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(101.02,0,100.67,0,100.47,0,100.38,0,100.33,0,100.34,0,100.37,0,100.39,0,100.21,0,100.21,0,100.22,0,100.28,0,100.25,0,100.25,0,100.21,0,100.16,0,100.18,0,100.1,1,99.96,1,99.88,1,99.88,1,99.86,1,99.84,1,99.8,1,99.82,1,99.81,1,99.92,1,100.03,1,99.99,1,100.02,1,100.01,1,100.13,1,100.33,1,100.13,1,99.96,1,100.05,1,99.83,1,99.8,1,100.01,1,100.1,1,100.13,1,100.16,1,100.41,1,101.34,1,101.65,1,101.85,1,102.07,1,102.12,1,102.14,1,102.21,1,102.28,1,102.19,1,102.33,1,102.54,1,102.44,1,102.78,1,102.9,1,103.08,1,102.77,1,102.65,1,102.71,1,103.29,1,102.86,1,103.45,1,103.72,1,103.65,1,103.83,1,104.45,1,105.14,1,105.07,1,105.31,1,105.19,1,105.3,1,105.02,1,105.17,1,105.28,1,105.45,1,105.38,1,105.8,1,105.96,1,105.08,1,105.11,1,105.61,1,105.5,1),dim=c(2,84),dimnames=list(c('Suiker','dummie'),1:84))
> y <- array(NA,dim=c(2,84),dimnames=list(c('Suiker','dummie'),1:84))
> 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 = '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
Suiker dummie t
1 101.02 0 1
2 100.67 0 2
3 100.47 0 3
4 100.38 0 4
5 100.33 0 5
6 100.34 0 6
7 100.37 0 7
8 100.39 0 8
9 100.21 0 9
10 100.21 0 10
11 100.22 0 11
12 100.28 0 12
13 100.25 0 13
14 100.25 0 14
15 100.21 0 15
16 100.16 0 16
17 100.18 0 17
18 100.10 1 18
19 99.96 1 19
20 99.88 1 20
21 99.88 1 21
22 99.86 1 22
23 99.84 1 23
24 99.80 1 24
25 99.82 1 25
26 99.81 1 26
27 99.92 1 27
28 100.03 1 28
29 99.99 1 29
30 100.02 1 30
31 100.01 1 31
32 100.13 1 32
33 100.33 1 33
34 100.13 1 34
35 99.96 1 35
36 100.05 1 36
37 99.83 1 37
38 99.80 1 38
39 100.01 1 39
40 100.10 1 40
41 100.13 1 41
42 100.16 1 42
43 100.41 1 43
44 101.34 1 44
45 101.65 1 45
46 101.85 1 46
47 102.07 1 47
48 102.12 1 48
49 102.14 1 49
50 102.21 1 50
51 102.28 1 51
52 102.19 1 52
53 102.33 1 53
54 102.54 1 54
55 102.44 1 55
56 102.78 1 56
57 102.90 1 57
58 103.08 1 58
59 102.77 1 59
60 102.65 1 60
61 102.71 1 61
62 103.29 1 62
63 102.86 1 63
64 103.45 1 64
65 103.72 1 65
66 103.65 1 66
67 103.83 1 67
68 104.45 1 68
69 105.14 1 69
70 105.07 1 70
71 105.31 1 71
72 105.19 1 72
73 105.30 1 73
74 105.02 1 74
75 105.17 1 75
76 105.28 1 76
77 105.45 1 77
78 105.38 1 78
79 105.80 1 79
80 105.96 1 80
81 105.08 1 81
82 105.11 1 82
83 105.61 1 83
84 105.50 1 84
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummie t
99.4133 -2.4401 0.1040
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.18191 -0.33813 -0.00306 0.39581 1.50273
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 99.413258 0.148892 667.69 <2e-16 ***
dummie -2.440071 0.226128 -10.79 <2e-16 ***
t 0.104017 0.003747 27.76 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5979 on 81 degrees of freedom
Multiple R-squared: 0.9184, Adjusted R-squared: 0.9164
F-statistic: 455.9 on 2 and 81 DF, p-value: < 2.2e-16
> 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,] 2.876379e-02 5.752757e-02 0.971236215
[2,] 1.667953e-02 3.335906e-02 0.983320468
[3,] 9.490063e-03 1.898013e-02 0.990509937
[4,] 2.813173e-03 5.626347e-03 0.997186827
[5,] 8.732973e-04 1.746595e-03 0.999126703
[6,] 3.054685e-04 6.109370e-04 0.999694532
[7,] 1.584050e-04 3.168101e-04 0.999841595
[8,] 6.500955e-05 1.300191e-04 0.999934990
[9,] 2.646557e-05 5.293114e-05 0.999973534
[10,] 8.801875e-06 1.760375e-05 0.999991198
[11,] 2.473181e-06 4.946361e-06 0.999997527
[12,] 7.745136e-07 1.549027e-06 0.999999225
[13,] 3.522650e-07 7.045301e-07 0.999999648
[14,] 1.736665e-07 3.473330e-07 0.999999826
[15,] 8.543680e-08 1.708736e-07 0.999999915
[16,] 3.712060e-08 7.424120e-08 0.999999963
[17,] 1.563057e-08 3.126113e-08 0.999999984
[18,] 6.375724e-09 1.275145e-08 0.999999994
[19,] 2.417524e-09 4.835048e-09 0.999999998
[20,] 9.674022e-10 1.934804e-09 0.999999999
[21,] 3.838435e-10 7.676870e-10 1.000000000
[22,] 4.579808e-10 9.159617e-10 1.000000000
[23,] 2.331248e-09 4.662496e-09 0.999999998
[24,] 4.098174e-09 8.196348e-09 0.999999996
[25,] 7.753050e-09 1.550610e-08 0.999999992
[26,] 9.618474e-09 1.923695e-08 0.999999990
[27,] 3.192081e-08 6.384162e-08 0.999999968
[28,] 5.653841e-07 1.130768e-06 0.999999435
[29,] 5.224414e-07 1.044883e-06 0.999999478
[30,] 2.124448e-07 4.248896e-07 0.999999788
[31,] 1.039007e-07 2.078014e-07 0.999999896
[32,] 4.923634e-08 9.847267e-08 0.999999951
[33,] 3.085062e-08 6.170123e-08 0.999999969
[34,] 2.081734e-08 4.163469e-08 0.999999979
[35,] 2.294610e-08 4.589220e-08 0.999999977
[36,] 3.917901e-08 7.835801e-08 0.999999961
[37,] 1.291991e-07 2.583982e-07 0.999999871
[38,] 1.717229e-06 3.434459e-06 0.999998283
[39,] 4.368521e-03 8.737042e-03 0.995631479
[40,] 1.068426e-01 2.136851e-01 0.893157445
[41,] 3.675584e-01 7.351167e-01 0.632441642
[42,] 6.399730e-01 7.200539e-01 0.360026954
[43,] 7.760407e-01 4.479185e-01 0.223959269
[44,] 8.318128e-01 3.363743e-01 0.168187170
[45,] 8.578206e-01 2.843588e-01 0.142179388
[46,] 8.671117e-01 2.657766e-01 0.132888281
[47,] 8.515678e-01 2.968644e-01 0.148432210
[48,] 8.339866e-01 3.320269e-01 0.166013433
[49,] 8.204841e-01 3.590318e-01 0.179515881
[50,] 7.888440e-01 4.223120e-01 0.211156005
[51,] 7.676712e-01 4.646577e-01 0.232328848
[52,] 7.420416e-01 5.159169e-01 0.257958429
[53,] 7.200622e-01 5.598757e-01 0.279937847
[54,] 6.722201e-01 6.555599e-01 0.327779934
[55,] 6.601166e-01 6.797669e-01 0.339883448
[56,] 6.888462e-01 6.223076e-01 0.311153807
[57,] 6.586375e-01 6.827249e-01 0.341362461
[58,] 7.892704e-01 4.214593e-01 0.210729648
[59,] 8.235060e-01 3.529879e-01 0.176493963
[60,] 8.494255e-01 3.011491e-01 0.150574533
[61,] 9.366124e-01 1.267753e-01 0.063387632
[62,] 9.931289e-01 1.374214e-02 0.006871069
[63,] 9.979323e-01 4.135327e-03 0.002067663
[64,] 9.972292e-01 5.541558e-03 0.002770779
[65,] 9.955683e-01 8.863357e-03 0.004431678
[66,] 9.929338e-01 1.413231e-02 0.007066153
[67,] 9.863408e-01 2.731836e-02 0.013659181
[68,] 9.742154e-01 5.156925e-02 0.025784626
[69,] 9.591691e-01 8.166179e-02 0.040830895
[70,] 9.316230e-01 1.367539e-01 0.068376964
[71,] 8.851638e-01 2.296723e-01 0.114836171
[72,] 7.940126e-01 4.119748e-01 0.205987385
[73,] 6.870590e-01 6.258820e-01 0.312940997
> postscript(file="/var/www/html/rcomp/tmp/1s7zc1229968685.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2v42k1229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vz731229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4kac51229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5wkgz1229968685.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 = 84
Frequency = 1
1 2 3 4 5
1.5027252022 1.0487080814 0.7446909605 0.5506738396 0.3966567188
6 7 8 9 10
0.3026395979 0.2286224770 0.1446053562 -0.1394117647 -0.2434288856
11 12 13 14 15
-0.3374460064 -0.3814631273 -0.5154802482 -0.6194973690 -0.7635144899
16 17 18 19 20
-0.9175316108 -1.0015487316 1.2545052871 1.0104881663 0.8264710454
21 22 23 24 25
0.7224539245 0.5984368037 0.4744196828 0.3304025619 0.2463854411
26 27 28 29 30
0.1323683202 0.1383511993 0.1443340784 0.0003169576 -0.0737001633
31 32 33 34 35
-0.1877172842 -0.1717344050 -0.0757515259 -0.3797686468 -0.6537857676
36 37 38 39 40
-0.6678028885 -0.9918200094 -1.1258371302 -1.0198542511 -1.0338713720
41 42 43 44 45
-1.1078884928 -1.1819056137 -1.0359227346 -0.2099398554 -0.0039569763
46 47 48 49 50
0.0920259028 0.2080087820 0.1539916611 0.0699745402 0.0359574194
51 52 53 54 55
0.0019402985 -0.1920768224 -0.1560939432 -0.0501110641 -0.2541281850
56 57 58 59 60
-0.0181453058 -0.0021624267 0.0738204524 -0.3401966684 -0.5642137893
61 62 63 64 65
-0.6082309102 -0.1322480310 -0.6662651519 -0.1802822728 -0.0142993936
66 67 68 69 70
-0.1883165145 -0.1123336354 0.4036492438 0.9896321229 0.8156150020
71 72 73 74 75
0.9515978812 0.7275807603 0.7335636394 0.3495465186 0.3955293977
76 77 78 79 80
0.4015122768 0.4674951560 0.2934780351 0.6094609142 0.6654437934
81 82 83 84
-0.3185733275 -0.3925904484 0.0033924308 -0.2106246901
> postscript(file="/var/www/html/rcomp/tmp/61myn1229968685.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 = 84
Frequency = 1
lag(myerror, k = 1) myerror
0 1.5027252022 NA
1 1.0487080814 1.5027252022
2 0.7446909605 1.0487080814
3 0.5506738396 0.7446909605
4 0.3966567188 0.5506738396
5 0.3026395979 0.3966567188
6 0.2286224770 0.3026395979
7 0.1446053562 0.2286224770
8 -0.1394117647 0.1446053562
9 -0.2434288856 -0.1394117647
10 -0.3374460064 -0.2434288856
11 -0.3814631273 -0.3374460064
12 -0.5154802482 -0.3814631273
13 -0.6194973690 -0.5154802482
14 -0.7635144899 -0.6194973690
15 -0.9175316108 -0.7635144899
16 -1.0015487316 -0.9175316108
17 1.2545052871 -1.0015487316
18 1.0104881663 1.2545052871
19 0.8264710454 1.0104881663
20 0.7224539245 0.8264710454
21 0.5984368037 0.7224539245
22 0.4744196828 0.5984368037
23 0.3304025619 0.4744196828
24 0.2463854411 0.3304025619
25 0.1323683202 0.2463854411
26 0.1383511993 0.1323683202
27 0.1443340784 0.1383511993
28 0.0003169576 0.1443340784
29 -0.0737001633 0.0003169576
30 -0.1877172842 -0.0737001633
31 -0.1717344050 -0.1877172842
32 -0.0757515259 -0.1717344050
33 -0.3797686468 -0.0757515259
34 -0.6537857676 -0.3797686468
35 -0.6678028885 -0.6537857676
36 -0.9918200094 -0.6678028885
37 -1.1258371302 -0.9918200094
38 -1.0198542511 -1.1258371302
39 -1.0338713720 -1.0198542511
40 -1.1078884928 -1.0338713720
41 -1.1819056137 -1.1078884928
42 -1.0359227346 -1.1819056137
43 -0.2099398554 -1.0359227346
44 -0.0039569763 -0.2099398554
45 0.0920259028 -0.0039569763
46 0.2080087820 0.0920259028
47 0.1539916611 0.2080087820
48 0.0699745402 0.1539916611
49 0.0359574194 0.0699745402
50 0.0019402985 0.0359574194
51 -0.1920768224 0.0019402985
52 -0.1560939432 -0.1920768224
53 -0.0501110641 -0.1560939432
54 -0.2541281850 -0.0501110641
55 -0.0181453058 -0.2541281850
56 -0.0021624267 -0.0181453058
57 0.0738204524 -0.0021624267
58 -0.3401966684 0.0738204524
59 -0.5642137893 -0.3401966684
60 -0.6082309102 -0.5642137893
61 -0.1322480310 -0.6082309102
62 -0.6662651519 -0.1322480310
63 -0.1802822728 -0.6662651519
64 -0.0142993936 -0.1802822728
65 -0.1883165145 -0.0142993936
66 -0.1123336354 -0.1883165145
67 0.4036492438 -0.1123336354
68 0.9896321229 0.4036492438
69 0.8156150020 0.9896321229
70 0.9515978812 0.8156150020
71 0.7275807603 0.9515978812
72 0.7335636394 0.7275807603
73 0.3495465186 0.7335636394
74 0.3955293977 0.3495465186
75 0.4015122768 0.3955293977
76 0.4674951560 0.4015122768
77 0.2934780351 0.4674951560
78 0.6094609142 0.2934780351
79 0.6654437934 0.6094609142
80 -0.3185733275 0.6654437934
81 -0.3925904484 -0.3185733275
82 0.0033924308 -0.3925904484
83 -0.2106246901 0.0033924308
84 NA -0.2106246901
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.0487080814 1.5027252022
[2,] 0.7446909605 1.0487080814
[3,] 0.5506738396 0.7446909605
[4,] 0.3966567188 0.5506738396
[5,] 0.3026395979 0.3966567188
[6,] 0.2286224770 0.3026395979
[7,] 0.1446053562 0.2286224770
[8,] -0.1394117647 0.1446053562
[9,] -0.2434288856 -0.1394117647
[10,] -0.3374460064 -0.2434288856
[11,] -0.3814631273 -0.3374460064
[12,] -0.5154802482 -0.3814631273
[13,] -0.6194973690 -0.5154802482
[14,] -0.7635144899 -0.6194973690
[15,] -0.9175316108 -0.7635144899
[16,] -1.0015487316 -0.9175316108
[17,] 1.2545052871 -1.0015487316
[18,] 1.0104881663 1.2545052871
[19,] 0.8264710454 1.0104881663
[20,] 0.7224539245 0.8264710454
[21,] 0.5984368037 0.7224539245
[22,] 0.4744196828 0.5984368037
[23,] 0.3304025619 0.4744196828
[24,] 0.2463854411 0.3304025619
[25,] 0.1323683202 0.2463854411
[26,] 0.1383511993 0.1323683202
[27,] 0.1443340784 0.1383511993
[28,] 0.0003169576 0.1443340784
[29,] -0.0737001633 0.0003169576
[30,] -0.1877172842 -0.0737001633
[31,] -0.1717344050 -0.1877172842
[32,] -0.0757515259 -0.1717344050
[33,] -0.3797686468 -0.0757515259
[34,] -0.6537857676 -0.3797686468
[35,] -0.6678028885 -0.6537857676
[36,] -0.9918200094 -0.6678028885
[37,] -1.1258371302 -0.9918200094
[38,] -1.0198542511 -1.1258371302
[39,] -1.0338713720 -1.0198542511
[40,] -1.1078884928 -1.0338713720
[41,] -1.1819056137 -1.1078884928
[42,] -1.0359227346 -1.1819056137
[43,] -0.2099398554 -1.0359227346
[44,] -0.0039569763 -0.2099398554
[45,] 0.0920259028 -0.0039569763
[46,] 0.2080087820 0.0920259028
[47,] 0.1539916611 0.2080087820
[48,] 0.0699745402 0.1539916611
[49,] 0.0359574194 0.0699745402
[50,] 0.0019402985 0.0359574194
[51,] -0.1920768224 0.0019402985
[52,] -0.1560939432 -0.1920768224
[53,] -0.0501110641 -0.1560939432
[54,] -0.2541281850 -0.0501110641
[55,] -0.0181453058 -0.2541281850
[56,] -0.0021624267 -0.0181453058
[57,] 0.0738204524 -0.0021624267
[58,] -0.3401966684 0.0738204524
[59,] -0.5642137893 -0.3401966684
[60,] -0.6082309102 -0.5642137893
[61,] -0.1322480310 -0.6082309102
[62,] -0.6662651519 -0.1322480310
[63,] -0.1802822728 -0.6662651519
[64,] -0.0142993936 -0.1802822728
[65,] -0.1883165145 -0.0142993936
[66,] -0.1123336354 -0.1883165145
[67,] 0.4036492438 -0.1123336354
[68,] 0.9896321229 0.4036492438
[69,] 0.8156150020 0.9896321229
[70,] 0.9515978812 0.8156150020
[71,] 0.7275807603 0.9515978812
[72,] 0.7335636394 0.7275807603
[73,] 0.3495465186 0.7335636394
[74,] 0.3955293977 0.3495465186
[75,] 0.4015122768 0.3955293977
[76,] 0.4674951560 0.4015122768
[77,] 0.2934780351 0.4674951560
[78,] 0.6094609142 0.2934780351
[79,] 0.6654437934 0.6094609142
[80,] -0.3185733275 0.6654437934
[81,] -0.3925904484 -0.3185733275
[82,] 0.0033924308 -0.3925904484
[83,] -0.2106246901 0.0033924308
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.0487080814 1.5027252022
2 0.7446909605 1.0487080814
3 0.5506738396 0.7446909605
4 0.3966567188 0.5506738396
5 0.3026395979 0.3966567188
6 0.2286224770 0.3026395979
7 0.1446053562 0.2286224770
8 -0.1394117647 0.1446053562
9 -0.2434288856 -0.1394117647
10 -0.3374460064 -0.2434288856
11 -0.3814631273 -0.3374460064
12 -0.5154802482 -0.3814631273
13 -0.6194973690 -0.5154802482
14 -0.7635144899 -0.6194973690
15 -0.9175316108 -0.7635144899
16 -1.0015487316 -0.9175316108
17 1.2545052871 -1.0015487316
18 1.0104881663 1.2545052871
19 0.8264710454 1.0104881663
20 0.7224539245 0.8264710454
21 0.5984368037 0.7224539245
22 0.4744196828 0.5984368037
23 0.3304025619 0.4744196828
24 0.2463854411 0.3304025619
25 0.1323683202 0.2463854411
26 0.1383511993 0.1323683202
27 0.1443340784 0.1383511993
28 0.0003169576 0.1443340784
29 -0.0737001633 0.0003169576
30 -0.1877172842 -0.0737001633
31 -0.1717344050 -0.1877172842
32 -0.0757515259 -0.1717344050
33 -0.3797686468 -0.0757515259
34 -0.6537857676 -0.3797686468
35 -0.6678028885 -0.6537857676
36 -0.9918200094 -0.6678028885
37 -1.1258371302 -0.9918200094
38 -1.0198542511 -1.1258371302
39 -1.0338713720 -1.0198542511
40 -1.1078884928 -1.0338713720
41 -1.1819056137 -1.1078884928
42 -1.0359227346 -1.1819056137
43 -0.2099398554 -1.0359227346
44 -0.0039569763 -0.2099398554
45 0.0920259028 -0.0039569763
46 0.2080087820 0.0920259028
47 0.1539916611 0.2080087820
48 0.0699745402 0.1539916611
49 0.0359574194 0.0699745402
50 0.0019402985 0.0359574194
51 -0.1920768224 0.0019402985
52 -0.1560939432 -0.1920768224
53 -0.0501110641 -0.1560939432
54 -0.2541281850 -0.0501110641
55 -0.0181453058 -0.2541281850
56 -0.0021624267 -0.0181453058
57 0.0738204524 -0.0021624267
58 -0.3401966684 0.0738204524
59 -0.5642137893 -0.3401966684
60 -0.6082309102 -0.5642137893
61 -0.1322480310 -0.6082309102
62 -0.6662651519 -0.1322480310
63 -0.1802822728 -0.6662651519
64 -0.0142993936 -0.1802822728
65 -0.1883165145 -0.0142993936
66 -0.1123336354 -0.1883165145
67 0.4036492438 -0.1123336354
68 0.9896321229 0.4036492438
69 0.8156150020 0.9896321229
70 0.9515978812 0.8156150020
71 0.7275807603 0.9515978812
72 0.7335636394 0.7275807603
73 0.3495465186 0.7335636394
74 0.3955293977 0.3495465186
75 0.4015122768 0.3955293977
76 0.4674951560 0.4015122768
77 0.2934780351 0.4674951560
78 0.6094609142 0.2934780351
79 0.6654437934 0.6094609142
80 -0.3185733275 0.6654437934
81 -0.3925904484 -0.3185733275
82 0.0033924308 -0.3925904484
83 -0.2106246901 0.0033924308
> 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/7rgjd1229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kc4w1229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91x2y1229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10vv021229968685.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wc1c1229968685.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/1257mg1229968686.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/13dbsd1229968686.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/14qr941229968686.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/15r4z71229968686.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/16q3xu1229968686.tab")
+ }
>
> system("convert tmp/1s7zc1229968685.ps tmp/1s7zc1229968685.png")
> system("convert tmp/2v42k1229968685.ps tmp/2v42k1229968685.png")
> system("convert tmp/3vz731229968685.ps tmp/3vz731229968685.png")
> system("convert tmp/4kac51229968685.ps tmp/4kac51229968685.png")
> system("convert tmp/5wkgz1229968685.ps tmp/5wkgz1229968685.png")
> system("convert tmp/61myn1229968685.ps tmp/61myn1229968685.png")
> system("convert tmp/7rgjd1229968685.ps tmp/7rgjd1229968685.png")
> system("convert tmp/8kc4w1229968685.ps tmp/8kc4w1229968685.png")
> system("convert tmp/91x2y1229968685.ps tmp/91x2y1229968685.png")
> system("convert tmp/10vv021229968685.ps tmp/10vv021229968685.png")
>
>
> proc.time()
user system elapsed
2.883 1.639 6.310