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Type 'q()' to quit R. > x <- array(list(9492.49,0,9682.35,0,9762.12,0,10124.63,0,10540.05,0,10601.61,0,10323.73,0,10418.4,0,10092.96,0,10364.91,0,10152.09,0,10032.8,0,10204.59,0,10001.6,0,10411.75,0,10673.38,0,10539.51,0,10723.78,0,10682.06,0,10283.19,0,10377.18,0,10486.64,0,10545.38,0,10554.27,0,10532.54,0,10324.31,0,10695.25,0,10827.81,0,10872.48,0,10971.19,0,11145.65,0,11234.68,0,11333.88,0,10997.97,0,11036.89,0,11257.35,0,11533.59,0,11963.12,0,12185.15,0,12377.62,0,12512.89,0,12631.48,0,12268.53,0,12754.8,0,13407.75,1,13480.21,1,13673.28,1,13239.71,1,13557.69,1,13901.28,1,13200.58,1,13406.97,1,12538.12,1,12419.57,1,12193.88,1,12656.63,1,12812.48,1,12056.67,1,11322.38,1,11530.75,1,11114.08,1),dim=c(2,61),dimnames=list(c('X','Y'),1:61)) > y <- array(NA,dim=c(2,61),dimnames=list(c('X','Y'),1:61)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No 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 X Y M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1 9492.49 0 1 0 0 0 0 0 0 0 0 0 0 2 9682.35 0 0 1 0 0 0 0 0 0 0 0 0 3 9762.12 0 0 0 1 0 0 0 0 0 0 0 0 4 10124.63 0 0 0 0 1 0 0 0 0 0 0 0 5 10540.05 0 0 0 0 0 1 0 0 0 0 0 0 6 10601.61 0 0 0 0 0 0 1 0 0 0 0 0 7 10323.73 0 0 0 0 0 0 0 1 0 0 0 0 8 10418.40 0 0 0 0 0 0 0 0 1 0 0 0 9 10092.96 0 0 0 0 0 0 0 0 0 1 0 0 10 10364.91 0 0 0 0 0 0 0 0 0 0 1 0 11 10152.09 0 0 0 0 0 0 0 0 0 0 0 1 12 10032.80 0 0 0 0 0 0 0 0 0 0 0 0 13 10204.59 0 1 0 0 0 0 0 0 0 0 0 0 14 10001.60 0 0 1 0 0 0 0 0 0 0 0 0 15 10411.75 0 0 0 1 0 0 0 0 0 0 0 0 16 10673.38 0 0 0 0 1 0 0 0 0 0 0 0 17 10539.51 0 0 0 0 0 1 0 0 0 0 0 0 18 10723.78 0 0 0 0 0 0 1 0 0 0 0 0 19 10682.06 0 0 0 0 0 0 0 1 0 0 0 0 20 10283.19 0 0 0 0 0 0 0 0 1 0 0 0 21 10377.18 0 0 0 0 0 0 0 0 0 1 0 0 22 10486.64 0 0 0 0 0 0 0 0 0 0 1 0 23 10545.38 0 0 0 0 0 0 0 0 0 0 0 1 24 10554.27 0 0 0 0 0 0 0 0 0 0 0 0 25 10532.54 0 1 0 0 0 0 0 0 0 0 0 0 26 10324.31 0 0 1 0 0 0 0 0 0 0 0 0 27 10695.25 0 0 0 1 0 0 0 0 0 0 0 0 28 10827.81 0 0 0 0 1 0 0 0 0 0 0 0 29 10872.48 0 0 0 0 0 1 0 0 0 0 0 0 30 10971.19 0 0 0 0 0 0 1 0 0 0 0 0 31 11145.65 0 0 0 0 0 0 0 1 0 0 0 0 32 11234.68 0 0 0 0 0 0 0 0 1 0 0 0 33 11333.88 0 0 0 0 0 0 0 0 0 1 0 0 34 10997.97 0 0 0 0 0 0 0 0 0 0 1 0 35 11036.89 0 0 0 0 0 0 0 0 0 0 0 1 36 11257.35 0 0 0 0 0 0 0 0 0 0 0 0 37 11533.59 0 1 0 0 0 0 0 0 0 0 0 0 38 11963.12 0 0 1 0 0 0 0 0 0 0 0 0 39 12185.15 0 0 0 1 0 0 0 0 0 0 0 0 40 12377.62 0 0 0 0 1 0 0 0 0 0 0 0 41 12512.89 0 0 0 0 0 1 0 0 0 0 0 0 42 12631.48 0 0 0 0 0 0 1 0 0 0 0 0 43 12268.53 0 0 0 0 0 0 0 1 0 0 0 0 44 12754.80 0 0 0 0 0 0 0 0 1 0 0 0 45 13407.75 1 0 0 0 0 0 0 0 0 1 0 0 46 13480.21 1 0 0 0 0 0 0 0 0 0 1 0 47 13673.28 1 0 0 0 0 0 0 0 0 0 0 1 48 13239.71 1 0 0 0 0 0 0 0 0 0 0 0 49 13557.69 1 1 0 0 0 0 0 0 0 0 0 0 50 13901.28 1 0 1 0 0 0 0 0 0 0 0 0 51 13200.58 1 0 0 1 0 0 0 0 0 0 0 0 52 13406.97 1 0 0 0 1 0 0 0 0 0 0 0 53 12538.12 1 0 0 0 0 1 0 0 0 0 0 0 54 12419.57 1 0 0 0 0 0 1 0 0 0 0 0 55 12193.88 1 0 0 0 0 0 0 1 0 0 0 0 56 12656.63 1 0 0 0 0 0 0 0 1 0 0 0 57 12812.48 1 0 0 0 0 0 0 0 0 1 0 0 58 12056.67 1 0 0 0 0 0 0 0 0 0 1 0 59 11322.38 1 0 0 0 0 0 0 0 0 0 0 1 60 11530.75 1 0 0 0 0 0 0 0 0 0 0 0 61 11114.08 1 1 0 0 0 0 0 0 0 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Y M1 M2 M3 M4 10528.84 1985.35 -118.12 248.63 325.06 556.18 M5 M6 M7 M8 M9 M10 474.70 543.62 396.86 543.63 281.87 154.30 M11 23.03 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1282.0 -496.0 -206.1 523.2 1682.3 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 10528.84 406.64 25.892 < 2e-16 *** Y 1985.35 256.84 7.730 5.65e-10 *** M1 -118.12 533.00 -0.222 0.826 M2 248.63 558.78 0.445 0.658 M3 325.06 558.78 0.582 0.563 M4 556.18 558.78 0.995 0.325 M5 474.70 558.78 0.850 0.400 M6 543.62 558.78 0.973 0.335 M7 396.86 558.78 0.710 0.481 M8 543.63 558.78 0.973 0.335 M9 281.87 556.42 0.507 0.615 M10 154.30 556.42 0.277 0.783 M11 23.03 556.42 0.041 0.967 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 879.8 on 48 degrees of freedom Multiple R-squared: 0.5614, Adjusted R-squared: 0.4518 F-statistic: 5.121 on 12 and 48 DF, p-value: 1.998e-05 > 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,] 0.1641074881 0.3282149762 0.8358925 [2,] 0.0703120746 0.1406241493 0.9296879 [3,] 0.0279623990 0.0559247981 0.9720376 [4,] 0.0127019529 0.0254039058 0.9872980 [5,] 0.0053872427 0.0107744853 0.9946128 [6,] 0.0024395998 0.0048791996 0.9975604 [7,] 0.0008541238 0.0017082475 0.9991459 [8,] 0.0003995446 0.0007990893 0.9996005 [9,] 0.0002482039 0.0004964079 0.9997518 [10,] 0.0003228521 0.0006457043 0.9996771 [11,] 0.0004039870 0.0008079741 0.9995960 [12,] 0.0005162475 0.0010324950 0.9994838 [13,] 0.0004965994 0.0009931987 0.9995034 [14,] 0.0003358093 0.0006716186 0.9996642 [15,] 0.0002160323 0.0004320646 0.9997840 [16,] 0.0002141512 0.0004283023 0.9997858 [17,] 0.0004713618 0.0009427235 0.9995286 [18,] 0.0013694434 0.0027388867 0.9986306 [19,] 0.0012576076 0.0025152152 0.9987424 [20,] 0.0011787262 0.0023574525 0.9988213 [21,] 0.0014630628 0.0029261256 0.9985369 [22,] 0.0042674385 0.0085348769 0.9957326 [23,] 0.0303162066 0.0606324133 0.9696838 [24,] 0.0601630293 0.1203260585 0.9398370 [25,] 0.0902551658 0.1805103315 0.9097448 [26,] 0.0949454436 0.1898908872 0.9050546 [27,] 0.0884006895 0.1768013790 0.9115993 [28,] 0.0649961414 0.1299922827 0.9350039 [29,] 0.0534266913 0.1068533827 0.9465733 [30,] 0.0254953754 0.0509907507 0.9745046 > postscript(file="/var/www/html/freestat/rcomp/tmp/1xaws1227780247.ps",horizontal=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2970j1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/freestat/rcomp/tmp/3yzfp1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4xh0c1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5i7dk1227780247.ps",horizontal=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 = 61 Frequency = 1 1 2 3 4 5 6 -918.222955 -1095.111773 -1091.779773 -960.381773 -463.489773 -470.845773 7 8 9 10 11 12 -601.969773 -654.069773 -717.749545 -318.229545 -399.773545 -496.035545 13 14 15 16 17 18 -206.122955 -775.861773 -442.149773 -411.631773 -464.029773 -348.675773 19 20 21 22 23 24 -243.639773 -789.279773 -433.529545 -196.499545 -6.483545 25.434455 25 26 27 28 29 30 121.827045 -453.151773 -158.649773 -257.201773 -131.059773 -101.265773 31 32 33 34 35 36 219.950227 162.210227 523.170455 314.830455 485.026455 728.514455 37 38 39 40 41 42 1122.877045 1185.658227 1331.250227 1292.608227 1509.350227 1559.024227 43 44 45 46 47 48 1342.830227 1682.330227 611.689318 811.719318 1136.065318 725.523318 49 50 51 52 53 54 1161.625909 1138.467091 361.329091 336.607091 -450.770909 -638.236909 55 56 57 58 59 60 -717.170909 -401.190909 16.419318 -611.820682 -1214.834682 -983.436682 61 -1281.984091 > postscript(file="/var/www/html/freestat/rcomp/tmp/6cbuc1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 61 Frequency = 1 lag(myerror, k = 1) myerror 0 -918.222955 NA 1 -1095.111773 -918.222955 2 -1091.779773 -1095.111773 3 -960.381773 -1091.779773 4 -463.489773 -960.381773 5 -470.845773 -463.489773 6 -601.969773 -470.845773 7 -654.069773 -601.969773 8 -717.749545 -654.069773 9 -318.229545 -717.749545 10 -399.773545 -318.229545 11 -496.035545 -399.773545 12 -206.122955 -496.035545 13 -775.861773 -206.122955 14 -442.149773 -775.861773 15 -411.631773 -442.149773 16 -464.029773 -411.631773 17 -348.675773 -464.029773 18 -243.639773 -348.675773 19 -789.279773 -243.639773 20 -433.529545 -789.279773 21 -196.499545 -433.529545 22 -6.483545 -196.499545 23 25.434455 -6.483545 24 121.827045 25.434455 25 -453.151773 121.827045 26 -158.649773 -453.151773 27 -257.201773 -158.649773 28 -131.059773 -257.201773 29 -101.265773 -131.059773 30 219.950227 -101.265773 31 162.210227 219.950227 32 523.170455 162.210227 33 314.830455 523.170455 34 485.026455 314.830455 35 728.514455 485.026455 36 1122.877045 728.514455 37 1185.658227 1122.877045 38 1331.250227 1185.658227 39 1292.608227 1331.250227 40 1509.350227 1292.608227 41 1559.024227 1509.350227 42 1342.830227 1559.024227 43 1682.330227 1342.830227 44 611.689318 1682.330227 45 811.719318 611.689318 46 1136.065318 811.719318 47 725.523318 1136.065318 48 1161.625909 725.523318 49 1138.467091 1161.625909 50 361.329091 1138.467091 51 336.607091 361.329091 52 -450.770909 336.607091 53 -638.236909 -450.770909 54 -717.170909 -638.236909 55 -401.190909 -717.170909 56 16.419318 -401.190909 57 -611.820682 16.419318 58 -1214.834682 -611.820682 59 -983.436682 -1214.834682 60 -1281.984091 -983.436682 61 NA -1281.984091 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1095.111773 -918.222955 [2,] -1091.779773 -1095.111773 [3,] -960.381773 -1091.779773 [4,] -463.489773 -960.381773 [5,] -470.845773 -463.489773 [6,] -601.969773 -470.845773 [7,] -654.069773 -601.969773 [8,] -717.749545 -654.069773 [9,] -318.229545 -717.749545 [10,] -399.773545 -318.229545 [11,] -496.035545 -399.773545 [12,] -206.122955 -496.035545 [13,] -775.861773 -206.122955 [14,] -442.149773 -775.861773 [15,] -411.631773 -442.149773 [16,] -464.029773 -411.631773 [17,] -348.675773 -464.029773 [18,] -243.639773 -348.675773 [19,] -789.279773 -243.639773 [20,] -433.529545 -789.279773 [21,] -196.499545 -433.529545 [22,] -6.483545 -196.499545 [23,] 25.434455 -6.483545 [24,] 121.827045 25.434455 [25,] -453.151773 121.827045 [26,] -158.649773 -453.151773 [27,] -257.201773 -158.649773 [28,] -131.059773 -257.201773 [29,] -101.265773 -131.059773 [30,] 219.950227 -101.265773 [31,] 162.210227 219.950227 [32,] 523.170455 162.210227 [33,] 314.830455 523.170455 [34,] 485.026455 314.830455 [35,] 728.514455 485.026455 [36,] 1122.877045 728.514455 [37,] 1185.658227 1122.877045 [38,] 1331.250227 1185.658227 [39,] 1292.608227 1331.250227 [40,] 1509.350227 1292.608227 [41,] 1559.024227 1509.350227 [42,] 1342.830227 1559.024227 [43,] 1682.330227 1342.830227 [44,] 611.689318 1682.330227 [45,] 811.719318 611.689318 [46,] 1136.065318 811.719318 [47,] 725.523318 1136.065318 [48,] 1161.625909 725.523318 [49,] 1138.467091 1161.625909 [50,] 361.329091 1138.467091 [51,] 336.607091 361.329091 [52,] -450.770909 336.607091 [53,] -638.236909 -450.770909 [54,] -717.170909 -638.236909 [55,] -401.190909 -717.170909 [56,] 16.419318 -401.190909 [57,] -611.820682 16.419318 [58,] -1214.834682 -611.820682 [59,] -983.436682 -1214.834682 [60,] -1281.984091 -983.436682 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1095.111773 -918.222955 2 -1091.779773 -1095.111773 3 -960.381773 -1091.779773 4 -463.489773 -960.381773 5 -470.845773 -463.489773 6 -601.969773 -470.845773 7 -654.069773 -601.969773 8 -717.749545 -654.069773 9 -318.229545 -717.749545 10 -399.773545 -318.229545 11 -496.035545 -399.773545 12 -206.122955 -496.035545 13 -775.861773 -206.122955 14 -442.149773 -775.861773 15 -411.631773 -442.149773 16 -464.029773 -411.631773 17 -348.675773 -464.029773 18 -243.639773 -348.675773 19 -789.279773 -243.639773 20 -433.529545 -789.279773 21 -196.499545 -433.529545 22 -6.483545 -196.499545 23 25.434455 -6.483545 24 121.827045 25.434455 25 -453.151773 121.827045 26 -158.649773 -453.151773 27 -257.201773 -158.649773 28 -131.059773 -257.201773 29 -101.265773 -131.059773 30 219.950227 -101.265773 31 162.210227 219.950227 32 523.170455 162.210227 33 314.830455 523.170455 34 485.026455 314.830455 35 728.514455 485.026455 36 1122.877045 728.514455 37 1185.658227 1122.877045 38 1331.250227 1185.658227 39 1292.608227 1331.250227 40 1509.350227 1292.608227 41 1559.024227 1509.350227 42 1342.830227 1559.024227 43 1682.330227 1342.830227 44 611.689318 1682.330227 45 811.719318 611.689318 46 1136.065318 811.719318 47 725.523318 1136.065318 48 1161.625909 725.523318 49 1138.467091 1161.625909 50 361.329091 1138.467091 51 336.607091 361.329091 52 -450.770909 336.607091 53 -638.236909 -450.770909 54 -717.170909 -638.236909 55 -401.190909 -717.170909 56 16.419318 -401.190909 57 -611.820682 16.419318 58 -1214.834682 -611.820682 59 -983.436682 -1214.834682 60 -1281.984091 -983.436682 > 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/freestat/rcomp/tmp/7bkn01227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8sp8t1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9svmi1227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10agk01227780247.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/118his1227780247.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/freestat/rcomp/tmp/12hxll1227780247.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/freestat/rcomp/tmp/13g4ss1227780247.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/freestat/rcomp/tmp/14qcup1227780247.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/freestat/rcomp/tmp/15saba1227780247.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/freestat/rcomp/tmp/16s6m21227780247.tab") + } > > system("convert tmp/1xaws1227780247.ps tmp/1xaws1227780247.png") > system("convert tmp/2970j1227780247.ps tmp/2970j1227780247.png") > system("convert tmp/3yzfp1227780247.ps tmp/3yzfp1227780247.png") > system("convert tmp/4xh0c1227780247.ps tmp/4xh0c1227780247.png") > system("convert tmp/5i7dk1227780247.ps tmp/5i7dk1227780247.png") > system("convert tmp/6cbuc1227780247.ps tmp/6cbuc1227780247.png") > system("convert tmp/7bkn01227780247.ps tmp/7bkn01227780247.png") > system("convert tmp/8sp8t1227780247.ps tmp/8sp8t1227780247.png") > system("convert tmp/9svmi1227780247.ps tmp/9svmi1227780247.png") > system("convert tmp/10agk01227780247.ps tmp/10agk01227780247.png") > > > proc.time() user system elapsed 3.644 2.508 4.140