R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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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(101.5,1,100.7,1,110.6,1,96.8,1,100.0,1,104.8,1,86.8,1,92.0,1,100.2,1,106.6,1,102.1,1,93.7,1,97.6,1,96.9,1,105.6,1,102.8,1,101.7,1,104.2,1,92.7,1,91.9,1,106.5,1,112.3,1,102.8,1,96.5,1,101.0,0,98.9,0,105.1,0,103.0,0,99.0,0,104.3,0,94.6,0,90.4,0,108.9,0,111.4,0,100.8,0,102.5,0,98.2,0,98.7,0,113.3,0,104.6,0,99.3,0,111.8,0,97.3,0,97.7,0,115.6,0,111.9,0,107.0,0,107.1,0,100.6,0,99.2,0,108.4,0,103.0,0,99.8,0,115.0,0,90.8,0,95.9,0,114.4,0,108.2,0,112.6,0,109.1,0,105.0,0,105.0,0,118.5,0,103.7,0,112.5,0,116.6,0,96.6,0,101.9,0,116.5,0,119.3,0,115.4,0,108.5,0,111.5,0,108.8,0,121.8,0,109.6,0,112.2,0,119.6,0,104.1,0,105.3,0,115.0,0,124.1,0,116.8,0,107.5,0,115.6,0,116.2,0,116.3,0,119.0,0,111.9,0,118.6,0,106.9,0,103.2,0),dim=c(2,92),dimnames=list(c('Y','X'),1:92))
> y <- array(NA,dim=c(2,92),dimnames=list(c('Y','X'),1:92))
> 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 = 'Do not include Seasonal 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
Y X
1 101.5 1
2 100.7 1
3 110.6 1
4 96.8 1
5 100.0 1
6 104.8 1
7 86.8 1
8 92.0 1
9 100.2 1
10 106.6 1
11 102.1 1
12 93.7 1
13 97.6 1
14 96.9 1
15 105.6 1
16 102.8 1
17 101.7 1
18 104.2 1
19 92.7 1
20 91.9 1
21 106.5 1
22 112.3 1
23 102.8 1
24 96.5 1
25 101.0 0
26 98.9 0
27 105.1 0
28 103.0 0
29 99.0 0
30 104.3 0
31 94.6 0
32 90.4 0
33 108.9 0
34 111.4 0
35 100.8 0
36 102.5 0
37 98.2 0
38 98.7 0
39 113.3 0
40 104.6 0
41 99.3 0
42 111.8 0
43 97.3 0
44 97.7 0
45 115.6 0
46 111.9 0
47 107.0 0
48 107.1 0
49 100.6 0
50 99.2 0
51 108.4 0
52 103.0 0
53 99.8 0
54 115.0 0
55 90.8 0
56 95.9 0
57 114.4 0
58 108.2 0
59 112.6 0
60 109.1 0
61 105.0 0
62 105.0 0
63 118.5 0
64 103.7 0
65 112.5 0
66 116.6 0
67 96.6 0
68 101.9 0
69 116.5 0
70 119.3 0
71 115.4 0
72 108.5 0
73 111.5 0
74 108.8 0
75 121.8 0
76 109.6 0
77 112.2 0
78 119.6 0
79 104.1 0
80 105.3 0
81 115.0 0
82 124.1 0
83 116.8 0
84 107.5 0
85 115.6 0
86 116.2 0
87 116.3 0
88 119.0 0
89 111.9 0
90 118.6 0
91 106.9 0
92 103.2 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
107.690 -7.386
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-17.2897 -5.3397 0.4531 5.3744 16.4103
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 107.6897 0.9039 119.142 < 2e-16 ***
X -7.3855 1.7697 -4.173 6.91e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.454 on 90 degrees of freedom
Multiple R-squared: 0.1621, Adjusted R-squared: 0.1528
F-statistic: 17.42 on 1 and 90 DF, p-value: 6.912e-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,] 0.39675594 0.79351188 0.6032441
[2,] 0.25892995 0.51785991 0.7410700
[3,] 0.65624072 0.68751857 0.3437593
[4,] 0.64802509 0.70394981 0.3519749
[5,] 0.53393630 0.93212740 0.4660637
[6,] 0.51265456 0.97469089 0.4873454
[7,] 0.41371584 0.82743167 0.5862842
[8,] 0.38637118 0.77274236 0.6136288
[9,] 0.30370891 0.60741782 0.6962911
[10,] 0.23668796 0.47337592 0.7633120
[11,] 0.21573457 0.43146914 0.7842654
[12,] 0.16500975 0.33001951 0.8349902
[13,] 0.11875543 0.23751086 0.8812446
[14,] 0.09297541 0.18595083 0.9070246
[15,] 0.10002001 0.20004003 0.8999800
[16,] 0.11679315 0.23358630 0.8832069
[17,] 0.11138258 0.22276516 0.8886174
[18,] 0.19299615 0.38599230 0.8070039
[19,] 0.15274853 0.30549706 0.8472515
[20,] 0.12217698 0.24435396 0.8778230
[21,] 0.09386860 0.18773721 0.9061314
[22,] 0.07525182 0.15050365 0.9247482
[23,] 0.05975988 0.11951975 0.9402401
[24,] 0.04347571 0.08695143 0.9565243
[25,] 0.03545981 0.07091963 0.9645402
[26,] 0.02581395 0.05162789 0.9741861
[27,] 0.03291254 0.06582508 0.9670875
[28,] 0.07207111 0.14414222 0.9279289
[29,] 0.07853064 0.15706128 0.9214694
[30,] 0.09592387 0.19184774 0.9040761
[31,] 0.07982586 0.15965173 0.9201741
[32,] 0.06348727 0.12697454 0.9365127
[33,] 0.06130139 0.12260278 0.9386986
[34,] 0.05790145 0.11580290 0.9420986
[35,] 0.08205180 0.16410361 0.9179482
[36,] 0.06556846 0.13113691 0.9344315
[37,] 0.06240613 0.12481226 0.9375939
[38,] 0.06871220 0.13742440 0.9312878
[39,] 0.07964354 0.15928709 0.9203565
[40,] 0.09084882 0.18169765 0.9091512
[41,] 0.13590350 0.27180700 0.8640965
[42,] 0.13656659 0.27313319 0.8634334
[43,] 0.11295065 0.22590131 0.8870493
[44,] 0.09220489 0.18440978 0.9077951
[45,] 0.08939747 0.17879495 0.9106025
[46,] 0.09801079 0.19602158 0.9019892
[47,] 0.08190286 0.16380572 0.9180971
[48,] 0.07223116 0.14446232 0.9277688
[49,] 0.08016108 0.16032216 0.9198389
[50,] 0.09573866 0.19147732 0.9042613
[51,] 0.31422972 0.62845944 0.6857703
[52,] 0.48363878 0.96727756 0.5163612
[53,] 0.49726345 0.99452689 0.5027366
[54,] 0.45892159 0.91784317 0.5410784
[55,] 0.43848197 0.87696395 0.5615180
[56,] 0.39724485 0.79448971 0.6027551
[57,] 0.38066390 0.76132779 0.6193361
[58,] 0.36819978 0.73639956 0.6318002
[59,] 0.43512935 0.87025869 0.5648707
[60,] 0.44480146 0.88960292 0.5551985
[61,] 0.40741229 0.81482457 0.5925877
[62,] 0.41679831 0.83359661 0.5832017
[63,] 0.66146979 0.67706043 0.3385302
[64,] 0.75049936 0.49900129 0.2495006
[65,] 0.74263085 0.51473830 0.2573692
[66,] 0.77824200 0.44351601 0.2217580
[67,] 0.75047454 0.49905092 0.2495255
[68,] 0.71446595 0.57106810 0.2855341
[69,] 0.65822450 0.68355100 0.3417755
[70,] 0.61511138 0.76977725 0.3848886
[71,] 0.70249801 0.59500398 0.2975020
[72,] 0.64689036 0.70621927 0.3531096
[73,] 0.57412375 0.85175249 0.4258762
[74,] 0.59123302 0.81753397 0.4087670
[75,] 0.63796079 0.72407842 0.3620392
[76,] 0.67719105 0.64561789 0.3228089
[77,] 0.59482769 0.81034462 0.4051723
[78,] 0.75279099 0.49441802 0.2472090
[79,] 0.69502517 0.60994967 0.3049748
[80,] 0.65263581 0.69472839 0.3473642
[81,] 0.54315213 0.91369574 0.4568479
[82,] 0.43264649 0.86529298 0.5673535
[83,] 0.32240201 0.64480402 0.6775980
> postscript(file="/var/www/html/freestat/rcomp/tmp/1md8x1229008201.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2n1u01229008201.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33twi1229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4pobd1229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5k5v71229008202.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 = 92
Frequency = 1
1 2 3 4 5 6
1.1958333 0.3958333 10.2958333 -3.5041667 -0.3041667 4.4958333
7 8 9 10 11 12
-13.5041667 -8.3041667 -0.1041667 6.2958333 1.7958333 -6.6041667
13 14 15 16 17 18
-2.7041667 -3.4041667 5.2958333 2.4958333 1.3958333 3.8958333
19 20 21 22 23 24
-7.6041667 -8.4041667 6.1958333 11.9958333 2.4958333 -3.8041667
25 26 27 28 29 30
-6.6897059 -8.7897059 -2.5897059 -4.6897059 -8.6897059 -3.3897059
31 32 33 34 35 36
-13.0897059 -17.2897059 1.2102941 3.7102941 -6.8897059 -5.1897059
37 38 39 40 41 42
-9.4897059 -8.9897059 5.6102941 -3.0897059 -8.3897059 4.1102941
43 44 45 46 47 48
-10.3897059 -9.9897059 7.9102941 4.2102941 -0.6897059 -0.5897059
49 50 51 52 53 54
-7.0897059 -8.4897059 0.7102941 -4.6897059 -7.8897059 7.3102941
55 56 57 58 59 60
-16.8897059 -11.7897059 6.7102941 0.5102941 4.9102941 1.4102941
61 62 63 64 65 66
-2.6897059 -2.6897059 10.8102941 -3.9897059 4.8102941 8.9102941
67 68 69 70 71 72
-11.0897059 -5.7897059 8.8102941 11.6102941 7.7102941 0.8102941
73 74 75 76 77 78
3.8102941 1.1102941 14.1102941 1.9102941 4.5102941 11.9102941
79 80 81 82 83 84
-3.5897059 -2.3897059 7.3102941 16.4102941 9.1102941 -0.1897059
85 86 87 88 89 90
7.9102941 8.5102941 8.6102941 11.3102941 4.2102941 10.9102941
91 92
-0.7897059 -4.4897059
> postscript(file="/var/www/html/freestat/rcomp/tmp/64mfz1229008202.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 = 92
Frequency = 1
lag(myerror, k = 1) myerror
0 1.1958333 NA
1 0.3958333 1.1958333
2 10.2958333 0.3958333
3 -3.5041667 10.2958333
4 -0.3041667 -3.5041667
5 4.4958333 -0.3041667
6 -13.5041667 4.4958333
7 -8.3041667 -13.5041667
8 -0.1041667 -8.3041667
9 6.2958333 -0.1041667
10 1.7958333 6.2958333
11 -6.6041667 1.7958333
12 -2.7041667 -6.6041667
13 -3.4041667 -2.7041667
14 5.2958333 -3.4041667
15 2.4958333 5.2958333
16 1.3958333 2.4958333
17 3.8958333 1.3958333
18 -7.6041667 3.8958333
19 -8.4041667 -7.6041667
20 6.1958333 -8.4041667
21 11.9958333 6.1958333
22 2.4958333 11.9958333
23 -3.8041667 2.4958333
24 -6.6897059 -3.8041667
25 -8.7897059 -6.6897059
26 -2.5897059 -8.7897059
27 -4.6897059 -2.5897059
28 -8.6897059 -4.6897059
29 -3.3897059 -8.6897059
30 -13.0897059 -3.3897059
31 -17.2897059 -13.0897059
32 1.2102941 -17.2897059
33 3.7102941 1.2102941
34 -6.8897059 3.7102941
35 -5.1897059 -6.8897059
36 -9.4897059 -5.1897059
37 -8.9897059 -9.4897059
38 5.6102941 -8.9897059
39 -3.0897059 5.6102941
40 -8.3897059 -3.0897059
41 4.1102941 -8.3897059
42 -10.3897059 4.1102941
43 -9.9897059 -10.3897059
44 7.9102941 -9.9897059
45 4.2102941 7.9102941
46 -0.6897059 4.2102941
47 -0.5897059 -0.6897059
48 -7.0897059 -0.5897059
49 -8.4897059 -7.0897059
50 0.7102941 -8.4897059
51 -4.6897059 0.7102941
52 -7.8897059 -4.6897059
53 7.3102941 -7.8897059
54 -16.8897059 7.3102941
55 -11.7897059 -16.8897059
56 6.7102941 -11.7897059
57 0.5102941 6.7102941
58 4.9102941 0.5102941
59 1.4102941 4.9102941
60 -2.6897059 1.4102941
61 -2.6897059 -2.6897059
62 10.8102941 -2.6897059
63 -3.9897059 10.8102941
64 4.8102941 -3.9897059
65 8.9102941 4.8102941
66 -11.0897059 8.9102941
67 -5.7897059 -11.0897059
68 8.8102941 -5.7897059
69 11.6102941 8.8102941
70 7.7102941 11.6102941
71 0.8102941 7.7102941
72 3.8102941 0.8102941
73 1.1102941 3.8102941
74 14.1102941 1.1102941
75 1.9102941 14.1102941
76 4.5102941 1.9102941
77 11.9102941 4.5102941
78 -3.5897059 11.9102941
79 -2.3897059 -3.5897059
80 7.3102941 -2.3897059
81 16.4102941 7.3102941
82 9.1102941 16.4102941
83 -0.1897059 9.1102941
84 7.9102941 -0.1897059
85 8.5102941 7.9102941
86 8.6102941 8.5102941
87 11.3102941 8.6102941
88 4.2102941 11.3102941
89 10.9102941 4.2102941
90 -0.7897059 10.9102941
91 -4.4897059 -0.7897059
92 NA -4.4897059
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.3958333 1.1958333
[2,] 10.2958333 0.3958333
[3,] -3.5041667 10.2958333
[4,] -0.3041667 -3.5041667
[5,] 4.4958333 -0.3041667
[6,] -13.5041667 4.4958333
[7,] -8.3041667 -13.5041667
[8,] -0.1041667 -8.3041667
[9,] 6.2958333 -0.1041667
[10,] 1.7958333 6.2958333
[11,] -6.6041667 1.7958333
[12,] -2.7041667 -6.6041667
[13,] -3.4041667 -2.7041667
[14,] 5.2958333 -3.4041667
[15,] 2.4958333 5.2958333
[16,] 1.3958333 2.4958333
[17,] 3.8958333 1.3958333
[18,] -7.6041667 3.8958333
[19,] -8.4041667 -7.6041667
[20,] 6.1958333 -8.4041667
[21,] 11.9958333 6.1958333
[22,] 2.4958333 11.9958333
[23,] -3.8041667 2.4958333
[24,] -6.6897059 -3.8041667
[25,] -8.7897059 -6.6897059
[26,] -2.5897059 -8.7897059
[27,] -4.6897059 -2.5897059
[28,] -8.6897059 -4.6897059
[29,] -3.3897059 -8.6897059
[30,] -13.0897059 -3.3897059
[31,] -17.2897059 -13.0897059
[32,] 1.2102941 -17.2897059
[33,] 3.7102941 1.2102941
[34,] -6.8897059 3.7102941
[35,] -5.1897059 -6.8897059
[36,] -9.4897059 -5.1897059
[37,] -8.9897059 -9.4897059
[38,] 5.6102941 -8.9897059
[39,] -3.0897059 5.6102941
[40,] -8.3897059 -3.0897059
[41,] 4.1102941 -8.3897059
[42,] -10.3897059 4.1102941
[43,] -9.9897059 -10.3897059
[44,] 7.9102941 -9.9897059
[45,] 4.2102941 7.9102941
[46,] -0.6897059 4.2102941
[47,] -0.5897059 -0.6897059
[48,] -7.0897059 -0.5897059
[49,] -8.4897059 -7.0897059
[50,] 0.7102941 -8.4897059
[51,] -4.6897059 0.7102941
[52,] -7.8897059 -4.6897059
[53,] 7.3102941 -7.8897059
[54,] -16.8897059 7.3102941
[55,] -11.7897059 -16.8897059
[56,] 6.7102941 -11.7897059
[57,] 0.5102941 6.7102941
[58,] 4.9102941 0.5102941
[59,] 1.4102941 4.9102941
[60,] -2.6897059 1.4102941
[61,] -2.6897059 -2.6897059
[62,] 10.8102941 -2.6897059
[63,] -3.9897059 10.8102941
[64,] 4.8102941 -3.9897059
[65,] 8.9102941 4.8102941
[66,] -11.0897059 8.9102941
[67,] -5.7897059 -11.0897059
[68,] 8.8102941 -5.7897059
[69,] 11.6102941 8.8102941
[70,] 7.7102941 11.6102941
[71,] 0.8102941 7.7102941
[72,] 3.8102941 0.8102941
[73,] 1.1102941 3.8102941
[74,] 14.1102941 1.1102941
[75,] 1.9102941 14.1102941
[76,] 4.5102941 1.9102941
[77,] 11.9102941 4.5102941
[78,] -3.5897059 11.9102941
[79,] -2.3897059 -3.5897059
[80,] 7.3102941 -2.3897059
[81,] 16.4102941 7.3102941
[82,] 9.1102941 16.4102941
[83,] -0.1897059 9.1102941
[84,] 7.9102941 -0.1897059
[85,] 8.5102941 7.9102941
[86,] 8.6102941 8.5102941
[87,] 11.3102941 8.6102941
[88,] 4.2102941 11.3102941
[89,] 10.9102941 4.2102941
[90,] -0.7897059 10.9102941
[91,] -4.4897059 -0.7897059
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.3958333 1.1958333
2 10.2958333 0.3958333
3 -3.5041667 10.2958333
4 -0.3041667 -3.5041667
5 4.4958333 -0.3041667
6 -13.5041667 4.4958333
7 -8.3041667 -13.5041667
8 -0.1041667 -8.3041667
9 6.2958333 -0.1041667
10 1.7958333 6.2958333
11 -6.6041667 1.7958333
12 -2.7041667 -6.6041667
13 -3.4041667 -2.7041667
14 5.2958333 -3.4041667
15 2.4958333 5.2958333
16 1.3958333 2.4958333
17 3.8958333 1.3958333
18 -7.6041667 3.8958333
19 -8.4041667 -7.6041667
20 6.1958333 -8.4041667
21 11.9958333 6.1958333
22 2.4958333 11.9958333
23 -3.8041667 2.4958333
24 -6.6897059 -3.8041667
25 -8.7897059 -6.6897059
26 -2.5897059 -8.7897059
27 -4.6897059 -2.5897059
28 -8.6897059 -4.6897059
29 -3.3897059 -8.6897059
30 -13.0897059 -3.3897059
31 -17.2897059 -13.0897059
32 1.2102941 -17.2897059
33 3.7102941 1.2102941
34 -6.8897059 3.7102941
35 -5.1897059 -6.8897059
36 -9.4897059 -5.1897059
37 -8.9897059 -9.4897059
38 5.6102941 -8.9897059
39 -3.0897059 5.6102941
40 -8.3897059 -3.0897059
41 4.1102941 -8.3897059
42 -10.3897059 4.1102941
43 -9.9897059 -10.3897059
44 7.9102941 -9.9897059
45 4.2102941 7.9102941
46 -0.6897059 4.2102941
47 -0.5897059 -0.6897059
48 -7.0897059 -0.5897059
49 -8.4897059 -7.0897059
50 0.7102941 -8.4897059
51 -4.6897059 0.7102941
52 -7.8897059 -4.6897059
53 7.3102941 -7.8897059
54 -16.8897059 7.3102941
55 -11.7897059 -16.8897059
56 6.7102941 -11.7897059
57 0.5102941 6.7102941
58 4.9102941 0.5102941
59 1.4102941 4.9102941
60 -2.6897059 1.4102941
61 -2.6897059 -2.6897059
62 10.8102941 -2.6897059
63 -3.9897059 10.8102941
64 4.8102941 -3.9897059
65 8.9102941 4.8102941
66 -11.0897059 8.9102941
67 -5.7897059 -11.0897059
68 8.8102941 -5.7897059
69 11.6102941 8.8102941
70 7.7102941 11.6102941
71 0.8102941 7.7102941
72 3.8102941 0.8102941
73 1.1102941 3.8102941
74 14.1102941 1.1102941
75 1.9102941 14.1102941
76 4.5102941 1.9102941
77 11.9102941 4.5102941
78 -3.5897059 11.9102941
79 -2.3897059 -3.5897059
80 7.3102941 -2.3897059
81 16.4102941 7.3102941
82 9.1102941 16.4102941
83 -0.1897059 9.1102941
84 7.9102941 -0.1897059
85 8.5102941 7.9102941
86 8.6102941 8.5102941
87 11.3102941 8.6102941
88 4.2102941 11.3102941
89 10.9102941 4.2102941
90 -0.7897059 10.9102941
91 -4.4897059 -0.7897059
> 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/7wjg21229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/85kdp1229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9wfje1229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ylqw1229008202.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mw311229008202.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/12pl3y1229008202.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/137wrc1229008202.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/14d1t11229008202.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/1588yo1229008202.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/164v6q1229008202.tab")
+ }
>
> system("convert tmp/1md8x1229008201.ps tmp/1md8x1229008201.png")
> system("convert tmp/2n1u01229008201.ps tmp/2n1u01229008201.png")
> system("convert tmp/33twi1229008202.ps tmp/33twi1229008202.png")
> system("convert tmp/4pobd1229008202.ps tmp/4pobd1229008202.png")
> system("convert tmp/5k5v71229008202.ps tmp/5k5v71229008202.png")
> system("convert tmp/64mfz1229008202.ps tmp/64mfz1229008202.png")
> system("convert tmp/7wjg21229008202.ps tmp/7wjg21229008202.png")
> system("convert tmp/85kdp1229008202.ps tmp/85kdp1229008202.png")
> system("convert tmp/9wfje1229008202.ps tmp/9wfje1229008202.png")
> system("convert tmp/10ylqw1229008202.ps tmp/10ylqw1229008202.png")
>
>
> proc.time()
user system elapsed
4.111 2.552 4.740