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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(2
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+ ,dim=c(6
+ ,85)
+ ,dimnames=list(c('SCORE'
+ ,'time_in_rfc'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p120'
+ ,'totsize')
+ ,1:85))
> y <- array(NA,dim=c(6,85),dimnames=list(c('SCORE','time_in_rfc','blogged_computations','compendiums_reviewed','feedback_messages_p120','totsize'),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 = '1'
> 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
SCORE time_in_rfc blogged_computations compendiums_reviewed
1 2 210907 79 30
2 4 179321 108 30
3 0 149061 43 26
4 0 237213 78 38
5 -4 173326 86 44
6 4 133131 44 30
7 4 258873 104 40
8 0 324799 158 47
9 -1 230964 102 30
10 0 236785 77 31
11 1 344297 80 30
12 0 174724 123 34
13 3 174415 73 31
14 -1 223632 105 33
15 4 294424 107 33
16 3 325107 84 36
17 1 106408 33 14
18 0 96560 42 17
19 -2 265769 96 32
20 -3 269651 106 30
21 -4 149112 56 35
22 2 152871 59 28
23 2 362301 76 34
24 -4 183167 91 39
25 3 277965 115 39
26 2 218946 76 29
27 2 244052 101 44
28 0 341570 94 21
29 5 233328 92 28
30 -2 206161 75 28
31 0 311473 128 38
32 -2 207176 56 32
33 -3 196553 41 29
34 2 143246 67 27
35 2 182192 77 40
36 2 194979 66 40
37 0 167488 69 28
38 4 143756 105 34
39 4 275541 116 33
40 2 152299 62 33
41 2 193339 100 35
42 -4 130585 67 29
43 3 112611 46 20
44 3 148446 135 37
45 2 182079 124 33
46 -1 243060 58 29
47 -3 162765 68 28
48 0 85574 37 21
49 1 225060 93 41
50 -3 133328 56 20
51 3 100750 83 30
52 0 101523 59 22
53 0 243511 133 42
54 0 152474 106 32
55 3 132487 71 36
56 -3 317394 116 31
57 0 244749 98 33
58 -4 184510 64 40
59 2 128423 32 38
60 -1 97839 25 24
61 3 172494 46 43
62 2 229242 63 31
63 5 351619 95 40
64 2 324598 113 37
65 -2 195838 111 31
66 0 254488 120 39
67 3 199476 87 32
68 -2 92499 25 18
69 0 224330 131 39
70 6 181633 47 30
71 -3 271856 109 37
72 3 95227 37 32
73 0 98146 15 17
74 -2 118612 54 12
75 1 65475 16 13
76 0 108446 22 17
77 2 121848 37 17
78 2 76302 29 20
79 -3 98104 55 17
80 -2 30989 5 17
81 1 31774 0 17
82 -4 150580 27 22
83 0 54157 37 15
84 1 59382 29 12
85 0 84105 17 17
feedback_messages_p120 totsize
1 94 112285
2 103 101193
3 93 116174
4 123 66198
5 148 71701
6 90 57793
7 124 80444
8 168 97668
9 115 133824
10 71 101481
11 108 67654
12 120 69112
13 114 82753
14 120 72654
15 124 101494
16 126 79215
17 37 31081
18 38 22996
19 120 83122
20 93 70106
21 95 60578
22 90 79892
23 110 100708
24 138 82875
25 133 139077
26 96 80670
27 164 143558
28 78 117105
29 102 120733
30 99 73107
31 129 132068
32 114 87011
33 99 95260
34 104 106671
35 138 70054
36 151 74011
37 72 83737
38 120 69094
39 115 93133
40 98 61370
41 71 84651
42 107 95364
43 73 26706
44 129 126846
45 118 102860
46 104 111813
47 107 120293
48 36 24266
49 139 109825
50 56 40909
51 93 140867
52 87 61056
53 110 101338
54 83 65567
55 98 40735
56 82 91413
57 115 76643
58 140 110681
59 120 92696
60 66 94785
61 139 86687
62 119 91721
63 141 115168
64 133 135777
65 98 102372
66 117 103772
67 105 135400
68 55 21399
69 132 130115
70 73 64466
71 86 54990
72 48 34777
73 48 27114
74 43 30080
75 46 69008
76 65 46300
77 52 30594
78 68 30976
79 47 25568
80 41 4154
81 47 4143
82 71 45588
83 30 18625
84 24 26263
85 63 20055
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc blogged_computations
-9.092e-01 -1.664e-07 -3.879e-03
compendiums_reviewed feedback_messages_p120 totsize
4.874e-02 -5.932e-03 1.111e-05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5.1612 -1.6979 0.2294 1.4998 5.3760
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -9.092e-01 1.024e+00 -0.887 0.378
time_in_rfc -1.664e-07 5.294e-06 -0.031 0.975
blogged_computations -3.879e-03 1.315e-02 -0.295 0.769
compendiums_reviewed 4.874e-02 7.591e-02 0.642 0.523
feedback_messages_p120 -5.932e-03 2.016e-02 -0.294 0.769
totsize 1.111e-05 1.176e-05 0.945 0.348
Residual standard error: 2.493 on 79 degrees of freedom
Multiple R-squared: 0.03555, Adjusted R-squared: -0.02549
F-statistic: 0.5824 on 5 and 79 DF, p-value: 0.7133
> 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,] 0.2491655 0.4983311 0.7508345
[2,] 0.4576801 0.9153602 0.5423199
[3,] 0.4807010 0.9614019 0.5192990
[4,] 0.6429567 0.7140866 0.3570433
[5,] 0.6035073 0.7929854 0.3964927
[6,] 0.5990328 0.8019345 0.4009672
[7,] 0.6428209 0.7143582 0.3571791
[8,] 0.5984752 0.8030495 0.4015248
[9,] 0.5820645 0.8358709 0.4179355
[10,] 0.5206013 0.9587974 0.4793987
[11,] 0.5591562 0.8816877 0.4408438
[12,] 0.6581056 0.6837888 0.3418944
[13,] 0.7591580 0.4816840 0.2408420
[14,] 0.7114229 0.5771543 0.2885771
[15,] 0.6479742 0.7040516 0.3520258
[16,] 0.7499549 0.5000901 0.2500451
[17,] 0.7185209 0.5629583 0.2814791
[18,] 0.6688918 0.6622164 0.3311082
[19,] 0.6090960 0.7818079 0.3909040
[20,] 0.6166845 0.7666310 0.3833155
[21,] 0.7088800 0.5822400 0.2911200
[22,] 0.7050612 0.5898777 0.2949388
[23,] 0.6563533 0.6872934 0.3436467
[24,] 0.6622439 0.6755122 0.3377561
[25,] 0.7193809 0.5612383 0.2806191
[26,] 0.6758316 0.6483368 0.3241684
[27,] 0.6550150 0.6899700 0.3449850
[28,] 0.6189839 0.7620322 0.3810161
[29,] 0.5540651 0.8918698 0.4459349
[30,] 0.6008279 0.7983441 0.3991721
[31,] 0.6550382 0.6899237 0.3449618
[32,] 0.6185780 0.7628440 0.3814220
[33,] 0.5698751 0.8602498 0.4301249
[34,] 0.7197869 0.5604262 0.2802131
[35,] 0.7506729 0.4986543 0.2493271
[36,] 0.7312088 0.5375823 0.2687912
[37,] 0.7137916 0.5724168 0.2862084
[38,] 0.6845836 0.6308327 0.3154164
[39,] 0.7526407 0.4947186 0.2473593
[40,] 0.6965276 0.6069447 0.3034724
[41,] 0.6360828 0.7278345 0.3639172
[42,] 0.6569712 0.6860575 0.3430288
[43,] 0.6326178 0.7347645 0.3673822
[44,] 0.5710036 0.8579928 0.4289964
[45,] 0.5125341 0.9749317 0.4874659
[46,] 0.4528201 0.9056401 0.5471799
[47,] 0.4926563 0.9853127 0.5073437
[48,] 0.6009917 0.7980165 0.3990083
[49,] 0.5333817 0.9332366 0.4666183
[50,] 0.7627431 0.4745138 0.2372569
[51,] 0.7258308 0.5483384 0.2741692
[52,] 0.8389730 0.3220541 0.1610270
[53,] 0.8066651 0.3866698 0.1933349
[54,] 0.7523603 0.4952793 0.2476397
[55,] 0.8142743 0.3714515 0.1857257
[56,] 0.7782801 0.4434398 0.2217199
[57,] 0.7565317 0.4869366 0.2434683
[58,] 0.6836271 0.6327459 0.3163729
[59,] 0.6074450 0.7851099 0.3925550
[60,] 0.5433393 0.9133214 0.4566607
[61,] 0.4569334 0.9138667 0.5430666
[62,] 0.7686082 0.4627837 0.2313918
[63,] 0.6967483 0.6065035 0.3032517
[64,] 0.7001696 0.5996609 0.2998304
[65,] 0.6016726 0.7966547 0.3983274
[66,] 0.5840265 0.8319469 0.4159735
[67,] 0.4554425 0.9108850 0.5445575
[68,] 0.3635389 0.7270777 0.6364611
> postscript(file="/var/wessaorg/rcomp/tmp/1hjxy1323691255.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/2pwb71323691255.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/39cx11323691255.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4frzi1323691255.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5stbo1323691255.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
1.09806245 3.38197202 -0.90605285 -0.60712235 -4.79203731 3.53127296
7 8 9 10 11 12
3.24744443 -0.80373610 -1.92419528 -0.97049951 0.70323768 -0.29817099
13 14 15 16 17 18
2.46685195 -1.35047911 3.37224742 2.40138541 1.24653452 0.22936725
19 20 21 22 23 24
-2.44598103 -3.32456638 -4.66453213 1.44461364 1.14022896 -4.71080057
25 26 27 28 29 30
1.74375428 1.49975456 0.57418548 -0.53180398 4.20327356 -2.35565186
31 32 33 34 35 36
-1.09732744 -2.68971010 -3.78409981 1.30820933 1.32848457 1.32108446
37 38 39 40 41 42
-0.66368249 3.62705376 3.44355279 1.46575539 1.10356851 -4.64791759
43 44 45 46 47 48
3.26772173 2.00948403 1.36872149 -1.86473306 -3.86701159 -0.01281280
49 50 51 52 53 54
-0.08716184 -2.94875026 1.77164497 -0.07991073 -1.05538669 -0.45042729
55 56 57 58 59 60
2.58048388 -3.62864816 -0.44811633 -5.16123819 0.88403345 -1.80935868
61 62 63 64 65 66
1.88145441 1.36717200 3.94287861 0.87792131 -2.69515287 -0.94328071
67 68 69 70 71 72
1.83805105 -1.76739534 -1.10943022 5.37596240 -3.52729303 2.40697252
73 74 75 76 77 78
0.13845218 -1.52576668 0.85437934 0.05492900 2.21278615 2.11861608
79 80 81 82 83 84
-2.69514289 -1.69785192 1.31860030 -4.11887826 0.30152695 1.29711009
85
0.31131709
> postscript(file="/var/wessaorg/rcomp/tmp/6shha1323691255.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 1.09806245 NA
1 3.38197202 1.09806245
2 -0.90605285 3.38197202
3 -0.60712235 -0.90605285
4 -4.79203731 -0.60712235
5 3.53127296 -4.79203731
6 3.24744443 3.53127296
7 -0.80373610 3.24744443
8 -1.92419528 -0.80373610
9 -0.97049951 -1.92419528
10 0.70323768 -0.97049951
11 -0.29817099 0.70323768
12 2.46685195 -0.29817099
13 -1.35047911 2.46685195
14 3.37224742 -1.35047911
15 2.40138541 3.37224742
16 1.24653452 2.40138541
17 0.22936725 1.24653452
18 -2.44598103 0.22936725
19 -3.32456638 -2.44598103
20 -4.66453213 -3.32456638
21 1.44461364 -4.66453213
22 1.14022896 1.44461364
23 -4.71080057 1.14022896
24 1.74375428 -4.71080057
25 1.49975456 1.74375428
26 0.57418548 1.49975456
27 -0.53180398 0.57418548
28 4.20327356 -0.53180398
29 -2.35565186 4.20327356
30 -1.09732744 -2.35565186
31 -2.68971010 -1.09732744
32 -3.78409981 -2.68971010
33 1.30820933 -3.78409981
34 1.32848457 1.30820933
35 1.32108446 1.32848457
36 -0.66368249 1.32108446
37 3.62705376 -0.66368249
38 3.44355279 3.62705376
39 1.46575539 3.44355279
40 1.10356851 1.46575539
41 -4.64791759 1.10356851
42 3.26772173 -4.64791759
43 2.00948403 3.26772173
44 1.36872149 2.00948403
45 -1.86473306 1.36872149
46 -3.86701159 -1.86473306
47 -0.01281280 -3.86701159
48 -0.08716184 -0.01281280
49 -2.94875026 -0.08716184
50 1.77164497 -2.94875026
51 -0.07991073 1.77164497
52 -1.05538669 -0.07991073
53 -0.45042729 -1.05538669
54 2.58048388 -0.45042729
55 -3.62864816 2.58048388
56 -0.44811633 -3.62864816
57 -5.16123819 -0.44811633
58 0.88403345 -5.16123819
59 -1.80935868 0.88403345
60 1.88145441 -1.80935868
61 1.36717200 1.88145441
62 3.94287861 1.36717200
63 0.87792131 3.94287861
64 -2.69515287 0.87792131
65 -0.94328071 -2.69515287
66 1.83805105 -0.94328071
67 -1.76739534 1.83805105
68 -1.10943022 -1.76739534
69 5.37596240 -1.10943022
70 -3.52729303 5.37596240
71 2.40697252 -3.52729303
72 0.13845218 2.40697252
73 -1.52576668 0.13845218
74 0.85437934 -1.52576668
75 0.05492900 0.85437934
76 2.21278615 0.05492900
77 2.11861608 2.21278615
78 -2.69514289 2.11861608
79 -1.69785192 -2.69514289
80 1.31860030 -1.69785192
81 -4.11887826 1.31860030
82 0.30152695 -4.11887826
83 1.29711009 0.30152695
84 0.31131709 1.29711009
85 NA 0.31131709
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.38197202 1.09806245
[2,] -0.90605285 3.38197202
[3,] -0.60712235 -0.90605285
[4,] -4.79203731 -0.60712235
[5,] 3.53127296 -4.79203731
[6,] 3.24744443 3.53127296
[7,] -0.80373610 3.24744443
[8,] -1.92419528 -0.80373610
[9,] -0.97049951 -1.92419528
[10,] 0.70323768 -0.97049951
[11,] -0.29817099 0.70323768
[12,] 2.46685195 -0.29817099
[13,] -1.35047911 2.46685195
[14,] 3.37224742 -1.35047911
[15,] 2.40138541 3.37224742
[16,] 1.24653452 2.40138541
[17,] 0.22936725 1.24653452
[18,] -2.44598103 0.22936725
[19,] -3.32456638 -2.44598103
[20,] -4.66453213 -3.32456638
[21,] 1.44461364 -4.66453213
[22,] 1.14022896 1.44461364
[23,] -4.71080057 1.14022896
[24,] 1.74375428 -4.71080057
[25,] 1.49975456 1.74375428
[26,] 0.57418548 1.49975456
[27,] -0.53180398 0.57418548
[28,] 4.20327356 -0.53180398
[29,] -2.35565186 4.20327356
[30,] -1.09732744 -2.35565186
[31,] -2.68971010 -1.09732744
[32,] -3.78409981 -2.68971010
[33,] 1.30820933 -3.78409981
[34,] 1.32848457 1.30820933
[35,] 1.32108446 1.32848457
[36,] -0.66368249 1.32108446
[37,] 3.62705376 -0.66368249
[38,] 3.44355279 3.62705376
[39,] 1.46575539 3.44355279
[40,] 1.10356851 1.46575539
[41,] -4.64791759 1.10356851
[42,] 3.26772173 -4.64791759
[43,] 2.00948403 3.26772173
[44,] 1.36872149 2.00948403
[45,] -1.86473306 1.36872149
[46,] -3.86701159 -1.86473306
[47,] -0.01281280 -3.86701159
[48,] -0.08716184 -0.01281280
[49,] -2.94875026 -0.08716184
[50,] 1.77164497 -2.94875026
[51,] -0.07991073 1.77164497
[52,] -1.05538669 -0.07991073
[53,] -0.45042729 -1.05538669
[54,] 2.58048388 -0.45042729
[55,] -3.62864816 2.58048388
[56,] -0.44811633 -3.62864816
[57,] -5.16123819 -0.44811633
[58,] 0.88403345 -5.16123819
[59,] -1.80935868 0.88403345
[60,] 1.88145441 -1.80935868
[61,] 1.36717200 1.88145441
[62,] 3.94287861 1.36717200
[63,] 0.87792131 3.94287861
[64,] -2.69515287 0.87792131
[65,] -0.94328071 -2.69515287
[66,] 1.83805105 -0.94328071
[67,] -1.76739534 1.83805105
[68,] -1.10943022 -1.76739534
[69,] 5.37596240 -1.10943022
[70,] -3.52729303 5.37596240
[71,] 2.40697252 -3.52729303
[72,] 0.13845218 2.40697252
[73,] -1.52576668 0.13845218
[74,] 0.85437934 -1.52576668
[75,] 0.05492900 0.85437934
[76,] 2.21278615 0.05492900
[77,] 2.11861608 2.21278615
[78,] -2.69514289 2.11861608
[79,] -1.69785192 -2.69514289
[80,] 1.31860030 -1.69785192
[81,] -4.11887826 1.31860030
[82,] 0.30152695 -4.11887826
[83,] 1.29711009 0.30152695
[84,] 0.31131709 1.29711009
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.38197202 1.09806245
2 -0.90605285 3.38197202
3 -0.60712235 -0.90605285
4 -4.79203731 -0.60712235
5 3.53127296 -4.79203731
6 3.24744443 3.53127296
7 -0.80373610 3.24744443
8 -1.92419528 -0.80373610
9 -0.97049951 -1.92419528
10 0.70323768 -0.97049951
11 -0.29817099 0.70323768
12 2.46685195 -0.29817099
13 -1.35047911 2.46685195
14 3.37224742 -1.35047911
15 2.40138541 3.37224742
16 1.24653452 2.40138541
17 0.22936725 1.24653452
18 -2.44598103 0.22936725
19 -3.32456638 -2.44598103
20 -4.66453213 -3.32456638
21 1.44461364 -4.66453213
22 1.14022896 1.44461364
23 -4.71080057 1.14022896
24 1.74375428 -4.71080057
25 1.49975456 1.74375428
26 0.57418548 1.49975456
27 -0.53180398 0.57418548
28 4.20327356 -0.53180398
29 -2.35565186 4.20327356
30 -1.09732744 -2.35565186
31 -2.68971010 -1.09732744
32 -3.78409981 -2.68971010
33 1.30820933 -3.78409981
34 1.32848457 1.30820933
35 1.32108446 1.32848457
36 -0.66368249 1.32108446
37 3.62705376 -0.66368249
38 3.44355279 3.62705376
39 1.46575539 3.44355279
40 1.10356851 1.46575539
41 -4.64791759 1.10356851
42 3.26772173 -4.64791759
43 2.00948403 3.26772173
44 1.36872149 2.00948403
45 -1.86473306 1.36872149
46 -3.86701159 -1.86473306
47 -0.01281280 -3.86701159
48 -0.08716184 -0.01281280
49 -2.94875026 -0.08716184
50 1.77164497 -2.94875026
51 -0.07991073 1.77164497
52 -1.05538669 -0.07991073
53 -0.45042729 -1.05538669
54 2.58048388 -0.45042729
55 -3.62864816 2.58048388
56 -0.44811633 -3.62864816
57 -5.16123819 -0.44811633
58 0.88403345 -5.16123819
59 -1.80935868 0.88403345
60 1.88145441 -1.80935868
61 1.36717200 1.88145441
62 3.94287861 1.36717200
63 0.87792131 3.94287861
64 -2.69515287 0.87792131
65 -0.94328071 -2.69515287
66 1.83805105 -0.94328071
67 -1.76739534 1.83805105
68 -1.10943022 -1.76739534
69 5.37596240 -1.10943022
70 -3.52729303 5.37596240
71 2.40697252 -3.52729303
72 0.13845218 2.40697252
73 -1.52576668 0.13845218
74 0.85437934 -1.52576668
75 0.05492900 0.85437934
76 2.21278615 0.05492900
77 2.11861608 2.21278615
78 -2.69514289 2.11861608
79 -1.69785192 -2.69514289
80 1.31860030 -1.69785192
81 -4.11887826 1.31860030
82 0.30152695 -4.11887826
83 1.29711009 0.30152695
84 0.31131709 1.29711009
> 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/7812f1323691255.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/89voq1323691255.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/9fmp41323691255.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/10i1cs1323691255.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11datt1323691255.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/121sbu1323691255.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13mnjf1323691255.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/1440pd1323691255.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/152rtb1323691255.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/16nh221323691255.tab")
+ }
>
> try(system("convert tmp/1hjxy1323691255.ps tmp/1hjxy1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pwb71323691255.ps tmp/2pwb71323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/39cx11323691255.ps tmp/39cx11323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/4frzi1323691255.ps tmp/4frzi1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/5stbo1323691255.ps tmp/5stbo1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/6shha1323691255.ps tmp/6shha1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/7812f1323691255.ps tmp/7812f1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/89voq1323691255.ps tmp/89voq1323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fmp41323691255.ps tmp/9fmp41323691255.png",intern=TRUE))
character(0)
> try(system("convert tmp/10i1cs1323691255.ps tmp/10i1cs1323691255.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.630 0.469 4.149