R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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.
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> x <- array(list(98.8,6.3,100.5,6.1,110.4,6.1,96.4,6.3,101.9,6.3,106.2,6,81,6.2,94.7,6.4,101,6.8,109.4,7.5,102.3,7.5,90.7,7.6,96.2,7.6,96.1,7.4,106,7.3,103.1,7.1,102,6.9,104.7,6.8,86,7.5,92.1,7.6,106.9,7.8,112.6,8,101.7,8.1,92,8.2,97.4,8.3,97,8.2,105.4,8,102.7,7.9,98.1,7.6,104.5,7.6,87.4,8.3,89.9,8.4,109.8,8.4,111.7,8.4,98.6,8.4,96.9,8.6,95.1,8.9,97,8.8,112.7,8.3,102.9,7.5,97.4,7.2,111.4,7.4,87.4,8.8,96.8,9.3,114.1,9.3,110.3,8.7,103.9,8.2,101.6,8.3,94.6,8.5,95.9,8.6,104.7,8.5,102.8,8.2,98.1,8.1,113.9,7.9,80.9,8.6,95.7,8.7,113.2,8.7,105.9,8.5,108.8,8.4,102.3,8.5,99,8.7,100.7,8.7,115.5,8.6,100.7,8.5,109.9,8.3,114.6,8,85.4,8.2,100.5,8.1,114.8,8.1,116.5,8,112.9,7.9,102,7.9,106,8,105.3,8,118.8,7.9,106.1,8,109.3,7.7,117.2,7.2,92.5,7.5,104.2,7.3,112.5,7,122.4,7,113.3,7,100,7.2,110.7,7.3,112.8,7.1,109.8,6.8,117.3,6.4,109.1,6.1,115.9,6.5,96,7.7,99.8,7.9,116.8,7.5,115.7,6.9,99.4,6.6,94.3,6.9,91,7.7),dim=c(2,97),dimnames=list(c('Y','X'),1:97))
> y <- array(NA,dim=c(2,97),dimnames=list(c('Y','X'),1:97))
> 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 98.8 6.3
2 100.5 6.1
3 110.4 6.1
4 96.4 6.3
5 101.9 6.3
6 106.2 6.0
7 81.0 6.2
8 94.7 6.4
9 101.0 6.8
10 109.4 7.5
11 102.3 7.5
12 90.7 7.6
13 96.2 7.6
14 96.1 7.4
15 106.0 7.3
16 103.1 7.1
17 102.0 6.9
18 104.7 6.8
19 86.0 7.5
20 92.1 7.6
21 106.9 7.8
22 112.6 8.0
23 101.7 8.1
24 92.0 8.2
25 97.4 8.3
26 97.0 8.2
27 105.4 8.0
28 102.7 7.9
29 98.1 7.6
30 104.5 7.6
31 87.4 8.3
32 89.9 8.4
33 109.8 8.4
34 111.7 8.4
35 98.6 8.4
36 96.9 8.6
37 95.1 8.9
38 97.0 8.8
39 112.7 8.3
40 102.9 7.5
41 97.4 7.2
42 111.4 7.4
43 87.4 8.8
44 96.8 9.3
45 114.1 9.3
46 110.3 8.7
47 103.9 8.2
48 101.6 8.3
49 94.6 8.5
50 95.9 8.6
51 104.7 8.5
52 102.8 8.2
53 98.1 8.1
54 113.9 7.9
55 80.9 8.6
56 95.7 8.7
57 113.2 8.7
58 105.9 8.5
59 108.8 8.4
60 102.3 8.5
61 99.0 8.7
62 100.7 8.7
63 115.5 8.6
64 100.7 8.5
65 109.9 8.3
66 114.6 8.0
67 85.4 8.2
68 100.5 8.1
69 114.8 8.1
70 116.5 8.0
71 112.9 7.9
72 102.0 7.9
73 106.0 8.0
74 105.3 8.0
75 118.8 7.9
76 106.1 8.0
77 109.3 7.7
78 117.2 7.2
79 92.5 7.5
80 104.2 7.3
81 112.5 7.0
82 122.4 7.0
83 113.3 7.0
84 100.0 7.2
85 110.7 7.3
86 112.8 7.1
87 109.8 6.8
88 117.3 6.4
89 109.1 6.1
90 115.9 6.5
91 96.0 7.7
92 99.8 7.9
93 116.8 7.5
94 115.7 6.9
95 99.4 6.6
96 94.3 6.9
97 91.0 7.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
113.617 -1.351
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-24.2413 -5.5395 -0.5851 7.4956 18.2394
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 113.617 8.875 12.802 <2e-16 ***
X -1.351 1.142 -1.182 0.24
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.874 on 95 degrees of freedom
Multiple R-squared: 0.01451, Adjusted R-squared: 0.004131
F-statistic: 1.398 on 1 and 95 DF, p-value: 0.2400
> 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,] 0.14907497 0.2981499 0.8509250
[2,] 0.06466329 0.1293266 0.9353367
[3,] 0.67303290 0.6539342 0.3269671
[4,] 0.57048834 0.8590233 0.4295117
[5,] 0.58167529 0.8366494 0.4183247
[6,] 0.55649731 0.8870054 0.4435027
[7,] 0.45968332 0.9193666 0.5403167
[8,] 0.53762015 0.9247597 0.4623798
[9,] 0.46383986 0.9276797 0.5361601
[10,] 0.39377292 0.7875458 0.6062271
[11,] 0.36059065 0.7211813 0.6394094
[12,] 0.29610620 0.5922124 0.7038938
[13,] 0.23530270 0.4706054 0.7646973
[14,] 0.19469217 0.3893843 0.8053078
[15,] 0.33631369 0.6726274 0.6636863
[16,] 0.32835070 0.6567014 0.6716493
[17,] 0.32874577 0.6574915 0.6712542
[18,] 0.41041084 0.8208217 0.5895892
[19,] 0.34245403 0.6849081 0.6575460
[20,] 0.35561340 0.7112268 0.6443866
[21,] 0.30126340 0.6025268 0.6987366
[22,] 0.25399655 0.5079931 0.7460035
[23,] 0.22320125 0.4464025 0.7767987
[24,] 0.18069669 0.3613934 0.8193033
[25,] 0.14958669 0.2991734 0.8504133
[26,] 0.12290426 0.2458085 0.8770957
[27,] 0.18802842 0.3760568 0.8119716
[28,] 0.21199344 0.4239869 0.7880066
[29,] 0.24128948 0.4825790 0.7587105
[30,] 0.28784303 0.5756861 0.7121570
[31,] 0.24184453 0.4836891 0.7581555
[32,] 0.20537167 0.4107433 0.7946283
[33,] 0.17851068 0.3570214 0.8214893
[34,] 0.14648647 0.2929729 0.8535135
[35,] 0.19102605 0.3820521 0.8089740
[36,] 0.15828664 0.3165733 0.8417134
[37,] 0.14674925 0.2934985 0.8532508
[38,] 0.15849177 0.3169835 0.8415082
[39,] 0.22131331 0.4426266 0.7786867
[40,] 0.18387529 0.3677506 0.8161247
[41,] 0.27745756 0.5549151 0.7225424
[42,] 0.29124029 0.5824806 0.7087597
[43,] 0.24671746 0.4934349 0.7532825
[44,] 0.20349571 0.4069914 0.7965043
[45,] 0.19171228 0.3834246 0.8082877
[46,] 0.17052282 0.3410456 0.8294772
[47,] 0.14093880 0.2818776 0.8590612
[48,] 0.11208879 0.2241776 0.8879112
[49,] 0.09478186 0.1895637 0.9052181
[50,] 0.11748608 0.2349722 0.8825139
[51,] 0.35024235 0.7004847 0.6497577
[52,] 0.33293246 0.6658649 0.6670675
[53,] 0.37499461 0.7499892 0.6250054
[54,] 0.33035637 0.6607127 0.6696436
[55,] 0.30640359 0.6128072 0.6935964
[56,] 0.25717284 0.5143457 0.7428272
[57,] 0.21927484 0.4385497 0.7807252
[58,] 0.18060379 0.3612076 0.8193962
[59,] 0.23777636 0.4755527 0.7622236
[60,] 0.19590250 0.3918050 0.8040975
[61,] 0.18185983 0.3637197 0.8181402
[62,] 0.21242237 0.4248447 0.7875776
[63,] 0.40640333 0.8128067 0.5935967
[64,] 0.36404031 0.7280806 0.6359597
[65,] 0.39665569 0.7933114 0.6033443
[66,] 0.46944161 0.9388832 0.5305584
[67,] 0.47722572 0.9544514 0.5227743
[68,] 0.41476528 0.8295306 0.5852347
[69,] 0.35529509 0.7105902 0.6447049
[70,] 0.29634580 0.5926916 0.7036542
[71,] 0.45024946 0.9004989 0.5497505
[72,] 0.40167125 0.8033425 0.5983288
[73,] 0.37637237 0.7527447 0.6236276
[74,] 0.44200085 0.8840017 0.5579992
[75,] 0.48454817 0.9690963 0.5154518
[76,] 0.40889638 0.8177928 0.5911036
[77,] 0.36463996 0.7292799 0.6353600
[78,] 0.54404279 0.9119144 0.4559572
[79,] 0.51275010 0.9744998 0.4872499
[80,] 0.45139844 0.9027969 0.5486016
[81,] 0.40582783 0.8116557 0.5941722
[82,] 0.37788350 0.7557670 0.6221165
[83,] 0.29407658 0.5881532 0.7059234
[84,] 0.27250915 0.5450183 0.7274909
[85,] 0.19088346 0.3817669 0.8091165
[86,] 0.17428347 0.3485669 0.8257165
[87,] 0.11776225 0.2355245 0.8822377
[88,] 0.06178033 0.1235607 0.9382197
> postscript(file="/var/www/html/rcomp/tmp/1694v1258646894.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22mr91258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/33gpu1258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ww511258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5j59q1258646894.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 = 97
Frequency = 1
1 2 3 4 5 6
-6.3062392 -4.8764273 5.0235727 -8.7062392 -3.2062392 0.6884787
7 8 9 10 11 12
-24.2413332 -10.2711452 -3.4307692 5.9148889 -1.1851111 -12.6500171
13 14 15 16 17 18
-7.1500171 -7.5202051 2.2447009 -0.9254871 -2.2956752 0.2692308
19 20 21 22 23 24
-17.4851111 -11.2500171 3.8201709 9.7903590 -0.9745470 -10.5394530
25 26 27 28 29 30
-5.0043590 -5.5394530 2.5903590 -0.2447351 -5.2500171 1.1499829
31 32 33 34 35 36
-15.0043590 -12.3692650 7.5307350 9.4307350 -3.6692650 -5.0990770
37 38 39 40 41 42
-6.4937949 -4.7288889 10.2956410 -0.5851111 -6.4903931 7.7797949
43 44 45 46 47 48
-14.3288889 -4.2534189 13.0465811 8.4360170 1.3605470 -0.8043590
49 50 51 52 53 54
-7.5341710 -6.0990770 2.5658290 0.2605470 -4.5745470 10.9552649
55 56 57 58 59 60
-21.0990770 -6.1639830 11.3360170 3.7658290 6.5307350 0.1658290
61 62 63 64 65 66
-2.8639830 -1.1639830 13.5009230 -1.4341710 7.4956410 11.7903590
67 68 69 70 71 72
-17.1394530 -2.1745470 12.1254530 13.6903590 9.9552649 -0.9447351
73 74 75 76 77 78
3.1903590 2.4903590 15.8552649 3.2903590 6.0850769 13.3096069
79 80 81 82 83 84
-10.9851111 0.4447009 8.3394188 18.2394188 9.1394188 -3.8903931
85 86 87 88 89 90
6.9447009 8.7745129 5.3692308 12.3288548 3.7235727 11.0639488
91 92 93 94 95 96
-7.2149231 -3.1447351 13.3148889 11.4043248 -5.3009572 -9.9956752
97
-12.2149231
> postscript(file="/var/www/html/rcomp/tmp/67awd1258646894.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 = 97
Frequency = 1
lag(myerror, k = 1) myerror
0 -6.3062392 NA
1 -4.8764273 -6.3062392
2 5.0235727 -4.8764273
3 -8.7062392 5.0235727
4 -3.2062392 -8.7062392
5 0.6884787 -3.2062392
6 -24.2413332 0.6884787
7 -10.2711452 -24.2413332
8 -3.4307692 -10.2711452
9 5.9148889 -3.4307692
10 -1.1851111 5.9148889
11 -12.6500171 -1.1851111
12 -7.1500171 -12.6500171
13 -7.5202051 -7.1500171
14 2.2447009 -7.5202051
15 -0.9254871 2.2447009
16 -2.2956752 -0.9254871
17 0.2692308 -2.2956752
18 -17.4851111 0.2692308
19 -11.2500171 -17.4851111
20 3.8201709 -11.2500171
21 9.7903590 3.8201709
22 -0.9745470 9.7903590
23 -10.5394530 -0.9745470
24 -5.0043590 -10.5394530
25 -5.5394530 -5.0043590
26 2.5903590 -5.5394530
27 -0.2447351 2.5903590
28 -5.2500171 -0.2447351
29 1.1499829 -5.2500171
30 -15.0043590 1.1499829
31 -12.3692650 -15.0043590
32 7.5307350 -12.3692650
33 9.4307350 7.5307350
34 -3.6692650 9.4307350
35 -5.0990770 -3.6692650
36 -6.4937949 -5.0990770
37 -4.7288889 -6.4937949
38 10.2956410 -4.7288889
39 -0.5851111 10.2956410
40 -6.4903931 -0.5851111
41 7.7797949 -6.4903931
42 -14.3288889 7.7797949
43 -4.2534189 -14.3288889
44 13.0465811 -4.2534189
45 8.4360170 13.0465811
46 1.3605470 8.4360170
47 -0.8043590 1.3605470
48 -7.5341710 -0.8043590
49 -6.0990770 -7.5341710
50 2.5658290 -6.0990770
51 0.2605470 2.5658290
52 -4.5745470 0.2605470
53 10.9552649 -4.5745470
54 -21.0990770 10.9552649
55 -6.1639830 -21.0990770
56 11.3360170 -6.1639830
57 3.7658290 11.3360170
58 6.5307350 3.7658290
59 0.1658290 6.5307350
60 -2.8639830 0.1658290
61 -1.1639830 -2.8639830
62 13.5009230 -1.1639830
63 -1.4341710 13.5009230
64 7.4956410 -1.4341710
65 11.7903590 7.4956410
66 -17.1394530 11.7903590
67 -2.1745470 -17.1394530
68 12.1254530 -2.1745470
69 13.6903590 12.1254530
70 9.9552649 13.6903590
71 -0.9447351 9.9552649
72 3.1903590 -0.9447351
73 2.4903590 3.1903590
74 15.8552649 2.4903590
75 3.2903590 15.8552649
76 6.0850769 3.2903590
77 13.3096069 6.0850769
78 -10.9851111 13.3096069
79 0.4447009 -10.9851111
80 8.3394188 0.4447009
81 18.2394188 8.3394188
82 9.1394188 18.2394188
83 -3.8903931 9.1394188
84 6.9447009 -3.8903931
85 8.7745129 6.9447009
86 5.3692308 8.7745129
87 12.3288548 5.3692308
88 3.7235727 12.3288548
89 11.0639488 3.7235727
90 -7.2149231 11.0639488
91 -3.1447351 -7.2149231
92 13.3148889 -3.1447351
93 11.4043248 13.3148889
94 -5.3009572 11.4043248
95 -9.9956752 -5.3009572
96 -12.2149231 -9.9956752
97 NA -12.2149231
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.8764273 -6.3062392
[2,] 5.0235727 -4.8764273
[3,] -8.7062392 5.0235727
[4,] -3.2062392 -8.7062392
[5,] 0.6884787 -3.2062392
[6,] -24.2413332 0.6884787
[7,] -10.2711452 -24.2413332
[8,] -3.4307692 -10.2711452
[9,] 5.9148889 -3.4307692
[10,] -1.1851111 5.9148889
[11,] -12.6500171 -1.1851111
[12,] -7.1500171 -12.6500171
[13,] -7.5202051 -7.1500171
[14,] 2.2447009 -7.5202051
[15,] -0.9254871 2.2447009
[16,] -2.2956752 -0.9254871
[17,] 0.2692308 -2.2956752
[18,] -17.4851111 0.2692308
[19,] -11.2500171 -17.4851111
[20,] 3.8201709 -11.2500171
[21,] 9.7903590 3.8201709
[22,] -0.9745470 9.7903590
[23,] -10.5394530 -0.9745470
[24,] -5.0043590 -10.5394530
[25,] -5.5394530 -5.0043590
[26,] 2.5903590 -5.5394530
[27,] -0.2447351 2.5903590
[28,] -5.2500171 -0.2447351
[29,] 1.1499829 -5.2500171
[30,] -15.0043590 1.1499829
[31,] -12.3692650 -15.0043590
[32,] 7.5307350 -12.3692650
[33,] 9.4307350 7.5307350
[34,] -3.6692650 9.4307350
[35,] -5.0990770 -3.6692650
[36,] -6.4937949 -5.0990770
[37,] -4.7288889 -6.4937949
[38,] 10.2956410 -4.7288889
[39,] -0.5851111 10.2956410
[40,] -6.4903931 -0.5851111
[41,] 7.7797949 -6.4903931
[42,] -14.3288889 7.7797949
[43,] -4.2534189 -14.3288889
[44,] 13.0465811 -4.2534189
[45,] 8.4360170 13.0465811
[46,] 1.3605470 8.4360170
[47,] -0.8043590 1.3605470
[48,] -7.5341710 -0.8043590
[49,] -6.0990770 -7.5341710
[50,] 2.5658290 -6.0990770
[51,] 0.2605470 2.5658290
[52,] -4.5745470 0.2605470
[53,] 10.9552649 -4.5745470
[54,] -21.0990770 10.9552649
[55,] -6.1639830 -21.0990770
[56,] 11.3360170 -6.1639830
[57,] 3.7658290 11.3360170
[58,] 6.5307350 3.7658290
[59,] 0.1658290 6.5307350
[60,] -2.8639830 0.1658290
[61,] -1.1639830 -2.8639830
[62,] 13.5009230 -1.1639830
[63,] -1.4341710 13.5009230
[64,] 7.4956410 -1.4341710
[65,] 11.7903590 7.4956410
[66,] -17.1394530 11.7903590
[67,] -2.1745470 -17.1394530
[68,] 12.1254530 -2.1745470
[69,] 13.6903590 12.1254530
[70,] 9.9552649 13.6903590
[71,] -0.9447351 9.9552649
[72,] 3.1903590 -0.9447351
[73,] 2.4903590 3.1903590
[74,] 15.8552649 2.4903590
[75,] 3.2903590 15.8552649
[76,] 6.0850769 3.2903590
[77,] 13.3096069 6.0850769
[78,] -10.9851111 13.3096069
[79,] 0.4447009 -10.9851111
[80,] 8.3394188 0.4447009
[81,] 18.2394188 8.3394188
[82,] 9.1394188 18.2394188
[83,] -3.8903931 9.1394188
[84,] 6.9447009 -3.8903931
[85,] 8.7745129 6.9447009
[86,] 5.3692308 8.7745129
[87,] 12.3288548 5.3692308
[88,] 3.7235727 12.3288548
[89,] 11.0639488 3.7235727
[90,] -7.2149231 11.0639488
[91,] -3.1447351 -7.2149231
[92,] 13.3148889 -3.1447351
[93,] 11.4043248 13.3148889
[94,] -5.3009572 11.4043248
[95,] -9.9956752 -5.3009572
[96,] -12.2149231 -9.9956752
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.8764273 -6.3062392
2 5.0235727 -4.8764273
3 -8.7062392 5.0235727
4 -3.2062392 -8.7062392
5 0.6884787 -3.2062392
6 -24.2413332 0.6884787
7 -10.2711452 -24.2413332
8 -3.4307692 -10.2711452
9 5.9148889 -3.4307692
10 -1.1851111 5.9148889
11 -12.6500171 -1.1851111
12 -7.1500171 -12.6500171
13 -7.5202051 -7.1500171
14 2.2447009 -7.5202051
15 -0.9254871 2.2447009
16 -2.2956752 -0.9254871
17 0.2692308 -2.2956752
18 -17.4851111 0.2692308
19 -11.2500171 -17.4851111
20 3.8201709 -11.2500171
21 9.7903590 3.8201709
22 -0.9745470 9.7903590
23 -10.5394530 -0.9745470
24 -5.0043590 -10.5394530
25 -5.5394530 -5.0043590
26 2.5903590 -5.5394530
27 -0.2447351 2.5903590
28 -5.2500171 -0.2447351
29 1.1499829 -5.2500171
30 -15.0043590 1.1499829
31 -12.3692650 -15.0043590
32 7.5307350 -12.3692650
33 9.4307350 7.5307350
34 -3.6692650 9.4307350
35 -5.0990770 -3.6692650
36 -6.4937949 -5.0990770
37 -4.7288889 -6.4937949
38 10.2956410 -4.7288889
39 -0.5851111 10.2956410
40 -6.4903931 -0.5851111
41 7.7797949 -6.4903931
42 -14.3288889 7.7797949
43 -4.2534189 -14.3288889
44 13.0465811 -4.2534189
45 8.4360170 13.0465811
46 1.3605470 8.4360170
47 -0.8043590 1.3605470
48 -7.5341710 -0.8043590
49 -6.0990770 -7.5341710
50 2.5658290 -6.0990770
51 0.2605470 2.5658290
52 -4.5745470 0.2605470
53 10.9552649 -4.5745470
54 -21.0990770 10.9552649
55 -6.1639830 -21.0990770
56 11.3360170 -6.1639830
57 3.7658290 11.3360170
58 6.5307350 3.7658290
59 0.1658290 6.5307350
60 -2.8639830 0.1658290
61 -1.1639830 -2.8639830
62 13.5009230 -1.1639830
63 -1.4341710 13.5009230
64 7.4956410 -1.4341710
65 11.7903590 7.4956410
66 -17.1394530 11.7903590
67 -2.1745470 -17.1394530
68 12.1254530 -2.1745470
69 13.6903590 12.1254530
70 9.9552649 13.6903590
71 -0.9447351 9.9552649
72 3.1903590 -0.9447351
73 2.4903590 3.1903590
74 15.8552649 2.4903590
75 3.2903590 15.8552649
76 6.0850769 3.2903590
77 13.3096069 6.0850769
78 -10.9851111 13.3096069
79 0.4447009 -10.9851111
80 8.3394188 0.4447009
81 18.2394188 8.3394188
82 9.1394188 18.2394188
83 -3.8903931 9.1394188
84 6.9447009 -3.8903931
85 8.7745129 6.9447009
86 5.3692308 8.7745129
87 12.3288548 5.3692308
88 3.7235727 12.3288548
89 11.0639488 3.7235727
90 -7.2149231 11.0639488
91 -3.1447351 -7.2149231
92 13.3148889 -3.1447351
93 11.4043248 13.3148889
94 -5.3009572 11.4043248
95 -9.9956752 -5.3009572
96 -12.2149231 -9.9956752
> 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/rcomp/tmp/7kv1x1258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kawt1258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ybu61258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104lhv1258646894.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11hy1t1258646894.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/rcomp/tmp/12echo1258646894.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/rcomp/tmp/13nvmh1258646894.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/rcomp/tmp/14xdmu1258646894.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/rcomp/tmp/15ilex1258646894.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/rcomp/tmp/166gqu1258646894.tab")
+ }
>
> system("convert tmp/1694v1258646894.ps tmp/1694v1258646894.png")
> system("convert tmp/22mr91258646894.ps tmp/22mr91258646894.png")
> system("convert tmp/33gpu1258646894.ps tmp/33gpu1258646894.png")
> system("convert tmp/4ww511258646894.ps tmp/4ww511258646894.png")
> system("convert tmp/5j59q1258646894.ps tmp/5j59q1258646894.png")
> system("convert tmp/67awd1258646894.ps tmp/67awd1258646894.png")
> system("convert tmp/7kv1x1258646894.ps tmp/7kv1x1258646894.png")
> system("convert tmp/8kawt1258646894.ps tmp/8kawt1258646894.png")
> system("convert tmp/9ybu61258646894.ps tmp/9ybu61258646894.png")
> system("convert tmp/104lhv1258646894.ps tmp/104lhv1258646894.png")
>
>
> proc.time()
user system elapsed
2.845 1.597 3.224