4.070245e-05 9.999796e-01 [134,] 1.574965e-05 3.149931e-05 9.999843e-01 [135,] 1.212650e-05 2.425301e-05 9.999879e-01 [136,] 9.126001e-06 1.825200e-05 9.999909e-01 [137,] 7.147853e-06 1.429571e-05 9.999929e-01 [138,] 5.277628e-06 1.055526e-05 9.999947e-01 [139,] 4.406404e-06 8.812808e-06 9.999956e-01 [140,] 4.124997e-06 8.249994e-06 9.999959e-01 [141,] 5.641322e-06 1.128264e-05 9.999944e-01 [142,] 8.984986e-06 1.796997e-05 9.999910e-01 [143,] 1.810134e-05 3.620267e-05 9.999819e-01 [144,] 3.498359e-05 6.996718e-05 9.999650e-01 [145,] 5.713911e-05 1.142782e-04 9.999429e-01 [146,] 9.318572e-05 1.863714e-04 9.999068e-01 [147,] 1.478827e-04 2.957654e-04 9.998521e-01 [148,] 2.063180e-04 4.126359e-04 9.997937e-01 [149,] 2.480518e-04 4.961036e-04 9.997519e-01 [150,] 2.612049e-04 5.224098e-04 9.997388e-01 [151,] 2.764528e-04 5.529056e-04 9.997235e-01 [152,] 2.789449e-04 5.578898e-04 9.997211e-01 [153,] 3.004060e-04 6.008119e-04 9.996996e-01 [154,] 2.990310e-04 5.980620e-04 9.997010e-01 [155,] 2.819456e-04 5.638913e-04 9.997181e-01 [156,] 2.794314e-04 5.588627e-04 9.997206e-01 [157,] 2.834838e-04 5.669676e-04 9.997165e-01 [158,] 3.253320e-04 6.506640e-04 9.996747e-01 [159,] 2.889902e-04 5.779804e-04 9.997110e-01 [160,] 2.632399e-04 5.264798e-04 9.997368e-01 [161,] 2.561812e-04 5.123623e-04 9.997438e-01 [162,] 2.373335e-04 4.746671e-04 9.997627e-01 [163,] 2.198351e-04 4.396702e-04 9.997802e-01 [164,] 2.234738e-04 4.469476e-04 9.997765e-01 [165,] 2.391894e-04 4.783787e-04 9.997608e-01 [166,] 2.615803e-04 5.231607e-04 9.997384e-01 [167,] 3.157300e-04 6.314599e-04 9.996843e-01 [168,] 3.633020e-04 7.266040e-04 9.996367e-01 [169,] 4.309606e-04 8.619211e-04 9.995690e-01 [170,] 5.763478e-04 1.152696e-03 9.994237e-01 [171,] 6.240925e-04 1.248185e-03 9.993759e-01 [172,] 6.654463e-04 1.330893e-03 9.993346e-01 [173,] 7.061806e-04 1.412361e-03 9.992938e-01 [174,] 7.257548e-04 1.451510e-03 9.992742e-01 [175,] 7.739410e-04 1.547882e-03 9.992261e-01 [176,] 9.562546e-04 1.912509e-03 9.990437e-01 [177,] 1.208457e-03 2.416913e-03 9.987915e-01 [178,] 1.461129e-03 2.922259e-03 9.985389e-01 [179,] 1.722647e-03 3.445295e-03 9.982774e-01 [180,] 2.124320e-03 4.248639e-03 9.978757e-01 [181,] 2.769511e-03 5.539023e-03 9.972305e-01 [182,] 3.707169e-03 7.414338e-03 9.962928e-01 [183,] 4.329541e-03 8.659083e-03 9.956705e-01 [184,] 4.633960e-03 9.267920e-03 9.953660e-01 [185,] 5.170571e-03 1.034114e-02 9.948294e-01 [186,] 5.579033e-03 1.115807e-02 9.944210e-01 [187,] 6.232205e-03 1.246441e-02 9.937678e-01 [188,] 7.210617e-03 1.442123e-02 9.927894e-01 [189,] 8.943801e-03 1.788760e-02 9.910562e-01 [190,] 1.006952e-02 2.013905e-02 9.899305e-01 [191,] 1.177567e-02 2.355133e-02 9.882243e-01 [192,] 1.378540e-02 2.757079e-02 9.862146e-01 [193,] 1.728738e-02 3.457476e-02 9.827126e-01 [194,] 2.225002e-02 4.450004e-02 9.777500e-01 [195,] 2.400416e-02 4.800832e-02 9.759958e-01 [196,] 2.538656e-02 5.077312e-02 9.746134e-01 [197,] 2.718012e-02 5.436024e-02 9.728199e-01 [198,] 2.840620e-02 5.681240e-02 9.715938e-01 [199,] 2.992221e-02 5.984441e-02 9.700778e-01 [200,] 3.261960e-02 6.523920e-02 9.673804e-01 [201,] 3.688957e-02 7.377913e-02 9.631104e-01 [202,] 4.047083e-02 8.094166e-02 9.595292e-01 [203,] 4.674818e-02 9.349636e-02 9.532518e-01 [204,] 5.242855e-02 1.048571e-01 9.475714e-01 [205,] 5.852309e-02 1.170462e-01 9.414769e-01 [206,] 6.533498e-02 1.306700e-01 9.346650e-01 [207,] 6.350399e-02 1.270080e-01 9.364960e-01 [208,] 6.317009e-02 1.263402e-01 9.368299e-01 [209,] 6.250530e-02 1.250106e-01 9.374947e-01 [210,] 6.163108e-02 1.232622e-01 9.383689e-01 [211,] 6.008987e-02 1.201797e-01 9.399101e-01 [212,] 6.019417e-02 1.203883e-01 9.398058e-01 [213,] 6.105813e-02 1.221163e-01 9.389419e-01 [214,] 6.122306e-02 1.224461e-01 9.387769e-01 [215,] 6.207116e-02 1.241423e-01 9.379288e-01 [216,] 6.313280e-02 1.262656e-01 9.368672e-01 [217,] 6.391184e-02 1.278237e-01 9.360882e-01 [218,] 6.554641e-02 1.310928e-01 9.344536e-01 [219,] 5.957510e-02 1.191502e-01 9.404249e-01 [220,] 5.429652e-02 1.085930e-01 9.457035e-01 [221,] 4.958568e-02 9.917136e-02 9.504143e-01 [222,] 4.440197e-02 8.880395e-02 9.555980e-01 [223,] 4.041149e-02 8.082298e-02 9.595885e-01 [224,] 3.683753e-02 7.367506e-02 9.631625e-01 [225,] 3.439921e-02 6.879842e-02 9.656008e-01 [226,] 3.376874e-02 6.753748e-02 9.662313e-01 [227,] 3.191627e-02 6.383254e-02 9.680837e-01 [228,] 3.129901e-02 6.259801e-02 9.687010e-01 [229,] 3.118696e-02 6.237391e-02 9.688130e-01 [230,] 3.092925e-02 6.185850e-02 9.690708e-01 [231,] 2.649853e-02 5.299706e-02 9.735015e-01 [232,] 2.307740e-02 4.615480e-02 9.769226e-01 [233,] 2.057541e-02 4.115083e-02 9.794246e-01 [234,] 1.825318e-02 3.650637e-02 9.817468e-01 [235,] 1.591503e-02 3.183005e-02 9.840850e-01 [236,] 1.436821e-02 2.873641e-02 9.856318e-01 [237,] 1.371028e-02 2.742055e-02 9.862897e-01 [238,] 1.579632e-02 3.159264e-02 9.842037e-01 [239,] 1.871673e-02 3.743347e-02 9.812833e-01 [240,] 2.134093e-02 4.268185e-02 9.786591e-01 [241,] 2.162516e-02 4.325033e-02 9.783748e-01 [242,] 2.196176e-02 4.392352e-02 9.780382e-01 [243,] 2.064392e-02 4.128785e-02 9.793561e-01 [244,] 1.943660e-02 3.887319e-02 9.805634e-01 [245,] 1.828244e-02 3.656489e-02 9.817176e-01 [246,] 1.609857e-02 3.219713e-02 9.839014e-01 [247,] 1.387793e-02 2.775586e-02 9.861221e-01 [248,] 1.341528e-02 2.683057e-02 9.865847e-01 [249,] 1.351774e-02 2.703549e-02 9.864823e-01 [250,] 1.542953e-02 3.085905e-02 9.845705e-01 [251,] 1.528939e-02 3.057878e-02 9.847106e-01 [252,] 1.406685e-02 2.813370e-02 9.859332e-01 [253,] 1.180037e-02 2.360073e-02 9.881996e-01 [254,] 9.648984e-03 1.929797e-02 9.903510e-01 [255,] 8.042767e-03 1.608553e-02 9.919572e-01 [256,] 6.716032e-03 1.343206e-02 9.932840e-01 [257,] 5.570381e-03 1.114076e-02 9.944296e-01 [258,] 4.800452e-03 9.600903e-03 9.951995e-01 [259,] 4.261380e-03 8.522760e-03 9.957386e-01 [260,] 3.963536e-03 7.927073e-03 9.960365e-01 [261,] 3.714751e-03 7.429502e-03 9.962852e-01 [262,] 3.401003e-03 6.802005e-03 9.965990e-01 [263,] 3.023063e-03 6.046127e-03 9.969769e-01 [264,] 2.636437e-03 5.272874e-03 9.973636e-01 [265,] 2.246715e-03 4.493430e-03 9.977533e-01 [266,] 1.871998e-03 3.743995e-03 9.981280e-01 [267,] 1.717296e-03 3.434591e-03 9.982827e-01 [268,] 1.613667e-03 3.227333e-03 9.983863e-01 [269,] 1.550378e-03 3.100755e-03 9.984496e-01 [270,] 1.440428e-03 2.880856e-03 9.985596e-01 [271,] 1.283115e-03 2.566229e-03 9.987169e-01 [272,] 1.160336e-03 2.320672e-03 9.988397e-01 [273,] 9.930998e-04 1.986200e-03 9.990069e-01 [274,] 8.204625e-04 1.640925e-03 9.991795e-01 [275,] 6.542974e-04 1.308595e-03 9.993457e-01 [276,] 5.173314e-04 1.034663e-03 9.994827e-01 [277,] 3.951390e-04 7.902781e-04 9.996049e-01 [278,] 2.921534e-04 5.843068e-04 9.997078e-01 [279,] 2.301754e-04 4.603507e-04 9.997698e-01 [280,] 1.788453e-04 3.576906e-04 9.998212e-01 [281,] 1.376029e-04 2.752057e-04 9.998624e-01 [282,] 1.044486e-04 2.088971e-04 9.998956e-01 [283,] 7.786110e-05 1.557222e-04 9.999221e-01 [284,] 5.577358e-05 1.115472e-04 9.999442e-01 [285,] 4.046887e-05 8.093775e-05 9.999595e-01 [286,] 4.359779e-05 8.719557e-05 9.999564e-01 [287,] 4.502371e-05 9.004742e-05 9.999550e-01 [288,] 4.818289e-05 9.636578e-05 9.999518e-01 [289,] 4.334471e-05 8.668942e-05 9.999567e-01 [290,] 4.151292e-05 8.302584e-05 9.999585e-01 [291,] 4.393757e-05 8.787514e-05 9.999561e-01 [292,] 5.266076e-05 1.053215e-04 9.999473e-01 [293,] 6.590620e-05 1.318124e-04 9.999341e-01 [294,] 8.359803e-05 1.671961e-04 9.999164e-01 [295,] 1.323852e-04 2.647704e-04 9.998676e-01 [296,] 2.213325e-04 4.426651e-04 9.997787e-01 [297,] 4.115827e-04 8.231654e-04 9.995884e-01 [298,] 1.448473e-03 2.896945e-03 9.985515e-01 [299,] 4.973331e-03 9.946661e-03 9.950267e-01 [300,] 1.999962e-02 3.999924e-02 9.800004e-01 [301,] 6.113288e-02 1.222658e-01 9.388671e-01 [302,] 1.558521e-01 3.117042e-01 8.441479e-01 [303,] 3.496115e-01 6.992229e-01 6.503885e-01 [304,] 6.476623e-01 7.046753e-01 3.523377e-01 [305,] 9.266567e-01 1.466867e-01 7.334334e-02 [306,] 9.926918e-01 1.461647e-02 7.308237e-03 [307,] 9.999403e-01 1.194157e-04 5.970783e-05 [308,] 1.000000e+00 6.978411e-08 3.489206e-08 [309,] 1.000000e+00 1.348629e-12 6.743144e-13 [310,] 1.000000e+00 1.914665e-13 9.573327e-14 [311,] 1.000000e+00 5.485826e-14 2.742913e-14 [312,] 1.000000e+00 9.928580e-14 4.964290e-14 [313,] 1.000000e+00 1.500807e-13 7.504033e-14 [314,] 1.000000e+00 7.532327e-14 3.766164e-14 [315,] 1.000000e+00 1.074530e-13 5.372652e-14 [316,] 1.000000e+00 2.732003e-13 1.366001e-13 [317,] 1.000000e+00 7.028229e-13 3.514115e-13 [318,] 1.000000e+00 2.070062e-12 1.035031e-12 [319,] 1.000000e+00 6.205439e-12 3.102719e-12 [320,] 1.000000e+00 1.072870e-11 5.364350e-12 [321,] 1.000000e+00 2.631817e-11 1.315908e-11 [322,] 1.000000e+00 8.387342e-11 4.193671e-11 [323,] 1.000000e+00 1.583714e-10 7.918569e-11 [324,] 1.000000e+00 1.597947e-10 7.989736e-11 [325,] 1.000000e+00 4.743065e-10 2.371532e-10 [326,] 1.000000e+00 2.755718e-10 1.377859e-10 [327,] 1.000000e+00 6.016100e-10 3.008050e-10 [328,] 1.000000e+00 1.990300e-09 9.951502e-10 [329,] 1.000000e+00 8.176300e-09 4.088150e-09 [330,] 1.000000e+00 2.572813e-08 1.286406e-08 [331,] 1.000000e+00 9.823422e-08 4.911711e-08 [332,] 9.999998e-01 4.549432e-07 2.274716e-07 [333,] 9.999989e-01 2.218635e-06 1.109318e-06 [334,] 9.999953e-01 9.449539e-06 4.724770e-06 [335,] 9.999965e-01 7.035547e-06 3.517774e-06 [336,] 9.999912e-01 1.760145e-05 8.800727e-06 [337,] 9.999588e-01 8.237983e-05 4.118992e-05 [338,] 9.997652e-01 4.696085e-04 2.348043e-04 [339,] 9.997013e-01 5.974102e-04 2.987051e-04 [340,] 9.981847e-01 3.630615e-03 1.815308e-03 [341,] 9.918338e-01 1.633231e-02 8.166154e-03 > postscript(file="/var/fisher/rcomp/tmp/11rh11352547499.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2lcv41352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3srbu1352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4hnxl1352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/593p41352547499.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 6 -14.5037298 21.1994960 27.3672379 42.3898185 23.6285282 -9.6972782 7 8 9 10 11 12 13.3736895 27.2188508 26.6253024 10.6672379 17.1962702 31.9285282 13 14 15 16 17 18 37.6679167 75.6711425 88.8388844 117.1614651 161.6001747 133.8743683 19 20 21 22 23 24 198.8453360 186.7904973 171.7969489 202.5388844 158.6679167 168.2001747 25 26 27 28 29 30 190.7395632 195.1427890 169.6105309 143.7331116 124.0718212 80.1460148 31 32 33 34 35 36 79.4169825 40.2621438 45.0685954 17.0105309 25.0395632 27.8718212 37 38 39 40 41 42 -21.3887903 -42.3855645 -41.6178226 -41.1952419 -37.4565323 -73.9823387 43 44 45 46 47 48 -57.2113710 -52.6662097 -27.5597581 -25.3178226 -23.7887903 -45.6565323 49 50 51 52 53 54 -72.7171438 -74.4139180 -85.9461761 -63.6235954 -48.4848858 -96.2106922 55 56 57 58 59 60 -68.1397245 -53.6945632 -55.5881116 -64.9461761 -75.6171438 -82.9848858 61 62 63 64 65 66 -97.5454973 -124.2422715 -115.5745296 -83.0519489 -85.3132392 -138.4390457 67 68 69 70 71 72 -117.8680780 -106.5229167 -78.7164651 -67.9745296 -45.5454973 -13.3132392 73 74 75 76 77 78 33.1261492 65.4293750 93.0971169 112.9196976 114.6584073 44.2326008 79 80 81 82 83 84 66.8035685 77.0487298 90.4551815 55.4971169 52.0261492 38.9584073 85 86 87 88 89 90 31.6977957 11.8010215 6.8687634 32.2913441 5.6300538 -46.7957527 91 92 93 94 95 96 -47.1247849 -28.5796237 -31.2731720 -21.2312366 -18.1022043 -14.0699462 97 98 99 100 101 102 -40.8305578 -48.1273320 -25.5595901 -25.1370094 4.3017003 -30.4241062 103 104 105 106 107 108 -27.1531384 -47.7079772 -50.0015255 -52.7595901 -24.0305578 -20.3982997 109 110 111 112 113 114 -39.0589113 -61.0556855 -65.0879435 -45.6653629 -24.3266532 -47.4524597 115 116 117 118 119 120 -53.4814919 -54.0363306 -39.2298790 -27.5879435 16.5410887 34.5733468 121 122 123 124 125 126 74.5127352 129.8159610 155.9837030 185.8062836 183.1449933 149.5191868 127 128 129 130 131 132 159.7901546 141.8353159 104.0417675 88.6837030 70.1127352 95.9449933 133 134 135 136 137 138 83.6843817 75.7876075 58.0553495 22.9779301 20.4166398 -7.0091667 139 140 141 142 143 144 -1.7381989 3.6069624 5.5134140 24.5553495 42.9843817 29.0166398 145 146 147 148 149 150 15.5560282 -17.6407460 32.4269960 15.6495766 13.4882863 19.9624798 151 152 153 154 155 156 13.9334476 27.7786089 5.2850605 42.9269960 63.8560282 111.6882863 157 158 159 160 161 162 124.9276747 146.9309005 146.0986425 131.4212231 130.3599328 121.8341263 163 164 165 166 167 168 109.4050941 88.4502554 64.9567070 63.2986425 49.0276747 56.5599328 169 170 171 172 173 174 41.2993212 17.4025470 23.8702890 16.7928696 46.2315793 0.2057728 175 176 177 178 179 180 -16.0232594 16.4219019 -5.1716465 -11.8297110 15.2993212 16.2315793 181 182 183 184 185 186 29.6709677 44.0741935 23.5419355 17.5645161 33.7032258 21.4774194 187 188 189 190 191 192 2.8483871 -4.5064516 -15.9000000 -8.0580645 16.2709677 6.8032258 193 194 195 196 197 198 6.5426142 -9.0541599 -10.3864180 -10.8638374 -20.6251277 -0.8509341 199 200 201 202 203 204 -55.8799664 -37.1348051 -48.9283535 -39.8864180 -49.9573858 -43.3251277 205 206 207 208 209 210 -63.3857392 -50.1825134 -75.2147715 -56.9921909 -64.2534812 -52.6792876 211 212 213 214 215 216 -92.7083199 -87.9631586 -103.1567070 -101.0147715 -105.1857392 -117.6534812 217 218 219 220 221 222 -145.3140927 -168.7108669 -158.3431250 -145.4205444 -118.5818347 -111.4076411 223 224 225 226 227 228 -142.8366734 -134.5915121 -149.2850605 -137.6431250 -148.3140927 -142.1818347 229 230 231 232 233 234 -166.0424462 -173.4392204 -174.1714785 -164.2488978 -164.3101882 -120.0359946 235 236 237 238 239 240 -135.1650269 -134.7198656 -122.3134140 -101.1714785 -128.1424462 -148.9101882 241 242 243 244 245 246 -186.7707997 -175.3675739 -188.8998320 -193.7772513 -191.9385417 -133.5643481 247 248 249 250 251 252 -150.5933804 -163.9482191 -163.3417675 -157.5998320 -173.0707997 -191.3385417 253 254 255 256 257 258 -218.8991532 -223.9959274 -219.3281855 -200.9056048 -204.5668952 -168.2927016 259 260 261 262 263 264 -166.3217339 -166.3765726 -140.4701210 -136.8281855 -171.8991532 -182.6668952 265 266 267 268 269 270 -178.0275067 -149.1242809 -132.9565390 -112.1339583 -108.3952487 -52.6210551 271 272 273 274 275 276 -45.7500874 -43.6049261 -19.2984745 -7.1565390 5.5724933 6.0047513 277 278 279 280 281 282 10.5441398 3.4473656 -0.9848925 -10.1623118 -19.6236022 17.2505914 283 284 285 286 287 288 24.0215591 28.2667204 23.2731720 11.7151075 14.1441398 -0.3236022 289 290 291 292 293 294 1.6157863 -11.7809879 -9.2132460 -22.0906653 -36.8519556 -1.3777621 295 296 297 298 299 300 -3.9067944 -4.3616331 -7.1551815 -10.5132460 -52.9842137 -70.4519556 301 302 303 304 305 306 -87.8125672 -80.7093414 -91.7415995 -86.6190188 -103.5803091 -71.5061156 307 308 309 310 311 312 -78.4351478 -81.4899866 -68.6835349 -93.4415995 -86.2125672 -88.4803091 313 314 315 316 317 318 -66.7409207 -63.4376949 -79.6699530 -86.1473723 -81.3086626 -30.4344691 319 320 321 322 323 324 -19.6635013 -26.0183401 22.7881116 22.4300470 64.4590793 104.0913374 325 326 327 328 329 330 238.2307258 241.2339516 268.5016935 253.5242742 254.3629839 276.2371774 331 332 333 334 335 336 263.0081452 242.8533065 242.5597581 230.2016935 206.8307258 200.7629839 337 338 339 340 341 342 225.4023723 201.4055981 172.8733401 148.2959207 110.2346304 172.6088239 343 344 345 346 347 348 187.5797917 193.2249530 180.7314046 176.8733401 181.0023723 171.2346304 349 350 351 352 353 354 180.5740188 196.7772446 163.7449866 103.8675672 82.7062769 140.1804704 355 356 357 358 359 360 111.7514382 124.4965995 109.6030511 103.4449866 93.8740188 44.8062769 361 362 363 364 365 366 73.2456653 47.5488911 43.8166331 3.6392137 1.0779234 15.2521169 367 368 369 370 371 372 49.2230847 29.6682460 33.3746976 15.1166331 9.9456653 17.0779234 > postscript(file="/var/fisher/rcomp/tmp/6d27n1352547499.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 -14.5037298 NA 1 21.1994960 -14.5037298 2 27.3672379 21.1994960 3 42.3898185 27.3672379 4 23.6285282 42.3898185 5 -9.6972782 23.6285282 6 13.3736895 -9.6972782 7 27.2188508 13.3736895 8 26.6253024 27.2188508 9 10.6672379 26.6253024 10 17.1962702 10.6672379 11 31.9285282 17.1962702 12 37.6679167 31.9285282 13 75.6711425 37.6679167 14 88.8388844 75.6711425 15 117.1614651 88.8388844 16 161.6001747 117.1614651 17 133.8743683 161.6001747 18 198.8453360 133.8743683 19 186.7904973 198.8453360 20 171.7969489 186.7904973 21 202.5388844 171.7969489 22 158.6679167 202.5388844 23 168.2001747 158.6679167 24 190.7395632 168.2001747 25 195.1427890 190.7395632 26 169.6105309 195.1427890 27 143.7331116 169.6105309 28 124.0718212 143.7331116 29 80.1460148 124.0718212 30 79.4169825 80.1460148 31 40.2621438 79.4169825 32 45.0685954 40.2621438 33 17.0105309 45.0685954 34 25.0395632 17.0105309 35 27.8718212 25.0395632 36 -21.3887903 27.8718212 37 -42.3855645 -21.3887903 38 -41.6178226 -42.3855645 39 -41.1952419 -41.6178226 40 -37.4565323 -41.1952419 41 -73.9823387 -37.4565323 42 -57.2113710 -73.9823387 43 -52.6662097 -57.2113710 44 -27.5597581 -52.6662097 45 -25.3178226 -27.5597581 46 -23.7887903 -25.3178226 47 -45.6565323 -23.7887903 48 -72.7171438 -45.6565323 49 -74.4139180 -72.7171438 50 -85.9461761 -74.4139180 51 -63.6235954 -85.9461761 52 -48.4848858 -63.6235954 53 -96.2106922 -48.4848858 54 -68.1397245 -96.2106922 55 -53.6945632 -68.1397245 56 -55.5881116 -53.6945632 57 -64.9461761 -55.5881116 58 -75.6171438 -64.9461761 59 -82.9848858 -75.6171438 60 -97.5454973 -82.9848858 61 -124.2422715 -97.5454973 62 -115.5745296 -124.2422715 63 -83.0519489 -115.5745296 64 -85.3132392 -83.0519489 65 -138.4390457 -85.3132392 66 -117.8680780 -138.4390457 67 -106.5229167 -117.8680780 68 -78.7164651 -106.5229167 69 -67.9745296 -78.7164651 70 -45.5454973 -67.9745296 71 -13.3132392 -45.5454973 72 33.1261492 -13.3132392 73 65.4293750 33.1261492 74 93.0971169 65.4293750 75 112.9196976 93.0971169 76 114.6584073 112.9196976 77 44.2326008 114.6584073 78 66.8035685 44.2326008 79 77.0487298 66.8035685 80 90.4551815 77.0487298 81 55.4971169 90.4551815 82 52.0261492 55.4971169 83 38.9584073 52.0261492 84 31.6977957 38.9584073 85 11.8010215 31.6977957 86 6.8687634 11.8010215 87 32.2913441 6.8687634 88 5.6300538 32.2913441 89 -46.7957527 5.6300538 90 -47.1247849 -46.7957527 91 -28.5796237 -47.1247849 92 -31.2731720 -28.5796237 93 -21.2312366 -31.2731720 94 -18.1022043 -21.2312366 95 -14.0699462 -18.1022043 96 -40.8305578 -14.0699462 97 -48.1273320 -40.8305578 98 -25.5595901 -48.1273320 99 -25.1370094 -25.5595901 100 4.3017003 -25.1370094 101 -30.4241062 4.3017003 102 -27.1531384 -30.4241062 103 -47.7079772 -27.1531384 104 -50.0015255 -47.7079772 105 -52.7595901 -50.0015255 106 -24.0305578 -52.7595901 107 -20.3982997 -24.0305578 108 -39.0589113 -20.3982997 109 -61.0556855 -39.0589113 110 -65.0879435 -61.0556855 111 -45.6653629 -65.0879435 112 -24.3266532 -45.6653629 113 -47.4524597 -24.3266532 114 -53.4814919 -47.4524597 115 -54.0363306 -53.4814919 116 -39.2298790 -54.0363306 117 -27.5879435 -39.2298790 118 16.5410887 -27.5879435 119 34.5733468 16.5410887 120 74.5127352 34.5733468 121 129.8159610 74.5127352 122 155.9837030 129.8159610 123 185.8062836 155.9837030 124 183.1449933 185.8062836 125 149.5191868 183.1449933 126 159.7901546 149.5191868 127 141.8353159 159.7901546 128 104.0417675 141.8353159 129 88.6837030 104.0417675 130 70.1127352 88.6837030 131 95.9449933 70.1127352 132 83.6843817 95.9449933 133 75.7876075 83.6843817 134 58.0553495 75.7876075 135 22.9779301 58.0553495 136 20.4166398 22.9779301 137 -7.0091667 20.4166398 138 -1.7381989 -7.0091667 139 3.6069624 -1.7381989 140 5.5134140 3.6069624 141 24.5553495 5.5134140 142 42.9843817 24.5553495 143 29.0166398 42.9843817 144 15.5560282 29.0166398 145 -17.6407460 15.5560282 146 32.4269960 -17.6407460 147 15.6495766 32.4269960 148 13.4882863 15.6495766 149 19.9624798 13.4882863 150 13.9334476 19.9624798 151 27.7786089 13.9334476 152 5.2850605 27.7786089 153 42.9269960 5.2850605 154 63.8560282 42.9269960 155 111.6882863 63.8560282 156 124.9276747 111.6882863 157 146.9309005 124.9276747 158 146.0986425 146.9309005 159 131.4212231 146.0986425 160 130.3599328 131.4212231 161 121.8341263 130.3599328 162 109.4050941 121.8341263 163 88.4502554 109.4050941 164 64.9567070 88.4502554 165 63.2986425 64.9567070 166 49.0276747 63.2986425 167 56.5599328 49.0276747 168 41.2993212 56.5599328 169 17.4025470 41.2993212 170 23.8702890 17.4025470 171 16.7928696 23.8702890 172 46.2315793 16.7928696 173 0.2057728 46.2315793 174 -16.0232594 0.2057728 175 16.4219019 -16.0232594 176 -5.1716465 16.4219019 177 -11.8297110 -5.1716465 178 15.2993212 -11.8297110 179 16.2315793 15.2993212 180 29.6709677 16.2315793 181 44.0741935 29.6709677 182 23.5419355 44.0741935 183 17.5645161 23.5419355 184 33.7032258 17.5645161 185 21.4774194 33.7032258 186 2.8483871 21.4774194 187 -4.5064516 2.8483871 188 -15.9000000 -4.5064516 189 -8.0580645 -15.9000000 190 16.2709677 -8.0580645 191 6.8032258 16.2709677 192 6.5426142 6.8032258 193 -9.0541599 6.5426142 194 -10.3864180 -9.0541599 195 -10.8638374 -10.3864180 196 -20.6251277 -10.8638374 197 -0.8509341 -20.6251277 198 -55.8799664 -0.8509341 199 -37.1348051 -55.8799664 200 -48.9283535 -37.1348051 201 -39.8864180 -48.9283535 202 -49.9573858 -39.8864180 203 -43.3251277 -49.9573858 204 -63.3857392 -43.3251277 205 -50.1825134 -63.3857392 206 -75.2147715 -50.1825134 207 -56.9921909 -75.2147715 208 -64.2534812 -56.9921909 209 -52.6792876 -64.2534812 210 -92.7083199 -52.6792876 211 -87.9631586 -92.7083199 212 -103.1567070 -87.9631586 213 -101.0147715 -103.1567070 214 -105.1857392 -101.0147715 215 -117.6534812 -105.1857392 216 -145.3140927 -117.6534812 217 -168.7108669 -145.3140927 218 -158.3431250 -168.7108669 219 -145.4205444 -158.3431250 220 -118.5818347 -145.4205444 221 -111.4076411 -118.5818347 222 -142.8366734 -111.4076411 223 -134.5915121 -142.8366734 224 -149.2850605 -134.5915121 225 -137.6431250 -149.2850605 226 -148.3140927 -137.6431250 227 -142.1818347 -148.3140927 228 -166.0424462 -142.1818347 229 -173.4392204 -166.0424462 230 -174.1714785 -173.4392204 231 -164.2488978 -174.1714785 232 -164.3101882 -164.2488978 233 -120.0359946 -164.3101882 234 -135.1650269 -120.0359946 235 -134.7198656 -135.1650269 236 -122.3134140 -134.7198656 237 -101.1714785 -122.3134140 238 -128.1424462 -101.1714785 239 -148.9101882 -128.1424462 240 -186.7707997 -148.9101882 241 -175.3675739 -186.7707997 242 -188.8998320 -175.3675739 243 -193.7772513 -188.8998320 244 -191.9385417 -193.7772513 245 -133.5643481 -191.9385417 246 -150.5933804 -133.5643481 247 -163.9482191 -150.5933804 248 -163.3417675 -163.9482191 249 -157.5998320 -163.3417675 250 -173.0707997 -157.5998320 251 -191.3385417 -173.0707997 252 -218.8991532 -191.3385417 253 -223.9959274 -218.8991532 254 -219.3281855 -223.9959274 255 -200.9056048 -219.3281855 256 -204.5668952 -200.9056048 257 -168.2927016 -204.5668952 258 -166.3217339 -168.2927016 259 -166.3765726 -166.3217339 260 -140.4701210 -166.3765726 261 -136.8281855 -140.4701210 262 -171.8991532 -136.8281855 263 -182.6668952 -171.8991532 264 -178.0275067 -182.6668952 265 -149.1242809 -178.0275067 266 -132.9565390 -149.1242809 267 -112.1339583 -132.9565390 268 -108.3952487 -112.1339583 269 -52.6210551 -108.3952487 270 -45.7500874 -52.6210551 271 -43.6049261 -45.7500874 272 -19.2984745 -43.6049261 273 -7.1565390 -19.2984745 274 5.5724933 -7.1565390 275 6.0047513 5.5724933 276 10.5441398 6.0047513 277 3.4473656 10.5441398 278 -0.9848925 3.4473656 279 -10.1623118 -0.9848925 280 -19.6236022 -10.1623118 281 17.2505914 -19.6236022 282 24.0215591 17.2505914 283 28.2667204 24.0215591 284 23.2731720 28.2667204 285 11.7151075 23.2731720 286 14.1441398 11.7151075 287 -0.3236022 14.1441398 288 1.6157863 -0.3236022 289 -11.7809879 1.6157863 290 -9.2132460 -11.7809879 291 -22.0906653 -9.2132460 292 -36.8519556 -22.0906653 293 -1.3777621 -36.8519556 294 -3.9067944 -1.3777621 295 -4.3616331 -3.9067944 296 -7.1551815 -4.3616331 297 -10.5132460 -7.1551815 298 -52.9842137 -10.5132460 299 -70.4519556 -52.9842137 300 -87.8125672 -70.4519556 301 -80.7093414 -87.8125672 302 -91.7415995 -80.7093414 303 -86.6190188 -91.7415995 304 -103.5803091 -86.6190188 305 -71.5061156 -103.5803091 306 -78.4351478 -71.5061156 307 -81.4899866 -78.4351478 308 -68.6835349 -81.4899866 309 -93.4415995 -68.6835349 310 -86.2125672 -93.4415995 311 -88.4803091 -86.2125672 312 -66.7409207 -88.4803091 313 -63.4376949 -66.7409207 314 -79.6699530 -63.4376949 315 -86.1473723 -79.6699530 316 -81.3086626 -86.1473723 317 -30.4344691 -81.3086626 318 -19.6635013 -30.4344691 319 -26.0183401 -19.6635013 320 22.7881116 -26.0183401 321 22.4300470 22.7881116 322 64.4590793 22.4300470 323 104.0913374 64.4590793 324 238.2307258 104.0913374 325 241.2339516 238.2307258 326 268.5016935 241.2339516 327 253.5242742 268.5016935 328 254.3629839 253.5242742 329 276.2371774 254.3629839 330 263.0081452 276.2371774 331 242.8533065 263.0081452 332 242.5597581 242.8533065 333 230.2016935 242.5597581 334 206.8307258 230.2016935 335 200.7629839 206.8307258 336 225.4023723 200.7629839 337 201.4055981 225.4023723 338 172.8733401 201.4055981 339 148.2959207 172.8733401 340 110.2346304 148.2959207 341 172.6088239 110.2346304 342 187.5797917 172.6088239 343 193.2249530 187.5797917 344 180.7314046 193.2249530 345 176.8733401 180.7314046 346 181.0023723 176.8733401 347 171.2346304 181.0023723 348 180.5740188 171.2346304 349 196.7772446 180.5740188 350 163.7449866 196.7772446 351 103.8675672 163.7449866 352 82.7062769 103.8675672 353 140.1804704 82.7062769 354 111.7514382 140.1804704 355 124.4965995 111.7514382 356 109.6030511 124.4965995 357 103.4449866 109.6030511 358 93.8740188 103.4449866 359 44.8062769 93.8740188 360 73.2456653 44.8062769 361 47.5488911 73.2456653 362 43.8166331 47.5488911 363 3.6392137 43.8166331 364 1.0779234 3.6392137 365 15.2521169 1.0779234 366 49.2230847 15.2521169 367 29.6682460 49.2230847 368 33.3746976 29.6682460 369 15.1166331 33.3746976 370 9.9456653 15.1166331 371 17.0779234 9.9456653 372 NA 17.0779234 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 21.1994960 -14.5037298 [2,] 27.3672379 21.1994960 [3,] 42.3898185 27.3672379 [4,] 23.6285282 42.3898185 [5,] -9.6972782 23.6285282 [6,] 13.3736895 -9.6972782 [7,] 27.2188508 13.3736895 [8,] 26.6253024 27.2188508 [9,] 10.6672379 26.6253024 [10,] 17.1962702 10.6672379 [11,] 31.9285282 17.1962702 [12,] 37.6679167 31.9285282 [13,] 75.6711425 37.6679167 [14,] 88.8388844 75.6711425 [15,] 117.1614651 88.8388844 [16,] 161.6001747 117.1614651 [17,] 133.8743683 161.6001747 [18,] 198.8453360 133.8743683 [19,] 186.7904973 198.8453360 [20,] 171.7969489 186.7904973 [21,] 202.5388844 171.7969489 [22,] 158.6679167 202.5388844 [23,] 168.2001747 158.6679167 [24,] 190.7395632 168.2001747 [25,] 195.1427890 190.7395632 [26,] 169.6105309 195.1427890 [27,] 143.7331116 169.6105309 [28,] 124.0718212 143.7331116 [29,] 80.1460148 124.0718212 [30,] 79.4169825 80.1460148 [31,] 40.2621438 79.4169825 [32,] 45.0685954 40.2621438 [33,] 17.0105309 45.0685954 [34,] 25.0395632 17.0105309 [35,] 27.8718212 25.0395632 [36,] -21.3887903 27.8718212 [37,] -42.3855645 -21.3887903 [38,] -41.6178226 -42.3855645 [39,] -41.1952419 -41.6178226 [40,] -37.4565323 -41.1952419 [41,] -73.9823387 -37.4565323 [42,] -57.2113710 -73.9823387 [43,] -52.6662097 -57.2113710 [44,] -27.5597581 -52.6662097 [45,] -25.3178226 -27.5597581 [46,] -23.7887903 -25.3178226 [47,] -45.6565323 -23.7887903 [48,] -72.7171438 -45.6565323 [49,] -74.4139180 -72.7171438 [50,] -85.9461761 -74.4139180 [51,] -63.6235954 -85.9461761 [52,] -48.4848858 -63.6235954 [53,] -96.2106922 -48.4848858 [54,] -68.1397245 -96.2106922 [55,] -53.6945632 -68.1397245 [56,] -55.5881116 -53.6945632 [57,] -64.9461761 -55.5881116 [58,] -75.6171438 -64.9461761 [59,] -82.9848858 -75.6171438 [60,] -97.5454973 -82.9848858 [61,] -124.2422715 -97.5454973 [62,] -115.5745296 -124.2422715 [63,] -83.0519489 -115.5745296 [64,] -85.3132392 -83.0519489 [65,] -138.4390457 -85.3132392 [66,] -117.8680780 -138.4390457 [67,] -106.5229167 -117.8680780 [68,] -78.7164651 -106.5229167 [69,] -67.9745296 -78.7164651 [70,] -45.5454973 -67.9745296 [71,] -13.3132392 -45.5454973 [72,] 33.1261492 -13.3132392 [73,] 65.4293750 33.1261492 [74,] 93.0971169 65.4293750 [75,] 112.9196976 93.0971169 [76,] 114.6584073 112.9196976 [77,] 44.2326008 114.6584073 [78,] 66.8035685 44.2326008 [79,] 77.0487298 66.8035685 [80,] 90.4551815 77.0487298 [81,] 55.4971169 90.4551815 [82,] 52.0261492 55.4971169 [83,] 38.9584073 52.0261492 [84,] 31.6977957 38.9584073 [85,] 11.8010215 31.6977957 [86,] 6.8687634 11.8010215 [87,] 32.2913441 6.8687634 [88,] 5.6300538 32.2913441 [89,] -46.7957527 5.6300538 [90,] -47.1247849 -46.7957527 [91,] -28.5796237 -47.1247849 [92,] -31.2731720 -28.5796237 [93,] -21.2312366 -31.2731720 [94,] -18.1022043 -21.2312366 [95,] -14.0699462 -18.1022043 [96,] -40.8305578 -14.0699462 [97,] -48.1273320 -40.8305578 [98,] -25.5595901 -48.1273320 [99,] -25.1370094 -25.5595901 [100,] 4.3017003 -25.1370094 [101,] -30.4241062 4.3017003 [102,] -27.1531384 -30.4241062 [103,] -47.7079772 -27.1531384 [104,] -50.0015255 -47.7079772 [105,] -52.7595901 -50.0015255 [106,] -24.0305578 -52.7595901 [107,] -20.3982997 -24.0305578 [108,] -39.0589113 -20.3982997 [109,] -61.0556855 -39.0589113 [110,] -65.0879435 -61.0556855 [111,] -45.6653629 -65.0879435 [112,] -24.3266532 -45.6653629 [113,] -47.4524597 -24.3266532 [114,] -53.4814919 -47.4524597 [115,] -54.0363306 -53.4814919 [116,] -39.2298790 -54.0363306 [117,] -27.5879435 -39.2298790 [118,] 16.5410887 -27.5879435 [119,] 34.5733468 16.5410887 [120,] 74.5127352 34.5733468 [121,] 129.8159610 74.5127352 [122,] 155.9837030 129.8159610 [123,] 185.8062836 155.9837030 [124,] 183.1449933 185.8062836 [125,] 149.5191868 183.1449933 [126,] 159.7901546 149.5191868 [127,] 141.8353159 159.7901546 [128,] 104.0417675 141.8353159 [129,] 88.6837030 104.0417675 [130,] 70.1127352 88.6837030 [131,] 95.9449933 70.1127352 [132,] 83.6843817 95.9449933 [133,] 75.7876075 83.6843817 [134,] 58.0553495 75.7876075 [135,] 22.9779301 58.0553495 [136,] 20.4166398 22.9779301 [137,] -7.0091667 20.4166398 [138,] -1.7381989 -7.0091667 [139,] 3.6069624 -1.7381989 [140,] 5.5134140 3.6069624 [141,] 24.5553495 5.5134140 [142,] 42.9843817 24.5553495 [143,] 29.0166398 42.9843817 [144,] 15.5560282 29.0166398 [145,] -17.6407460 15.5560282 [146,] 32.4269960 -17.6407460 [147,] 15.6495766 32.4269960 [148,] 13.4882863 15.6495766 [149,] 19.9624798 13.4882863 [150,] 13.9334476 19.9624798 [151,] 27.7786089 13.9334476 [152,] 5.2850605 27.7786089 [153,] 42.9269960 5.2850605 [154,] 63.8560282 42.9269960 [155,] 111.6882863 63.8560282 [156,] 124.9276747 111.6882863 [157,] 146.9309005 124.9276747 [158,] 146.0986425 146.9309005 [159,] 131.4212231 146.0986425 [160,] 130.3599328 131.4212231 [161,] 121.8341263 130.3599328 [162,] 109.4050941 121.8341263 [163,] 88.4502554 109.4050941 [164,] 64.9567070 88.4502554 [165,] 63.2986425 64.9567070 [166,] 49.0276747 63.2986425 [167,] 56.5599328 49.0276747 [168,] 41.2993212 56.5599328 [169,] 17.4025470 41.2993212 [170,] 23.8702890 17.4025470 [171,] 16.7928696 23.8702890 [172,] 46.2315793 16.7928696 [173,] 0.2057728 46.2315793 [174,] -16.0232594 0.2057728 [175,] 16.4219019 -16.0232594 [176,] -5.1716465 16.4219019 [177,] -11.8297110 -5.1716465 [178,] 15.2993212 -11.8297110 [179,] 16.2315793 15.2993212 [180,] 29.6709677 16.2315793 [181,] 44.0741935 29.6709677 [182,] 23.5419355 44.0741935 [183,] 17.5645161 23.5419355 [184,] 33.7032258 17.5645161 [185,] 21.4774194 33.7032258 [186,] 2.8483871 21.4774194 [187,] -4.5064516 2.8483871 [188,] -15.9000000 -4.5064516 [189,] -8.0580645 -15.9000000 [190,] 16.2709677 -8.0580645 [191,] 6.8032258 16.2709677 [192,] 6.5426142 6.8032258 [193,] -9.0541599 6.5426142 [194,] -10.3864180 -9.0541599 [195,] -10.8638374 -10.3864180 [196,] -20.6251277 -10.8638374 [197,] -0.8509341 -20.6251277 [198,] -55.8799664 -0.8509341 [199,] -37.1348051 -55.8799664 [200,] -48.9283535 -37.1348051 [201,] -39.8864180 -48.9283535 [202,] -49.9573858 -39.8864180 [203,] -43.3251277 -49.9573858 [204,] -63.3857392 -43.3251277 [205,] -50.1825134 -63.3857392 [206,] -75.2147715 -50.1825134 [207,] -56.9921909 -75.2147715 [208,] -64.2534812 -56.9921909 [209,] -52.6792876 -64.2534812 [210,] -92.7083199 -52.6792876 [211,] -87.9631586 -92.7083199 [212,] -103.1567070 -87.9631586 [213,] -101.0147715 -103.1567070 [214,] -105.1857392 -101.0147715 [215,] -117.6534812 -105.1857392 [216,] -145.3140927 -117.6534812 [217,] -168.7108669 -145.3140927 [218,] -158.3431250 -168.7108669 [219,] -145.4205444 -158.3431250 [220,] -118.5818347 -145.4205444 [221,] -111.4076411 -118.5818347 [222,] -142.8366734 -111.4076411 [223,] -134.5915121 -142.8366734 [224,] -149.2850605 -134.5915121 [225,] -137.6431250 -149.2850605 [226,] -148.3140927 -137.6431250 [227,] -142.1818347 -148.3140927 [228,] -166.0424462 -142.1818347 [229,] -173.4392204 -166.0424462 [230,] -174.1714785 -173.4392204 [231,] -164.2488978 -174.1714785 [232,] -164.3101882 -164.2488978 [233,] -120.0359946 -164.3101882 [234,] -135.1650269 -120.0359946 [235,] -134.7198656 -135.1650269 [236,] -122.3134140 -134.7198656 [237,] -101.1714785 -122.3134140 [238,] -128.1424462 -101.1714785 [239,] -148.9101882 -128.1424462 [240,] -186.7707997 -148.9101882 [241,] -175.3675739 -186.7707997 [242,] -188.8998320 -175.3675739 [243,] -193.7772513 -188.8998320 [244,] -191.9385417 -193.7772513 [245,] -133.5643481 -191.9385417 [246,] -150.5933804 -133.5643481 [247,] -163.9482191 -150.5933804 [248,] -163.3417675 -163.9482191 [249,] -157.5998320 -163.3417675 [250,] -173.0707997 -157.5998320 [251,] -191.3385417 -173.0707997 [252,] -218.8991532 -191.3385417 [253,] -223.9959274 -218.8991532 [254,] -219.3281855 -223.9959274 [255,] -200.9056048 -219.3281855 [256,] -204.5668952 -200.9056048 [257,] -168.2927016 -204.5668952 [258,] -166.3217339 -168.2927016 [259,] -166.3765726 -166.3217339 [260,] -140.4701210 -166.3765726 [261,] -136.8281855 -140.4701210 [262,] -171.8991532 -136.8281855 [263,] -182.6668952 -171.8991532 [264,] -178.0275067 -182.6668952 [265,] -149.1242809 -178.0275067 [266,] -132.9565390 -149.1242809 [267,] -112.1339583 -132.9565390 [268,] -108.3952487 -112.1339583 [269,] -52.6210551 -108.3952487 [270,] -45.7500874 -52.6210551 [271,] -43.6049261 -45.7500874 [272,] -19.2984745 -43.6049261 [273,] -7.1565390 -19.2984745 [274,] 5.5724933 -7.1565390 [275,] 6.0047513 5.5724933 [276,] 10.5441398 6.0047513 [277,] 3.4473656 10.5441398 [278,] -0.9848925 3.4473656 [279,] -10.1623118 -0.9848925 [280,] -19.6236022 -10.1623118 [281,] 17.2505914 -19.6236022 [282,] 24.0215591 17.2505914 [283,] 28.2667204 24.0215591 [284,] 23.2731720 28.2667204 [285,] 11.7151075 23.2731720 [286,] 14.1441398 11.7151075 [287,] -0.3236022 14.1441398 [288,] 1.6157863 -0.3236022 [289,] -11.7809879 1.6157863 [290,] -9.2132460 -11.7809879 [291,] -22.0906653 -9.2132460 [292,] -36.8519556 -22.0906653 [293,] -1.3777621 -36.8519556 [294,] -3.9067944 -1.3777621 [295,] -4.3616331 -3.9067944 [296,] -7.1551815 -4.3616331 [297,] -10.5132460 -7.1551815 [298,] -52.9842137 -10.5132460 [299,] -70.4519556 -52.9842137 [300,] -87.8125672 -70.4519556 [301,] -80.7093414 -87.8125672 [302,] -91.7415995 -80.7093414 [303,] -86.6190188 -91.7415995 [304,] -103.5803091 -86.6190188 [305,] -71.5061156 -103.5803091 [306,] -78.4351478 -71.5061156 [307,] -81.4899866 -78.4351478 [308,] -68.6835349 -81.4899866 [309,] -93.4415995 -68.6835349 [310,] -86.2125672 -93.4415995 [311,] -88.4803091 -86.2125672 [312,] -66.7409207 -88.4803091 [313,] -63.4376949 -66.7409207 [314,] -79.6699530 -63.4376949 [315,] -86.1473723 -79.6699530 [316,] -81.3086626 -86.1473723 [317,] -30.4344691 -81.3086626 [318,] -19.6635013 -30.4344691 [319,] -26.0183401 -19.6635013 [320,] 22.7881116 -26.0183401 [321,] 22.4300470 22.7881116 [322,] 64.4590793 22.4300470 [323,] 104.0913374 64.4590793 [324,] 238.2307258 104.0913374 [325,] 241.2339516 238.2307258 [326,] 268.5016935 241.2339516 [327,] 253.5242742 268.5016935 [328,] 254.3629839 253.5242742 [329,] 276.2371774 254.3629839 [330,] 263.0081452 276.2371774 [331,] 242.8533065 263.0081452 [332,] 242.5597581 242.8533065 [333,] 230.2016935 242.5597581 [334,] 206.8307258 230.2016935 [335,] 200.7629839 206.8307258 [336,] 225.4023723 200.7629839 [337,] 201.4055981 225.4023723 [338,] 172.8733401 201.4055981 [339,] 148.2959207 172.8733401 [340,] 110.2346304 148.2959207 [341,] 172.6088239 110.2346304 [342,] 187.5797917 172.6088239 [343,] 193.2249530 187.5797917 [344,] 180.7314046 193.2249530 [345,] 176.8733401 180.7314046 [346,] 181.0023723 176.8733401 [347,] 171.2346304 181.0023723 [348,] 180.5740188 171.2346304 [349,] 196.7772446 180.5740188 [350,] 163.7449866 196.7772446 [351,] 103.8675672 163.7449866 [352,] 82.7062769 103.8675672 [353,] 140.1804704 82.7062769 [354,] 111.7514382 140.1804704 [355,] 124.4965995 111.7514382 [356,] 109.6030511 124.4965995 [357,] 103.4449866 109.6030511 [358,] 93.8740188 103.4449866 [359,] 44.8062769 93.8740188 [360,] 73.2456653 44.8062769 [361,] 47.5488911 73.2456653 [362,] 43.8166331 47.5488911 [363,] 3.6392137 43.8166331 [364,] 1.0779234 3.6392137 [365,] 15.2521169 1.0779234 [366,] 49.2230847 15.2521169 [367,] 29.6682460 49.2230847 [368,] 33.3746976 29.6682460 [369,] 15.1166331 33.3746976 [370,] 9.9456653 15.1166331 [371,] 17.0779234 9.9456653 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 21.1994960 -14.5037298 2 27.3672379 21.1994960 3 42.3898185 27.3672379 4 23.6285282 42.3898185 5 -9.6972782 23.6285282 6 13.3736895 -9.6972782 7 27.2188508 13.3736895 8 26.6253024 27.2188508 9 10.6672379 26.6253024 10 17.1962702 10.6672379 11 31.9285282 17.1962702 12 37.6679167 31.9285282 13 75.6711425 37.6679167 14 88.8388844 75.6711425 15 117.1614651 88.8388844 16 161.6001747 117.1614651 17 133.8743683 161.6001747 18 198.8453360 133.8743683 19 186.7904973 198.8453360 20 171.7969489 186.7904973 21 202.5388844 171.7969489 22 158.6679167 202.5388844 23 168.2001747 158.6679167 24 190.7395632 168.2001747 25 195.1427890 190.7395632 26 169.6105309 195.1427890 27 143.7331116 169.6105309 28 124.0718212 143.7331116 29 80.1460148 124.0718212 30 79.4169825 80.1460148 31 40.2621438 79.4169825 32 45.0685954 40.2621438 33 17.0105309 45.0685954 34 25.0395632 17.0105309 35 27.8718212 25.0395632 36 -21.3887903 27.8718212 37 -42.3855645 -21.3887903 38 -41.6178226 -42.3855645 39 -41.1952419 -41.6178226 40 -37.4565323 -41.1952419 41 -73.9823387 -37.4565323 42 -57.2113710 -73.9823387 43 -52.6662097 -57.2113710 44 -27.5597581 -52.6662097 45 -25.3178226 -27.5597581 46 -23.7887903 -25.3178226 47 -45.6565323 -23.7887903 48 -72.7171438 -45.6565323 49 -74.4139180 -72.7171438 50 -85.9461761 -74.4139180 51 -63.6235954 -85.9461761 52 -48.4848858 -63.6235954 53 -96.2106922 -48.4848858 54 -68.1397245 -96.2106922 55 -53.6945632 -68.1397245 56 -55.5881116 -53.6945632 57 -64.9461761 -55.5881116 58 -75.6171438 -64.9461761 59 -82.9848858 -75.6171438 60 -97.5454973 -82.9848858 61 -124.2422715 -97.5454973 62 -115.5745296 -124.2422715 63 -83.0519489 -115.5745296 64 -85.3132392 -83.0519489 65 -138.4390457 -85.3132392 66 -117.8680780 -138.4390457 67 -106.5229167 -117.8680780 68 -78.7164651 -106.5229167 69 -67.9745296 -78.7164651 70 -45.5454973 -67.9745296 71 -13.3132392 -45.5454973 72 33.1261492 -13.3132392 73 65.4293750 33.1261492 74 93.0971169 65.4293750 75 112.9196976 93.0971169 76 114.6584073 112.9196976 77 44.2326008 114.6584073 78 66.8035685 44.2326008 79 77.0487298 66.8035685 80 90.4551815 77.0487298 81 55.4971169 90.4551815 82 52.0261492 55.4971169 83 38.9584073 52.0261492 84 31.6977957 38.9584073 85 11.8010215 31.6977957 86 6.8687634 11.8010215 87 32.2913441 6.8687634 88 5.6300538 32.2913441 89 -46.7957527 5.6300538 90 -47.1247849 -46.7957527 91 -28.5796237 -47.1247849 92 -31.2731720 -28.5796237 93 -21.2312366 -31.2731720 94 -18.1022043 -21.2312366 95 -14.0699462 -18.1022043 96 -40.8305578 -14.0699462 97 -48.1273320 -40.8305578 98 -25.5595901 -48.1273320 99 -25.1370094 -25.5595901 100 4.3017003 -25.1370094 101 -30.4241062 4.3017003 102 -27.1531384 -30.4241062 103 -47.7079772 -27.1531384 104 -50.0015255 -47.7079772 105 -52.7595901 -50.0015255 106 -24.0305578 -52.7595901 107 -20.3982997 -24.0305578 108 -39.0589113 -20.3982997 109 -61.0556855 -39.0589113 110 -65.0879435 -61.0556855 111 -45.6653629 -65.0879435 112 -24.3266532 -45.6653629 113 -47.4524597 -24.3266532 114 -53.4814919 -47.4524597 115 -54.0363306 -53.4814919 116 -39.2298790 -54.0363306 117 -27.5879435 -39.2298790 118 16.5410887 -27.5879435 119 34.5733468 16.5410887 120 74.5127352 34.5733468 121 129.8159610 74.5127352 122 155.9837030 129.8159610 123 185.8062836 155.9837030 124 183.1449933 185.8062836 125 149.5191868 183.1449933 126 159.7901546 149.5191868 127 141.8353159 159.7901546 128 104.0417675 141.8353159 129 88.6837030 104.0417675 130 70.1127352 88.6837030 131 95.9449933 70.1127352 132 83.6843817 95.9449933 133 75.7876075 83.6843817 134 58.0553495 75.7876075 135 22.9779301 58.0553495 136 20.4166398 22.9779301 137 -7.0091667 20.4166398 138 -1.7381989 -7.0091667 139 3.6069624 -1.7381989 140 5.5134140 3.6069624 141 24.5553495 5.5134140 142 42.9843817 24.5553495 143 29.0166398 42.9843817 144 15.5560282 29.0166398 145 -17.6407460 15.5560282 146 32.4269960 -17.6407460 147 15.6495766 32.4269960 148 13.4882863 15.6495766 149 19.9624798 13.4882863 150 13.9334476 19.9624798 151 27.7786089 13.9334476 152 5.2850605 27.7786089 153 42.9269960 5.2850605 154 63.8560282 42.9269960 155 111.6882863 63.8560282 156 124.9276747 111.6882863 157 146.9309005 124.9276747 158 146.0986425 146.9309005 159 131.4212231 146.0986425 160 130.3599328 131.4212231 161 121.8341263 130.3599328 162 109.4050941 121.8341263 163 88.4502554 109.4050941 164 64.9567070 88.4502554 165 63.2986425 64.9567070 166 49.0276747 63.2986425 167 56.5599328 49.0276747 168 41.2993212 56.5599328 169 17.4025470 41.2993212 170 23.8702890 17.4025470 171 16.7928696 23.8702890 172 46.2315793 16.7928696 173 0.2057728 46.2315793 174 -16.0232594 0.2057728 175 16.4219019 -16.0232594 176 -5.1716465 16.4219019 177 -11.8297110 -5.1716465 178 15.2993212 -11.8297110 179 16.2315793 15.2993212 180 29.6709677 16.2315793 181 44.0741935 29.6709677 182 23.5419355 44.0741935 183 17.5645161 23.5419355 184 33.7032258 17.5645161 185 21.4774194 33.7032258 186 2.8483871 21.4774194 187 -4.5064516 2.8483871 188 -15.9000000 -4.5064516 189 -8.0580645 -15.9000000 190 16.2709677 -8.0580645 191 6.8032258 16.2709677 192 6.5426142 6.8032258 193 -9.0541599 6.5426142 194 -10.3864180 -9.0541599 195 -10.8638374 -10.3864180 196 -20.6251277 -10.8638374 197 -0.8509341 -20.6251277 198 -55.8799664 -0.8509341 199 -37.1348051 -55.8799664 200 -48.9283535 -37.1348051 201 -39.8864180 -48.9283535 202 -49.9573858 -39.8864180 203 -43.3251277 -49.9573858 204 -63.3857392 -43.3251277 205 -50.1825134 -63.3857392 206 -75.2147715 -50.1825134 207 -56.9921909 -75.2147715 208 -64.2534812 -56.9921909 209 -52.6792876 -64.2534812 210 -92.7083199 -52.6792876 211 -87.9631586 -92.7083199 212 -103.1567070 -87.9631586 213 -101.0147715 -103.1567070 214 -105.1857392 -101.0147715 215 -117.6534812 -105.1857392 216 -145.3140927 -117.6534812 217 -168.7108669 -145.3140927 218 -158.3431250 -168.7108669 219 -145.4205444 -158.3431250 220 -118.5818347 -145.4205444 221 -111.4076411 -118.5818347 222 -142.8366734 -111.4076411 223 -134.5915121 -142.8366734 224 -149.2850605 -134.5915121 225 -137.6431250 -149.2850605 226 -148.3140927 -137.6431250 227 -142.1818347 -148.3140927 228 -166.0424462 -142.1818347 229 -173.4392204 -166.0424462 230 -174.1714785 -173.4392204 231 -164.2488978 -174.1714785 232 -164.3101882 -164.2488978 233 -120.0359946 -164.3101882 234 -135.1650269 -120.0359946 235 -134.7198656 -135.1650269 236 -122.3134140 -134.7198656 237 -101.1714785 -122.3134140 238 -128.1424462 -101.1714785 239 -148.9101882 -128.1424462 240 -186.7707997 -148.9101882 241 -175.3675739 -186.7707997 242 -188.8998320 -175.3675739 243 -193.7772513 -188.8998320 244 -191.9385417 -193.7772513 245 -133.5643481 -191.9385417 246 -150.5933804 -133.5643481 247 -163.9482191 -150.5933804 248 -163.3417675 -163.9482191 249 -157.5998320 -163.3417675 250 -173.0707997 -157.5998320 251 -191.3385417 -173.0707997 252 -218.8991532 -191.3385417 253 -223.9959274 -218.8991532 254 -219.3281855 -223.9959274 255 -200.9056048 -219.3281855 256 -204.5668952 -200.9056048 257 -168.2927016 -204.5668952 258 -166.3217339 -168.2927016 259 -166.3765726 -166.3217339 260 -140.4701210 -166.3765726 261 -136.8281855 -140.4701210 262 -171.8991532 -136.8281855 263 -182.6668952 -171.8991532 264 -178.0275067 -182.6668952 265 -149.1242809 -178.0275067 266 -132.9565390 -149.1242809 267 -112.1339583 -132.9565390 268 -108.3952487 -112.1339583 269 -52.6210551 -108.3952487 270 -45.7500874 -52.6210551 271 -43.6049261 -45.7500874 272 -19.2984745 -43.6049261 273 -7.1565390 -19.2984745 274 5.5724933 -7.1565390 275 6.0047513 5.5724933 276 10.5441398 6.0047513 277 3.4473656 10.5441398 278 -0.9848925 3.4473656 279 -10.1623118 -0.9848925 280 -19.6236022 -10.1623118 281 17.2505914 -19.6236022 282 24.0215591 17.2505914 283 28.2667204 24.0215591 284 23.2731720 28.2667204 285 11.7151075 23.2731720 286 14.1441398 11.7151075 287 -0.3236022 14.1441398 288 1.6157863 -0.3236022 289 -11.7809879 1.6157863 290 -9.2132460 -11.7809879 291 -22.0906653 -9.2132460 292 -36.8519556 -22.0906653 293 -1.3777621 -36.8519556 294 -3.9067944 -1.3777621 295 -4.3616331 -3.9067944 296 -7.1551815 -4.3616331 297 -10.5132460 -7.1551815 298 -52.9842137 -10.5132460 299 -70.4519556 -52.9842137 300 -87.8125672 -70.4519556 301 -80.7093414 -87.8125672 302 -91.7415995 -80.7093414 303 -86.6190188 -91.7415995 304 -103.5803091 -86.6190188 305 -71.5061156 -103.5803091 306 -78.4351478 -71.5061156 307 -81.4899866 -78.4351478 308 -68.6835349 -81.4899866 309 -93.4415995 -68.6835349 310 -86.2125672 -93.4415995 311 -88.4803091 -86.2125672 312 -66.7409207 -88.4803091 313 -63.4376949 -66.7409207 314 -79.6699530 -63.4376949 315 -86.1473723 -79.6699530 316 -81.3086626 -86.1473723 317 -30.4344691 -81.3086626 318 -19.6635013 -30.4344691 319 -26.0183401 -19.6635013 320 22.7881116 -26.0183401 321 22.4300470 22.7881116 322 64.4590793 22.4300470 323 104.0913374 64.4590793 324 238.2307258 104.0913374 325 241.2339516 238.2307258 326 268.5016935 241.2339516 327 253.5242742 268.5016935 328 254.3629839 253.5242742 329 276.2371774 254.3629839 330 263.0081452 276.2371774 331 242.8533065 263.0081452 332 242.5597581 242.8533065 333 230.2016935 242.5597581 334 206.8307258 230.2016935 335 200.7629839 206.8307258 336 225.4023723 200.7629839 337 201.4055981 225.4023723 338 172.8733401 201.4055981 339 148.2959207 172.8733401 340 110.2346304 148.2959207 341 172.6088239 110.2346304 342 187.5797917 172.6088239 343 193.2249530 187.5797917 344 180.7314046 193.2249530 345 176.8733401 180.7314046 346 181.0023723 176.8733401 347 171.2346304 181.0023723 348 180.5740188 171.2346304 349 196.7772446 180.5740188 350 163.7449866 196.7772446 351 103.8675672 163.7449866 352 82.7062769 103.8675672 353 140.1804704 82.7062769 354 111.7514382 140.1804704 355 124.4965995 111.7514382 356 109.6030511 124.4965995 357 103.4449866 109.6030511 358 93.8740188 103.4449866 359 44.8062769 93.8740188 360 73.2456653 44.8062769 361 47.5488911 73.2456653 362 43.8166331 47.5488911 363 3.6392137 43.8166331 364 1.0779234 3.6392137 365 15.2521169 1.0779234 366 49.2230847 15.2521169 367 29.6682460 49.2230847 368 33.3746976 29.6682460 369 15.1166331 33.3746976 370 9.9456653 15.1166331 371 17.0779234 9.9456653 > 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/fisher/rcomp/tmp/7usg81352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8ezjl1352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9quxt1352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/104o3f1352547499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/fisher/rcomp/tmp/115djq1352547499.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/fisher/rcomp/tmp/12o00u1352547499.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/fisher/rcomp/tmp/13eqmp1352547499.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/fisher/rcomp/tmp/14hqwx1352547499.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/fisher/rcomp/tmp/15jhri1352547499.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/fisher/rcomp/tmp/16l0061352547499.tab") + } > > try(system("convert tmp/11rh11352547499.ps tmp/11rh11352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/2lcv41352547499.ps tmp/2lcv41352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/3srbu1352547499.ps tmp/3srbu1352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/4hnxl1352547499.ps tmp/4hnxl1352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/593p41352547499.ps tmp/593p41352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/6d27n1352547499.ps tmp/6d27n1352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/7usg81352547499.ps tmp/7usg81352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/8ezjl1352547499.ps tmp/8ezjl1352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/9quxt1352547499.ps tmp/9quxt1352547499.png",intern=TRUE)) character(0) > try(system("convert tmp/104o3f1352547499.ps tmp/104o3f1352547499.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 14.197 1.213 15.443