R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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 '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(210907
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+ ,0)
+ ,dim=c(6
+ ,85)
+ ,dimnames=list(c('time'
+ ,'logins'
+ ,'BC'
+ ,'LFM'
+ ,'Course'
+ ,'Totaal')
+ ,1:85))
> y <- array(NA,dim=c(6,85),dimnames=list(c('time','logins','BC','LFM','Course','Totaal'),1:85))
> 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 = '6'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Totaal time logins BC LFM Course
1 2 210907 56 79 94 0
2 4 179321 89 108 103 0
3 0 149061 44 43 93 0
4 0 237213 84 78 123 0
5 -4 173326 88 86 148 0
6 4 133131 55 44 90 0
7 4 258873 60 104 124 0
8 0 324799 154 158 168 0
9 -1 230964 53 102 115 0
10 0 236785 119 77 71 0
11 1 344297 75 80 108 0
12 0 174724 92 123 120 0
13 3 174415 100 73 114 0
14 -1 223632 73 105 120 0
15 4 294424 77 107 124 0
16 3 325107 99 84 126 0
17 1 106408 30 33 37 0
18 0 96560 76 42 38 1
19 -2 265769 146 96 120 0
20 -3 269651 67 106 93 0
21 -4 149112 56 56 95 0
22 2 152871 58 59 90 0
23 2 362301 119 76 110 0
24 -4 183167 66 91 138 0
25 3 277965 89 115 133 0
26 2 218946 41 76 96 0
27 2 244052 68 101 164 0
28 0 341570 168 94 78 1
29 5 233328 132 92 102 0
30 -2 206161 71 75 99 0
31 0 311473 112 128 129 0
32 -2 207176 70 56 114 0
33 -3 196553 57 41 99 0
34 2 143246 103 67 104 0
35 2 182192 52 77 138 0
36 2 194979 62 66 151 0
37 0 167488 45 69 72 0
38 4 143756 46 105 120 0
39 4 275541 63 116 115 0
40 2 152299 53 62 98 0
41 2 193339 78 100 71 0
42 -4 130585 46 67 107 0
43 3 112611 41 46 73 1
44 3 148446 91 135 129 0
45 2 182079 63 124 118 0
46 -1 243060 63 58 104 0
47 -3 162765 32 68 107 0
48 0 85574 34 37 36 1
49 1 225060 93 93 139 0
50 -3 133328 55 56 56 1
51 3 100750 72 83 93 0
52 0 101523 42 59 87 1
53 0 243511 71 133 110 0
54 0 152474 65 106 83 0
55 3 132487 41 71 98 0
56 -3 317394 86 116 82 0
57 0 244749 95 98 115 0
58 -4 184510 49 64 140 0
59 2 128423 64 32 120 0
60 -1 97839 38 25 66 0
61 3 172494 52 46 139 0
62 2 229242 247 63 119 0
63 5 351619 139 95 141 0
64 2 324598 110 113 133 0
65 -2 195838 67 111 98 0
66 0 254488 83 120 117 0
67 3 199476 70 87 105 0
68 -2 92499 32 25 55 1
69 0 224330 83 131 132 0
70 6 181633 70 47 73 0
71 -3 271856 103 109 86 0
72 3 95227 34 37 48 0
73 0 98146 40 15 48 1
74 -2 118612 46 54 43 1
75 1 65475 18 16 46 1
76 0 108446 60 22 65 1
77 2 121848 39 37 52 1
78 2 76302 31 29 68 1
79 -3 98104 54 55 47 1
80 -2 30989 14 5 41 1
81 1 31774 23 0 47 1
82 -4 150580 77 27 71 1
83 0 54157 19 37 30 1
84 1 59382 49 29 24 1
85 0 84105 20 17 63 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time logins BC LFM Course
6.884e-01 -2.077e-06 8.019e-03 -2.244e-03 9.579e-04 -1.123e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.9829 -1.6267 0.3306 1.5161 5.1630
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.884e-01 1.370e+00 0.503 0.617
time -2.077e-06 5.940e-06 -0.350 0.728
logins 8.019e-03 1.005e-02 0.798 0.427
BC -2.244e-03 1.250e-02 -0.180 0.858
LFM 9.579e-04 1.327e-02 0.072 0.943
Course -1.123e+00 9.505e-01 -1.181 0.241
Residual standard error: 2.483 on 79 degrees of freedom
Multiple R-squared: 0.04337, Adjusted R-squared: -0.01717
F-statistic: 0.7164 on 5 and 79 DF, p-value: 0.613
> 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,] 0.7468501 0.5062997 0.2531499
[2,] 0.8291350 0.3417301 0.1708650
[3,] 0.7319801 0.5360399 0.2680199
[4,] 0.6641674 0.6716652 0.3358326
[5,] 0.6902497 0.6195006 0.3097503
[6,] 0.6463258 0.7073484 0.3536742
[7,] 0.6769021 0.6461957 0.3230979
[8,] 0.6451582 0.7096835 0.3548418
[9,] 0.5886091 0.8227819 0.4113909
[10,] 0.4964269 0.9928537 0.5035731
[11,] 0.4940920 0.9881840 0.5059080
[12,] 0.6675142 0.6649715 0.3324858
[13,] 0.8087898 0.3824204 0.1912102
[14,] 0.7670271 0.4659457 0.2329729
[15,] 0.7135680 0.5728639 0.2864320
[16,] 0.8079002 0.3841997 0.1920998
[17,] 0.8001034 0.3997932 0.1998966
[18,] 0.7611421 0.4777157 0.2388579
[19,] 0.7301917 0.5396167 0.2698083
[20,] 0.6712079 0.6575842 0.3287921
[21,] 0.7683191 0.4633617 0.2316809
[22,] 0.7741513 0.4516973 0.2258487
[23,] 0.7253939 0.5492122 0.2746061
[24,] 0.7217713 0.5564573 0.2782287
[25,] 0.7620391 0.4759218 0.2379609
[26,] 0.7266606 0.5466787 0.2733394
[27,] 0.7004295 0.5991410 0.2995705
[28,] 0.6683683 0.6632635 0.3316317
[29,] 0.6090553 0.7818894 0.3909447
[30,] 0.6454986 0.7090027 0.3545014
[31,] 0.6924045 0.6151911 0.3075955
[32,] 0.6474580 0.7050840 0.3525420
[33,] 0.5987892 0.8024215 0.4012108
[34,] 0.7544772 0.4910456 0.2455228
[35,] 0.7892540 0.4214921 0.2107460
[36,] 0.7651700 0.4696601 0.2348300
[37,] 0.7321273 0.5357454 0.2678727
[38,] 0.7018394 0.5963212 0.2981606
[39,] 0.7788302 0.4423397 0.2211698
[40,] 0.7317830 0.5364340 0.2682170
[41,] 0.6737843 0.6524313 0.3262157
[42,] 0.6759712 0.6480575 0.3240288
[43,] 0.6596724 0.6806552 0.3403276
[44,] 0.6055911 0.7888177 0.3944089
[45,] 0.5570870 0.8858261 0.4429130
[46,] 0.4964705 0.9929409 0.5035295
[47,] 0.4935145 0.9870290 0.5064855
[48,] 0.5961851 0.8076297 0.4038149
[49,] 0.5304157 0.9391687 0.4695843
[50,] 0.7665359 0.4669282 0.2334641
[51,] 0.7254023 0.5491954 0.2745977
[52,] 0.8303867 0.3392266 0.1696133
[53,] 0.8233909 0.3532181 0.1766091
[54,] 0.7671096 0.4657807 0.2328904
[55,] 0.8214444 0.3571113 0.1785556
[56,] 0.8032480 0.3935039 0.1967520
[57,] 0.8216017 0.3567966 0.1783983
[58,] 0.7577106 0.4845788 0.2422894
[59,] 0.7114151 0.5771699 0.2885849
[60,] 0.6786441 0.6427118 0.3213559
[61,] 0.6063490 0.7873020 0.3936510
[62,] 0.8156140 0.3687720 0.1843860
[63,] 0.7702048 0.4595904 0.2297952
[64,] 0.6784369 0.6431263 0.3215631
[65,] 0.5604797 0.8790406 0.4395203
[66,] 0.4628577 0.9257153 0.5371423
[67,] 0.3279246 0.6558492 0.6720754
[68,] 0.2316542 0.4633084 0.7683458
> postscript(file="/var/wessaorg/rcomp/tmp/1px321324635218.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/wessaorg/rcomp/tmp/2kvg11324635218.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3kv5n1324635218.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4aulh1324635218.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5rcoz1324635218.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 85
Frequency = 1
1 2 3 4 5 6
1.38776528 3.11399432 -0.72427872 -0.81214518 -4.98290667 3.15954739
7 8 9 10 11 12
3.48267041 -1.05514681 -1.51503046 -1.04612175 0.50128615 -0.90223711
13 14 15 16 17 18
1.92653015 -1.68869077 3.42692110 2.26071380 0.33059990 0.08334938
19 20 21 22 23 24
-3.20673391 -3.51689287 -4.79314393 1.21014670 1.17496563 -4.76525823
25 26 27 28 29 30
2.30584146 1.51609519 1.34269125 -0.06713973 3.84641696 -2.75613698
31 32 33 34 35 36
-0.77599391 -2.80301037 -3.74011875 0.83385424 1.31356572 1.22280234
37 38 39 40 41 42
-0.61557166 3.36191653 3.52877912 1.24812034 1.24401710 -4.73824963
43 44 45 46 47 48
3.37278956 2.06950800 1.34974069 -1.65828404 -3.55690812 0.38801448
49 50 51 52 53 54
0.10877573 -2.65772229 2.04060961 0.35750026 -0.55896121 -0.73464605
55 56 57 58 59 60
2.32339039 -3.53711424 -0.83216039 -4.68864870 1.02193862 -1.79707623
61 62 63 64 65 66
2.22290864 -0.16557377 4.00534264 1.22981512 -2.66376863 -0.66826141
67 68 69 70 71 72
2.25917529 -1.62669066 -0.72058470 5.16301818 -3.78754985 2.27374106
73 74 75 76 77 78
0.30515574 -1.60815310 1.41787104 0.16559637 2.40793353 2.34421028
79 80 81 82 83 84
-2.71648441 -1.64157153 1.27092430 -3.87774028 0.44879117 1.20687934
85
0.42648654
> postscript(file="/var/wessaorg/rcomp/tmp/6dj4o1324635218.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 = 85
Frequency = 1
lag(myerror, k = 1) myerror
0 1.38776528 NA
1 3.11399432 1.38776528
2 -0.72427872 3.11399432
3 -0.81214518 -0.72427872
4 -4.98290667 -0.81214518
5 3.15954739 -4.98290667
6 3.48267041 3.15954739
7 -1.05514681 3.48267041
8 -1.51503046 -1.05514681
9 -1.04612175 -1.51503046
10 0.50128615 -1.04612175
11 -0.90223711 0.50128615
12 1.92653015 -0.90223711
13 -1.68869077 1.92653015
14 3.42692110 -1.68869077
15 2.26071380 3.42692110
16 0.33059990 2.26071380
17 0.08334938 0.33059990
18 -3.20673391 0.08334938
19 -3.51689287 -3.20673391
20 -4.79314393 -3.51689287
21 1.21014670 -4.79314393
22 1.17496563 1.21014670
23 -4.76525823 1.17496563
24 2.30584146 -4.76525823
25 1.51609519 2.30584146
26 1.34269125 1.51609519
27 -0.06713973 1.34269125
28 3.84641696 -0.06713973
29 -2.75613698 3.84641696
30 -0.77599391 -2.75613698
31 -2.80301037 -0.77599391
32 -3.74011875 -2.80301037
33 0.83385424 -3.74011875
34 1.31356572 0.83385424
35 1.22280234 1.31356572
36 -0.61557166 1.22280234
37 3.36191653 -0.61557166
38 3.52877912 3.36191653
39 1.24812034 3.52877912
40 1.24401710 1.24812034
41 -4.73824963 1.24401710
42 3.37278956 -4.73824963
43 2.06950800 3.37278956
44 1.34974069 2.06950800
45 -1.65828404 1.34974069
46 -3.55690812 -1.65828404
47 0.38801448 -3.55690812
48 0.10877573 0.38801448
49 -2.65772229 0.10877573
50 2.04060961 -2.65772229
51 0.35750026 2.04060961
52 -0.55896121 0.35750026
53 -0.73464605 -0.55896121
54 2.32339039 -0.73464605
55 -3.53711424 2.32339039
56 -0.83216039 -3.53711424
57 -4.68864870 -0.83216039
58 1.02193862 -4.68864870
59 -1.79707623 1.02193862
60 2.22290864 -1.79707623
61 -0.16557377 2.22290864
62 4.00534264 -0.16557377
63 1.22981512 4.00534264
64 -2.66376863 1.22981512
65 -0.66826141 -2.66376863
66 2.25917529 -0.66826141
67 -1.62669066 2.25917529
68 -0.72058470 -1.62669066
69 5.16301818 -0.72058470
70 -3.78754985 5.16301818
71 2.27374106 -3.78754985
72 0.30515574 2.27374106
73 -1.60815310 0.30515574
74 1.41787104 -1.60815310
75 0.16559637 1.41787104
76 2.40793353 0.16559637
77 2.34421028 2.40793353
78 -2.71648441 2.34421028
79 -1.64157153 -2.71648441
80 1.27092430 -1.64157153
81 -3.87774028 1.27092430
82 0.44879117 -3.87774028
83 1.20687934 0.44879117
84 0.42648654 1.20687934
85 NA 0.42648654
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.11399432 1.38776528
[2,] -0.72427872 3.11399432
[3,] -0.81214518 -0.72427872
[4,] -4.98290667 -0.81214518
[5,] 3.15954739 -4.98290667
[6,] 3.48267041 3.15954739
[7,] -1.05514681 3.48267041
[8,] -1.51503046 -1.05514681
[9,] -1.04612175 -1.51503046
[10,] 0.50128615 -1.04612175
[11,] -0.90223711 0.50128615
[12,] 1.92653015 -0.90223711
[13,] -1.68869077 1.92653015
[14,] 3.42692110 -1.68869077
[15,] 2.26071380 3.42692110
[16,] 0.33059990 2.26071380
[17,] 0.08334938 0.33059990
[18,] -3.20673391 0.08334938
[19,] -3.51689287 -3.20673391
[20,] -4.79314393 -3.51689287
[21,] 1.21014670 -4.79314393
[22,] 1.17496563 1.21014670
[23,] -4.76525823 1.17496563
[24,] 2.30584146 -4.76525823
[25,] 1.51609519 2.30584146
[26,] 1.34269125 1.51609519
[27,] -0.06713973 1.34269125
[28,] 3.84641696 -0.06713973
[29,] -2.75613698 3.84641696
[30,] -0.77599391 -2.75613698
[31,] -2.80301037 -0.77599391
[32,] -3.74011875 -2.80301037
[33,] 0.83385424 -3.74011875
[34,] 1.31356572 0.83385424
[35,] 1.22280234 1.31356572
[36,] -0.61557166 1.22280234
[37,] 3.36191653 -0.61557166
[38,] 3.52877912 3.36191653
[39,] 1.24812034 3.52877912
[40,] 1.24401710 1.24812034
[41,] -4.73824963 1.24401710
[42,] 3.37278956 -4.73824963
[43,] 2.06950800 3.37278956
[44,] 1.34974069 2.06950800
[45,] -1.65828404 1.34974069
[46,] -3.55690812 -1.65828404
[47,] 0.38801448 -3.55690812
[48,] 0.10877573 0.38801448
[49,] -2.65772229 0.10877573
[50,] 2.04060961 -2.65772229
[51,] 0.35750026 2.04060961
[52,] -0.55896121 0.35750026
[53,] -0.73464605 -0.55896121
[54,] 2.32339039 -0.73464605
[55,] -3.53711424 2.32339039
[56,] -0.83216039 -3.53711424
[57,] -4.68864870 -0.83216039
[58,] 1.02193862 -4.68864870
[59,] -1.79707623 1.02193862
[60,] 2.22290864 -1.79707623
[61,] -0.16557377 2.22290864
[62,] 4.00534264 -0.16557377
[63,] 1.22981512 4.00534264
[64,] -2.66376863 1.22981512
[65,] -0.66826141 -2.66376863
[66,] 2.25917529 -0.66826141
[67,] -1.62669066 2.25917529
[68,] -0.72058470 -1.62669066
[69,] 5.16301818 -0.72058470
[70,] -3.78754985 5.16301818
[71,] 2.27374106 -3.78754985
[72,] 0.30515574 2.27374106
[73,] -1.60815310 0.30515574
[74,] 1.41787104 -1.60815310
[75,] 0.16559637 1.41787104
[76,] 2.40793353 0.16559637
[77,] 2.34421028 2.40793353
[78,] -2.71648441 2.34421028
[79,] -1.64157153 -2.71648441
[80,] 1.27092430 -1.64157153
[81,] -3.87774028 1.27092430
[82,] 0.44879117 -3.87774028
[83,] 1.20687934 0.44879117
[84,] 0.42648654 1.20687934
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.11399432 1.38776528
2 -0.72427872 3.11399432
3 -0.81214518 -0.72427872
4 -4.98290667 -0.81214518
5 3.15954739 -4.98290667
6 3.48267041 3.15954739
7 -1.05514681 3.48267041
8 -1.51503046 -1.05514681
9 -1.04612175 -1.51503046
10 0.50128615 -1.04612175
11 -0.90223711 0.50128615
12 1.92653015 -0.90223711
13 -1.68869077 1.92653015
14 3.42692110 -1.68869077
15 2.26071380 3.42692110
16 0.33059990 2.26071380
17 0.08334938 0.33059990
18 -3.20673391 0.08334938
19 -3.51689287 -3.20673391
20 -4.79314393 -3.51689287
21 1.21014670 -4.79314393
22 1.17496563 1.21014670
23 -4.76525823 1.17496563
24 2.30584146 -4.76525823
25 1.51609519 2.30584146
26 1.34269125 1.51609519
27 -0.06713973 1.34269125
28 3.84641696 -0.06713973
29 -2.75613698 3.84641696
30 -0.77599391 -2.75613698
31 -2.80301037 -0.77599391
32 -3.74011875 -2.80301037
33 0.83385424 -3.74011875
34 1.31356572 0.83385424
35 1.22280234 1.31356572
36 -0.61557166 1.22280234
37 3.36191653 -0.61557166
38 3.52877912 3.36191653
39 1.24812034 3.52877912
40 1.24401710 1.24812034
41 -4.73824963 1.24401710
42 3.37278956 -4.73824963
43 2.06950800 3.37278956
44 1.34974069 2.06950800
45 -1.65828404 1.34974069
46 -3.55690812 -1.65828404
47 0.38801448 -3.55690812
48 0.10877573 0.38801448
49 -2.65772229 0.10877573
50 2.04060961 -2.65772229
51 0.35750026 2.04060961
52 -0.55896121 0.35750026
53 -0.73464605 -0.55896121
54 2.32339039 -0.73464605
55 -3.53711424 2.32339039
56 -0.83216039 -3.53711424
57 -4.68864870 -0.83216039
58 1.02193862 -4.68864870
59 -1.79707623 1.02193862
60 2.22290864 -1.79707623
61 -0.16557377 2.22290864
62 4.00534264 -0.16557377
63 1.22981512 4.00534264
64 -2.66376863 1.22981512
65 -0.66826141 -2.66376863
66 2.25917529 -0.66826141
67 -1.62669066 2.25917529
68 -0.72058470 -1.62669066
69 5.16301818 -0.72058470
70 -3.78754985 5.16301818
71 2.27374106 -3.78754985
72 0.30515574 2.27374106
73 -1.60815310 0.30515574
74 1.41787104 -1.60815310
75 0.16559637 1.41787104
76 2.40793353 0.16559637
77 2.34421028 2.40793353
78 -2.71648441 2.34421028
79 -1.64157153 -2.71648441
80 1.27092430 -1.64157153
81 -3.87774028 1.27092430
82 0.44879117 -3.87774028
83 1.20687934 0.44879117
84 0.42648654 1.20687934
> 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/wessaorg/rcomp/tmp/75yjw1324635218.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/wessaorg/rcomp/tmp/8hy761324635218.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/wessaorg/rcomp/tmp/9va8g1324635218.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/wessaorg/rcomp/tmp/106phr1324635218.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11kneu1324635218.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12hzb81324635218.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13c08q1324635218.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14jceo1324635218.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/wessaorg/rcomp/tmp/15byls1324635219.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/wessaorg/rcomp/tmp/16xszs1324635219.tab")
+ }
>
> try(system("convert tmp/1px321324635218.ps tmp/1px321324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kvg11324635218.ps tmp/2kvg11324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kv5n1324635218.ps tmp/3kv5n1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/4aulh1324635218.ps tmp/4aulh1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rcoz1324635218.ps tmp/5rcoz1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dj4o1324635218.ps tmp/6dj4o1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/75yjw1324635218.ps tmp/75yjw1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hy761324635218.ps tmp/8hy761324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/9va8g1324635218.ps tmp/9va8g1324635218.png",intern=TRUE))
character(0)
> try(system("convert tmp/106phr1324635218.ps tmp/106phr1324635218.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.445 0.556 4.040