R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(91.2,0,99.2,0,108.2,0,101.5,0,106.9,0,104.4,0,77.9,0,60,0,99.5,0,95,0,105.6,0,102.5,0,93.3,0,97.3,0,127,0,111.7,0,96.4,0,133,0,72.2,0,95.8,0,124.1,0,127.6,0,110.7,0,104.6,0,112.7,1,115.3,1,139.4,1,119,1,97.4,1,154,1,81.5,1,88.8,1,127.7,1,105.1,1,114.9,1,106.4,1,104.5,1,121.6,1,141.4,1,99,1,126.7,1,134.1,1,81.3,1,88.6,1,132.7,1,132.9,1,134.4,1,103.7,1,119.7,1,115,1,132.9,1,108.5,1,113.9,1,142,1,97.7,1,92.2,1,128.8,1,134.9,1,128.2,1,114.8,1,117.9,1,119.1,1,120.7,1,129.1,1,117.6,1,129.2,1,100,1,87.3,1),dim=c(2,68),dimnames=list(c('X','Y'),1:68))
> y <- array(NA,dim=c(2,68),dimnames=list(c('X','Y'),1:68))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
X Y M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 91.2 0 1 0 0 0 0 0 0 0 0 0 0 1
2 99.2 0 0 1 0 0 0 0 0 0 0 0 0 2
3 108.2 0 0 0 1 0 0 0 0 0 0 0 0 3
4 101.5 0 0 0 0 1 0 0 0 0 0 0 0 4
5 106.9 0 0 0 0 0 1 0 0 0 0 0 0 5
6 104.4 0 0 0 0 0 0 1 0 0 0 0 0 6
7 77.9 0 0 0 0 0 0 0 1 0 0 0 0 7
8 60.0 0 0 0 0 0 0 0 0 1 0 0 0 8
9 99.5 0 0 0 0 0 0 0 0 0 1 0 0 9
10 95.0 0 0 0 0 0 0 0 0 0 0 1 0 10
11 105.6 0 0 0 0 0 0 0 0 0 0 0 1 11
12 102.5 0 0 0 0 0 0 0 0 0 0 0 0 12
13 93.3 0 1 0 0 0 0 0 0 0 0 0 0 13
14 97.3 0 0 1 0 0 0 0 0 0 0 0 0 14
15 127.0 0 0 0 1 0 0 0 0 0 0 0 0 15
16 111.7 0 0 0 0 1 0 0 0 0 0 0 0 16
17 96.4 0 0 0 0 0 1 0 0 0 0 0 0 17
18 133.0 0 0 0 0 0 0 1 0 0 0 0 0 18
19 72.2 0 0 0 0 0 0 0 1 0 0 0 0 19
20 95.8 0 0 0 0 0 0 0 0 1 0 0 0 20
21 124.1 0 0 0 0 0 0 0 0 0 1 0 0 21
22 127.6 0 0 0 0 0 0 0 0 0 0 1 0 22
23 110.7 0 0 0 0 0 0 0 0 0 0 0 1 23
24 104.6 0 0 0 0 0 0 0 0 0 0 0 0 24
25 112.7 1 1 0 0 0 0 0 0 0 0 0 0 25
26 115.3 1 0 1 0 0 0 0 0 0 0 0 0 26
27 139.4 1 0 0 1 0 0 0 0 0 0 0 0 27
28 119.0 1 0 0 0 1 0 0 0 0 0 0 0 28
29 97.4 1 0 0 0 0 1 0 0 0 0 0 0 29
30 154.0 1 0 0 0 0 0 1 0 0 0 0 0 30
31 81.5 1 0 0 0 0 0 0 1 0 0 0 0 31
32 88.8 1 0 0 0 0 0 0 0 1 0 0 0 32
33 127.7 1 0 0 0 0 0 0 0 0 1 0 0 33
34 105.1 1 0 0 0 0 0 0 0 0 0 1 0 34
35 114.9 1 0 0 0 0 0 0 0 0 0 0 1 35
36 106.4 1 0 0 0 0 0 0 0 0 0 0 0 36
37 104.5 1 1 0 0 0 0 0 0 0 0 0 0 37
38 121.6 1 0 1 0 0 0 0 0 0 0 0 0 38
39 141.4 1 0 0 1 0 0 0 0 0 0 0 0 39
40 99.0 1 0 0 0 1 0 0 0 0 0 0 0 40
41 126.7 1 0 0 0 0 1 0 0 0 0 0 0 41
42 134.1 1 0 0 0 0 0 1 0 0 0 0 0 42
43 81.3 1 0 0 0 0 0 0 1 0 0 0 0 43
44 88.6 1 0 0 0 0 0 0 0 1 0 0 0 44
45 132.7 1 0 0 0 0 0 0 0 0 1 0 0 45
46 132.9 1 0 0 0 0 0 0 0 0 0 1 0 46
47 134.4 1 0 0 0 0 0 0 0 0 0 0 1 47
48 103.7 1 0 0 0 0 0 0 0 0 0 0 0 48
49 119.7 1 1 0 0 0 0 0 0 0 0 0 0 49
50 115.0 1 0 1 0 0 0 0 0 0 0 0 0 50
51 132.9 1 0 0 1 0 0 0 0 0 0 0 0 51
52 108.5 1 0 0 0 1 0 0 0 0 0 0 0 52
53 113.9 1 0 0 0 0 1 0 0 0 0 0 0 53
54 142.0 1 0 0 0 0 0 1 0 0 0 0 0 54
55 97.7 1 0 0 0 0 0 0 1 0 0 0 0 55
56 92.2 1 0 0 0 0 0 0 0 1 0 0 0 56
57 128.8 1 0 0 0 0 0 0 0 0 1 0 0 57
58 134.9 1 0 0 0 0 0 0 0 0 0 1 0 58
59 128.2 1 0 0 0 0 0 0 0 0 0 0 1 59
60 114.8 1 0 0 0 0 0 0 0 0 0 0 0 60
61 117.9 1 1 0 0 0 0 0 0 0 0 0 0 61
62 119.1 1 0 1 0 0 0 0 0 0 0 0 0 62
63 120.7 1 0 0 1 0 0 0 0 0 0 0 0 63
64 129.1 1 0 0 0 1 0 0 0 0 0 0 0 64
65 117.6 1 0 0 0 0 1 0 0 0 0 0 0 65
66 129.2 1 0 0 0 0 0 1 0 0 0 0 0 66
67 100.0 1 0 0 0 0 0 0 1 0 0 0 0 67
68 87.3 1 0 0 0 0 0 0 0 1 0 0 0 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y M1 M2 M3 M4
93.7594 6.6017 0.9154 5.3743 22.1499 5.1088
M5 M6 M7 M8 M9 M10
3.2177 25.9432 -21.9812 -21.8723 16.8833 13.1822
M11 t
12.6011 0.2411
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-17.0002 -4.8091 -0.2215 6.6329 20.4627
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 93.7594 4.8616 19.286 < 2e-16 ***
Y 6.6017 4.4463 1.485 0.143422
M1 0.9154 5.8992 0.155 0.877265
M2 5.3743 5.8857 0.913 0.365242
M3 22.1499 5.8741 3.771 0.000405 ***
M4 5.1088 5.8645 0.871 0.387537
M5 3.2177 5.8569 0.549 0.585010
M6 25.9432 5.8513 4.434 4.58e-05 ***
M7 -21.9812 5.8477 -3.759 0.000421 ***
M8 -21.8723 5.8461 -3.741 0.000445 ***
M9 16.8833 6.1123 2.762 0.007832 **
M10 13.1822 6.1075 2.158 0.035363 *
M11 12.6011 6.1046 2.064 0.043817 *
t 0.2411 0.1086 2.220 0.030649 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.651 on 54 degrees of freedom
Multiple R-squared: 0.7813, Adjusted R-squared: 0.7287
F-statistic: 14.84 on 13 and 54 DF, p-value: 1.955e-13
> 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,] 0.5964834 0.80703319 0.40351660
[2,] 0.7694324 0.46113514 0.23056757
[3,] 0.7462730 0.50745390 0.25372695
[4,] 0.8956924 0.20861530 0.10430765
[5,] 0.8724605 0.25507903 0.12753951
[6,] 0.8930776 0.21384483 0.10692242
[7,] 0.8547931 0.29041375 0.14520688
[8,] 0.8087143 0.38257147 0.19128573
[9,] 0.7326435 0.53471300 0.26735650
[10,] 0.6467229 0.70655411 0.35327706
[11,] 0.5863037 0.82739254 0.41369627
[12,] 0.5408368 0.91832643 0.45916322
[13,] 0.6663267 0.66734654 0.33367327
[14,] 0.8348123 0.33037545 0.16518772
[15,] 0.8004148 0.39917046 0.19958523
[16,] 0.7437374 0.51252512 0.25626256
[17,] 0.6661654 0.66766929 0.33383464
[18,] 0.8497345 0.30053098 0.15026549
[19,] 0.8480632 0.30387358 0.15193679
[20,] 0.8021318 0.39573648 0.19786824
[21,] 0.8198982 0.36020355 0.18010177
[22,] 0.7641614 0.47167719 0.23583859
[23,] 0.8041827 0.39163450 0.19581725
[24,] 0.9310571 0.13788584 0.06894292
[25,] 0.9434966 0.11300688 0.05650344
[26,] 0.9166521 0.16669571 0.08334786
[27,] 0.9500431 0.09991385 0.04995692
[28,] 0.9161028 0.16779437 0.08389719
[29,] 0.8685154 0.26296919 0.13148459
[30,] 0.8037065 0.39258700 0.19629350
[31,] 0.7416140 0.51677197 0.25838599
[32,] 0.7161003 0.56779949 0.28389974
[33,] 0.5865414 0.82691723 0.41345861
[34,] 0.4585587 0.91711740 0.54144130
[35,] 0.4146479 0.82929581 0.58535209
> postscript(file="/var/www/html/freestat/rcomp/tmp/1dwuq1227359805.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2lnm11227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xwdm1227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4yjvo1227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5oom11227359805.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 = 68
Frequency = 1
1 2 3 4 5 6
-3.71588050 -0.41588050 -8.43254717 1.66745283 8.71745283 -16.74921384
7 8 9 10 11 12
4.43411950 -13.81588050 -13.31259434 -14.35259434 -3.41259434 5.84740566
13 14 15 16 17 18
-4.50908805 -5.20908805 7.47424528 8.97424528 -4.67575472 8.95757862
19 20 21 22 23 24
-4.15908805 19.09091195 8.39419811 15.35419811 -1.20580189 5.05419811
25 26 27 28 29 30
5.39605346 3.29605346 10.37938679 6.77938679 -13.17061321 20.46272013
31 32 33 34 35 36
-4.35394654 2.59605346 2.49933962 -16.64066038 -6.50066038 -2.64066038
37 38 39 40 41 42
-5.69715409 6.70284591 9.48617925 -16.11382075 13.23617925 -2.33048742
43 44 45 46 47 48
-7.44715409 -0.49715409 4.60613208 8.26613208 10.10613208 -8.23386792
49 50 51 52 53 54
6.60963836 -2.79036164 -1.90702830 -9.50702830 -2.45702830 2.67630503
55 56 57 58 59 60
6.05963836 0.20963836 -2.18707547 7.37292453 1.01292453 -0.02707547
61 62 63 64 65 66
1.91643082 -1.58356918 -17.00023585 8.19976415 -1.65023585 -13.01690252
67 68
5.46643082 -7.58356918
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ea8z1227359805.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 -3.71588050 NA
1 -0.41588050 -3.71588050
2 -8.43254717 -0.41588050
3 1.66745283 -8.43254717
4 8.71745283 1.66745283
5 -16.74921384 8.71745283
6 4.43411950 -16.74921384
7 -13.81588050 4.43411950
8 -13.31259434 -13.81588050
9 -14.35259434 -13.31259434
10 -3.41259434 -14.35259434
11 5.84740566 -3.41259434
12 -4.50908805 5.84740566
13 -5.20908805 -4.50908805
14 7.47424528 -5.20908805
15 8.97424528 7.47424528
16 -4.67575472 8.97424528
17 8.95757862 -4.67575472
18 -4.15908805 8.95757862
19 19.09091195 -4.15908805
20 8.39419811 19.09091195
21 15.35419811 8.39419811
22 -1.20580189 15.35419811
23 5.05419811 -1.20580189
24 5.39605346 5.05419811
25 3.29605346 5.39605346
26 10.37938679 3.29605346
27 6.77938679 10.37938679
28 -13.17061321 6.77938679
29 20.46272013 -13.17061321
30 -4.35394654 20.46272013
31 2.59605346 -4.35394654
32 2.49933962 2.59605346
33 -16.64066038 2.49933962
34 -6.50066038 -16.64066038
35 -2.64066038 -6.50066038
36 -5.69715409 -2.64066038
37 6.70284591 -5.69715409
38 9.48617925 6.70284591
39 -16.11382075 9.48617925
40 13.23617925 -16.11382075
41 -2.33048742 13.23617925
42 -7.44715409 -2.33048742
43 -0.49715409 -7.44715409
44 4.60613208 -0.49715409
45 8.26613208 4.60613208
46 10.10613208 8.26613208
47 -8.23386792 10.10613208
48 6.60963836 -8.23386792
49 -2.79036164 6.60963836
50 -1.90702830 -2.79036164
51 -9.50702830 -1.90702830
52 -2.45702830 -9.50702830
53 2.67630503 -2.45702830
54 6.05963836 2.67630503
55 0.20963836 6.05963836
56 -2.18707547 0.20963836
57 7.37292453 -2.18707547
58 1.01292453 7.37292453
59 -0.02707547 1.01292453
60 1.91643082 -0.02707547
61 -1.58356918 1.91643082
62 -17.00023585 -1.58356918
63 8.19976415 -17.00023585
64 -1.65023585 8.19976415
65 -13.01690252 -1.65023585
66 5.46643082 -13.01690252
67 -7.58356918 5.46643082
68 NA -7.58356918
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.41588050 -3.71588050
[2,] -8.43254717 -0.41588050
[3,] 1.66745283 -8.43254717
[4,] 8.71745283 1.66745283
[5,] -16.74921384 8.71745283
[6,] 4.43411950 -16.74921384
[7,] -13.81588050 4.43411950
[8,] -13.31259434 -13.81588050
[9,] -14.35259434 -13.31259434
[10,] -3.41259434 -14.35259434
[11,] 5.84740566 -3.41259434
[12,] -4.50908805 5.84740566
[13,] -5.20908805 -4.50908805
[14,] 7.47424528 -5.20908805
[15,] 8.97424528 7.47424528
[16,] -4.67575472 8.97424528
[17,] 8.95757862 -4.67575472
[18,] -4.15908805 8.95757862
[19,] 19.09091195 -4.15908805
[20,] 8.39419811 19.09091195
[21,] 15.35419811 8.39419811
[22,] -1.20580189 15.35419811
[23,] 5.05419811 -1.20580189
[24,] 5.39605346 5.05419811
[25,] 3.29605346 5.39605346
[26,] 10.37938679 3.29605346
[27,] 6.77938679 10.37938679
[28,] -13.17061321 6.77938679
[29,] 20.46272013 -13.17061321
[30,] -4.35394654 20.46272013
[31,] 2.59605346 -4.35394654
[32,] 2.49933962 2.59605346
[33,] -16.64066038 2.49933962
[34,] -6.50066038 -16.64066038
[35,] -2.64066038 -6.50066038
[36,] -5.69715409 -2.64066038
[37,] 6.70284591 -5.69715409
[38,] 9.48617925 6.70284591
[39,] -16.11382075 9.48617925
[40,] 13.23617925 -16.11382075
[41,] -2.33048742 13.23617925
[42,] -7.44715409 -2.33048742
[43,] -0.49715409 -7.44715409
[44,] 4.60613208 -0.49715409
[45,] 8.26613208 4.60613208
[46,] 10.10613208 8.26613208
[47,] -8.23386792 10.10613208
[48,] 6.60963836 -8.23386792
[49,] -2.79036164 6.60963836
[50,] -1.90702830 -2.79036164
[51,] -9.50702830 -1.90702830
[52,] -2.45702830 -9.50702830
[53,] 2.67630503 -2.45702830
[54,] 6.05963836 2.67630503
[55,] 0.20963836 6.05963836
[56,] -2.18707547 0.20963836
[57,] 7.37292453 -2.18707547
[58,] 1.01292453 7.37292453
[59,] -0.02707547 1.01292453
[60,] 1.91643082 -0.02707547
[61,] -1.58356918 1.91643082
[62,] -17.00023585 -1.58356918
[63,] 8.19976415 -17.00023585
[64,] -1.65023585 8.19976415
[65,] -13.01690252 -1.65023585
[66,] 5.46643082 -13.01690252
[67,] -7.58356918 5.46643082
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.41588050 -3.71588050
2 -8.43254717 -0.41588050
3 1.66745283 -8.43254717
4 8.71745283 1.66745283
5 -16.74921384 8.71745283
6 4.43411950 -16.74921384
7 -13.81588050 4.43411950
8 -13.31259434 -13.81588050
9 -14.35259434 -13.31259434
10 -3.41259434 -14.35259434
11 5.84740566 -3.41259434
12 -4.50908805 5.84740566
13 -5.20908805 -4.50908805
14 7.47424528 -5.20908805
15 8.97424528 7.47424528
16 -4.67575472 8.97424528
17 8.95757862 -4.67575472
18 -4.15908805 8.95757862
19 19.09091195 -4.15908805
20 8.39419811 19.09091195
21 15.35419811 8.39419811
22 -1.20580189 15.35419811
23 5.05419811 -1.20580189
24 5.39605346 5.05419811
25 3.29605346 5.39605346
26 10.37938679 3.29605346
27 6.77938679 10.37938679
28 -13.17061321 6.77938679
29 20.46272013 -13.17061321
30 -4.35394654 20.46272013
31 2.59605346 -4.35394654
32 2.49933962 2.59605346
33 -16.64066038 2.49933962
34 -6.50066038 -16.64066038
35 -2.64066038 -6.50066038
36 -5.69715409 -2.64066038
37 6.70284591 -5.69715409
38 9.48617925 6.70284591
39 -16.11382075 9.48617925
40 13.23617925 -16.11382075
41 -2.33048742 13.23617925
42 -7.44715409 -2.33048742
43 -0.49715409 -7.44715409
44 4.60613208 -0.49715409
45 8.26613208 4.60613208
46 10.10613208 8.26613208
47 -8.23386792 10.10613208
48 6.60963836 -8.23386792
49 -2.79036164 6.60963836
50 -1.90702830 -2.79036164
51 -9.50702830 -1.90702830
52 -2.45702830 -9.50702830
53 2.67630503 -2.45702830
54 6.05963836 2.67630503
55 0.20963836 6.05963836
56 -2.18707547 0.20963836
57 7.37292453 -2.18707547
58 1.01292453 7.37292453
59 -0.02707547 1.01292453
60 1.91643082 -0.02707547
61 -1.58356918 1.91643082
62 -17.00023585 -1.58356918
63 8.19976415 -17.00023585
64 -1.65023585 8.19976415
65 -13.01690252 -1.65023585
66 5.46643082 -13.01690252
67 -7.58356918 5.46643082
> 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/7w85l1227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8e6781227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/953zg1227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10n7kh1227359805.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lxi11227359805.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/12q4hj1227359805.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/13hab01227359805.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/14b4ka1227359805.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/15hk0l1227359805.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/16qw961227359805.tab")
+ }
>
> system("convert tmp/1dwuq1227359805.ps tmp/1dwuq1227359805.png")
> system("convert tmp/2lnm11227359805.ps tmp/2lnm11227359805.png")
> system("convert tmp/3xwdm1227359805.ps tmp/3xwdm1227359805.png")
> system("convert tmp/4yjvo1227359805.ps tmp/4yjvo1227359805.png")
> system("convert tmp/5oom11227359805.ps tmp/5oom11227359805.png")
> system("convert tmp/6ea8z1227359805.ps tmp/6ea8z1227359805.png")
> system("convert tmp/7w85l1227359805.ps tmp/7w85l1227359805.png")
> system("convert tmp/8e6781227359805.ps tmp/8e6781227359805.png")
> system("convert tmp/953zg1227359805.ps tmp/953zg1227359805.png")
> system("convert tmp/10n7kh1227359805.ps tmp/10n7kh1227359805.png")
>
>
> proc.time()
user system elapsed
3.723 2.484 4.065