R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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.
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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(27951,29781,32914,33488,35652,36488,35387,35676,34844,32447,31068,29010,29812,30951,32974,32936,34012,32946,31948,30599,27691,25073,23406,22248,22896,25317,26558,26471,27543,26198,24725,25005,23462,20780,19815,19761,21454,23899,24939,23580,24562,24696,23785,23812,21917,19713,19282,18788,21453,24482,27474,27264,27349,30632,29429,30084,26290,24379,23335,21346,21106,24514,28353,30805,31348,34556,33855,34787,32529,29998,29257,28155,30466,35704,39327,39351,42234,43630,43722,43121,37985,37135,34646,33026,35087,38846,42013,43908,42868,44423,44167,43636,44382,42142,43452,36912,42413,45344,44873,47510,49554,47369,45998,48140,48441,44928,40454,38661,37246,36843,36424,37594,38144,38737,34560,36080,33508,35462,33374,32110,35533,35532,37903,36763,40399,44164,44496,43110,43880),dim=c(1,129),dimnames=list(c('Y'),1:129))
> y <- array(NA,dim=c(1,129),dimnames=list(c('Y'),1:129))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 27951 1 0 0 0 0 0 0 0 0 0 0 1
2 29781 0 1 0 0 0 0 0 0 0 0 0 2
3 32914 0 0 1 0 0 0 0 0 0 0 0 3
4 33488 0 0 0 1 0 0 0 0 0 0 0 4
5 35652 0 0 0 0 1 0 0 0 0 0 0 5
6 36488 0 0 0 0 0 1 0 0 0 0 0 6
7 35387 0 0 0 0 0 0 1 0 0 0 0 7
8 35676 0 0 0 0 0 0 0 1 0 0 0 8
9 34844 0 0 0 0 0 0 0 0 1 0 0 9
10 32447 0 0 0 0 0 0 0 0 0 1 0 10
11 31068 0 0 0 0 0 0 0 0 0 0 1 11
12 29010 0 0 0 0 0 0 0 0 0 0 0 12
13 29812 1 0 0 0 0 0 0 0 0 0 0 13
14 30951 0 1 0 0 0 0 0 0 0 0 0 14
15 32974 0 0 1 0 0 0 0 0 0 0 0 15
16 32936 0 0 0 1 0 0 0 0 0 0 0 16
17 34012 0 0 0 0 1 0 0 0 0 0 0 17
18 32946 0 0 0 0 0 1 0 0 0 0 0 18
19 31948 0 0 0 0 0 0 1 0 0 0 0 19
20 30599 0 0 0 0 0 0 0 1 0 0 0 20
21 27691 0 0 0 0 0 0 0 0 1 0 0 21
22 25073 0 0 0 0 0 0 0 0 0 1 0 22
23 23406 0 0 0 0 0 0 0 0 0 0 1 23
24 22248 0 0 0 0 0 0 0 0 0 0 0 24
25 22896 1 0 0 0 0 0 0 0 0 0 0 25
26 25317 0 1 0 0 0 0 0 0 0 0 0 26
27 26558 0 0 1 0 0 0 0 0 0 0 0 27
28 26471 0 0 0 1 0 0 0 0 0 0 0 28
29 27543 0 0 0 0 1 0 0 0 0 0 0 29
30 26198 0 0 0 0 0 1 0 0 0 0 0 30
31 24725 0 0 0 0 0 0 1 0 0 0 0 31
32 25005 0 0 0 0 0 0 0 1 0 0 0 32
33 23462 0 0 0 0 0 0 0 0 1 0 0 33
34 20780 0 0 0 0 0 0 0 0 0 1 0 34
35 19815 0 0 0 0 0 0 0 0 0 0 1 35
36 19761 0 0 0 0 0 0 0 0 0 0 0 36
37 21454 1 0 0 0 0 0 0 0 0 0 0 37
38 23899 0 1 0 0 0 0 0 0 0 0 0 38
39 24939 0 0 1 0 0 0 0 0 0 0 0 39
40 23580 0 0 0 1 0 0 0 0 0 0 0 40
41 24562 0 0 0 0 1 0 0 0 0 0 0 41
42 24696 0 0 0 0 0 1 0 0 0 0 0 42
43 23785 0 0 0 0 0 0 1 0 0 0 0 43
44 23812 0 0 0 0 0 0 0 1 0 0 0 44
45 21917 0 0 0 0 0 0 0 0 1 0 0 45
46 19713 0 0 0 0 0 0 0 0 0 1 0 46
47 19282 0 0 0 0 0 0 0 0 0 0 1 47
48 18788 0 0 0 0 0 0 0 0 0 0 0 48
49 21453 1 0 0 0 0 0 0 0 0 0 0 49
50 24482 0 1 0 0 0 0 0 0 0 0 0 50
51 27474 0 0 1 0 0 0 0 0 0 0 0 51
52 27264 0 0 0 1 0 0 0 0 0 0 0 52
53 27349 0 0 0 0 1 0 0 0 0 0 0 53
54 30632 0 0 0 0 0 1 0 0 0 0 0 54
55 29429 0 0 0 0 0 0 1 0 0 0 0 55
56 30084 0 0 0 0 0 0 0 1 0 0 0 56
57 26290 0 0 0 0 0 0 0 0 1 0 0 57
58 24379 0 0 0 0 0 0 0 0 0 1 0 58
59 23335 0 0 0 0 0 0 0 0 0 0 1 59
60 21346 0 0 0 0 0 0 0 0 0 0 0 60
61 21106 1 0 0 0 0 0 0 0 0 0 0 61
62 24514 0 1 0 0 0 0 0 0 0 0 0 62
63 28353 0 0 1 0 0 0 0 0 0 0 0 63
64 30805 0 0 0 1 0 0 0 0 0 0 0 64
65 31348 0 0 0 0 1 0 0 0 0 0 0 65
66 34556 0 0 0 0 0 1 0 0 0 0 0 66
67 33855 0 0 0 0 0 0 1 0 0 0 0 67
68 34787 0 0 0 0 0 0 0 1 0 0 0 68
69 32529 0 0 0 0 0 0 0 0 1 0 0 69
70 29998 0 0 0 0 0 0 0 0 0 1 0 70
71 29257 0 0 0 0 0 0 0 0 0 0 1 71
72 28155 0 0 0 0 0 0 0 0 0 0 0 72
73 30466 1 0 0 0 0 0 0 0 0 0 0 73
74 35704 0 1 0 0 0 0 0 0 0 0 0 74
75 39327 0 0 1 0 0 0 0 0 0 0 0 75
76 39351 0 0 0 1 0 0 0 0 0 0 0 76
77 42234 0 0 0 0 1 0 0 0 0 0 0 77
78 43630 0 0 0 0 0 1 0 0 0 0 0 78
79 43722 0 0 0 0 0 0 1 0 0 0 0 79
80 43121 0 0 0 0 0 0 0 1 0 0 0 80
81 37985 0 0 0 0 0 0 0 0 1 0 0 81
82 37135 0 0 0 0 0 0 0 0 0 1 0 82
83 34646 0 0 0 0 0 0 0 0 0 0 1 83
84 33026 0 0 0 0 0 0 0 0 0 0 0 84
85 35087 1 0 0 0 0 0 0 0 0 0 0 85
86 38846 0 1 0 0 0 0 0 0 0 0 0 86
87 42013 0 0 1 0 0 0 0 0 0 0 0 87
88 43908 0 0 0 1 0 0 0 0 0 0 0 88
89 42868 0 0 0 0 1 0 0 0 0 0 0 89
90 44423 0 0 0 0 0 1 0 0 0 0 0 90
91 44167 0 0 0 0 0 0 1 0 0 0 0 91
92 43636 0 0 0 0 0 0 0 1 0 0 0 92
93 44382 0 0 0 0 0 0 0 0 1 0 0 93
94 42142 0 0 0 0 0 0 0 0 0 1 0 94
95 43452 0 0 0 0 0 0 0 0 0 0 1 95
96 36912 0 0 0 0 0 0 0 0 0 0 0 96
97 42413 1 0 0 0 0 0 0 0 0 0 0 97
98 45344 0 1 0 0 0 0 0 0 0 0 0 98
99 44873 0 0 1 0 0 0 0 0 0 0 0 99
100 47510 0 0 0 1 0 0 0 0 0 0 0 100
101 49554 0 0 0 0 1 0 0 0 0 0 0 101
102 47369 0 0 0 0 0 1 0 0 0 0 0 102
103 45998 0 0 0 0 0 0 1 0 0 0 0 103
104 48140 0 0 0 0 0 0 0 1 0 0 0 104
105 48441 0 0 0 0 0 0 0 0 1 0 0 105
106 44928 0 0 0 0 0 0 0 0 0 1 0 106
107 40454 0 0 0 0 0 0 0 0 0 0 1 107
108 38661 0 0 0 0 0 0 0 0 0 0 0 108
109 37246 1 0 0 0 0 0 0 0 0 0 0 109
110 36843 0 1 0 0 0 0 0 0 0 0 0 110
111 36424 0 0 1 0 0 0 0 0 0 0 0 111
112 37594 0 0 0 1 0 0 0 0 0 0 0 112
113 38144 0 0 0 0 1 0 0 0 0 0 0 113
114 38737 0 0 0 0 0 1 0 0 0 0 0 114
115 34560 0 0 0 0 0 0 1 0 0 0 0 115
116 36080 0 0 0 0 0 0 0 1 0 0 0 116
117 33508 0 0 0 0 0 0 0 0 1 0 0 117
118 35462 0 0 0 0 0 0 0 0 0 1 0 118
119 33374 0 0 0 0 0 0 0 0 0 0 1 119
120 32110 0 0 0 0 0 0 0 0 0 0 0 120
121 35533 1 0 0 0 0 0 0 0 0 0 0 121
122 35532 0 1 0 0 0 0 0 0 0 0 0 122
123 37903 0 0 1 0 0 0 0 0 0 0 0 123
124 36763 0 0 0 1 0 0 0 0 0 0 0 124
125 40399 0 0 0 0 1 0 0 0 0 0 0 125
126 44164 0 0 0 0 0 1 0 0 0 0 0 126
127 44496 0 0 0 0 0 0 1 0 0 0 0 127
128 43110 0 0 0 0 0 0 0 1 0 0 0 128
129 43880 0 0 0 0 0 0 0 0 1 0 0 129
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
19301.7 2240.8 4454.0 6371.2 6777.4 7917.8
M6 M7 M8 M9 M10 M11
8710.9 7509.4 7557.4 5687.3 3467.6 1939.0
t
131.8
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9120.0 -4921.6 -699.2 5323.8 9688.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 19301.68 2068.55 9.331 8.77e-16 ***
M1 2240.76 2563.01 0.874 0.383779
M2 4454.03 2562.67 1.738 0.084857 .
M3 6371.21 2562.41 2.486 0.014327 *
M4 6777.39 2562.22 2.645 0.009298 **
M5 7917.85 2562.11 3.090 0.002503 **
M6 8710.94 2562.07 3.400 0.000925 ***
M7 7509.39 2562.11 2.931 0.004071 **
M8 7557.39 2562.22 2.950 0.003850 **
M9 5687.30 2562.41 2.220 0.028397 *
M10 3467.64 2622.51 1.322 0.188683
M11 1939.02 2622.40 0.739 0.461154
t 131.82 13.89 9.490 3.73e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5864 on 116 degrees of freedom
Multiple R-squared: 0.5049, Adjusted R-squared: 0.4537
F-statistic: 9.859 on 12 and 116 DF, p-value: 4.906e-13
> postscript(file="/var/www/html/rcomp/tmp/14jnv1291111772.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/www/html/rcomp/tmp/2fbmg1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3fbmg1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4fbmg1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fbmg1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 129
Frequency = 1
1 2 3 4 5 6
6276.74949 5761.65859 6845.65859 6881.65859 7773.38586 7684.47677
7 8 9 10 11 12
7653.20404 7762.38586 8668.65859 8359.50182 8377.30182 8126.50182
13 14 15 16 17 18
6555.92687 5349.83596 5323.83596 4747.83596 4551.56323 2560.65414
19 20 21 22 23 24
2632.38141 1103.56323 -66.16404 -596.32081 -866.52081 -217.32081
25 26 27 28 29 30
-1941.89576 -1865.98667 -2673.98667 -3298.98667 -3499.25939 -5769.16848
31 32 33 34 35 36
-6172.44121 -6072.25939 -5876.98667 -6471.14343 -6039.34343 -4286.14343
37 38 39 40 41 42
-4965.71838 -4865.80929 -5874.80929 -7771.80929 -8062.08202 -8852.99111
43 44 45 46 47 48
-8694.26384 -8847.08202 -9003.80929 -9119.96606 -8154.16606 -6840.96606
49 50 51 52 53 54
-6548.54101 -5864.63192 -4921.63192 -5669.63192 -6856.90465 -4498.81374
55 56 57 58 59 60
-4632.08646 -4156.90465 -6212.63192 -6035.78869 -5682.98869 -5864.78869
61 62 63 64 65 66
-8477.36364 -7414.45455 -5624.45455 -3710.45455 -4439.72727 -2156.63636
67 68 69 70 71 72
-1787.90909 -1035.72727 -1555.45455 -1998.61131 -1342.81131 -637.61131
73 74 75 76 77 78
-699.18626 2193.72283 3767.72283 3253.72283 4864.45010 5335.54101
79 80 81 82 83 84
6497.26828 5716.45010 2318.72283 3556.56606 2464.36606 2651.56606
85 86 87 88 89 90
2339.99111 3753.90020 4871.90020 6228.90020 3916.62747 4546.71838
91 92 93 94 95 96
5360.44566 4649.62747 7133.90020 6981.74343 9688.54343 4955.74343
97 98 99 100 101 102
8084.16848 8670.07758 6150.07758 8249.07758 9020.80485 5910.89576
103 104 105 106 107 108
5609.62303 7571.80485 9611.07758 8185.92081 5108.72081 5122.92081
109 110 111 112 113 114
1335.34586 -1412.74505 -3880.74505 -3248.74505 -3971.01778 -4302.92687
115 116 117 118 119 120
-7410.19960 -6070.01778 -6903.74505 -2861.90182 -3553.10182 -3009.90182
121 122 123 124 125 126
-1959.47677 -4305.56768 -3983.56768 -5661.56768 -3297.84040 -457.74949
127 128 129
943.97778 -621.84040 1886.43232
> postscript(file="/var/www/html/rcomp/tmp/6qk3j1291111772.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 = 129
Frequency = 1
lag(myerror, k = 1) myerror
0 6276.74949 NA
1 5761.65859 6276.74949
2 6845.65859 5761.65859
3 6881.65859 6845.65859
4 7773.38586 6881.65859
5 7684.47677 7773.38586
6 7653.20404 7684.47677
7 7762.38586 7653.20404
8 8668.65859 7762.38586
9 8359.50182 8668.65859
10 8377.30182 8359.50182
11 8126.50182 8377.30182
12 6555.92687 8126.50182
13 5349.83596 6555.92687
14 5323.83596 5349.83596
15 4747.83596 5323.83596
16 4551.56323 4747.83596
17 2560.65414 4551.56323
18 2632.38141 2560.65414
19 1103.56323 2632.38141
20 -66.16404 1103.56323
21 -596.32081 -66.16404
22 -866.52081 -596.32081
23 -217.32081 -866.52081
24 -1941.89576 -217.32081
25 -1865.98667 -1941.89576
26 -2673.98667 -1865.98667
27 -3298.98667 -2673.98667
28 -3499.25939 -3298.98667
29 -5769.16848 -3499.25939
30 -6172.44121 -5769.16848
31 -6072.25939 -6172.44121
32 -5876.98667 -6072.25939
33 -6471.14343 -5876.98667
34 -6039.34343 -6471.14343
35 -4286.14343 -6039.34343
36 -4965.71838 -4286.14343
37 -4865.80929 -4965.71838
38 -5874.80929 -4865.80929
39 -7771.80929 -5874.80929
40 -8062.08202 -7771.80929
41 -8852.99111 -8062.08202
42 -8694.26384 -8852.99111
43 -8847.08202 -8694.26384
44 -9003.80929 -8847.08202
45 -9119.96606 -9003.80929
46 -8154.16606 -9119.96606
47 -6840.96606 -8154.16606
48 -6548.54101 -6840.96606
49 -5864.63192 -6548.54101
50 -4921.63192 -5864.63192
51 -5669.63192 -4921.63192
52 -6856.90465 -5669.63192
53 -4498.81374 -6856.90465
54 -4632.08646 -4498.81374
55 -4156.90465 -4632.08646
56 -6212.63192 -4156.90465
57 -6035.78869 -6212.63192
58 -5682.98869 -6035.78869
59 -5864.78869 -5682.98869
60 -8477.36364 -5864.78869
61 -7414.45455 -8477.36364
62 -5624.45455 -7414.45455
63 -3710.45455 -5624.45455
64 -4439.72727 -3710.45455
65 -2156.63636 -4439.72727
66 -1787.90909 -2156.63636
67 -1035.72727 -1787.90909
68 -1555.45455 -1035.72727
69 -1998.61131 -1555.45455
70 -1342.81131 -1998.61131
71 -637.61131 -1342.81131
72 -699.18626 -637.61131
73 2193.72283 -699.18626
74 3767.72283 2193.72283
75 3253.72283 3767.72283
76 4864.45010 3253.72283
77 5335.54101 4864.45010
78 6497.26828 5335.54101
79 5716.45010 6497.26828
80 2318.72283 5716.45010
81 3556.56606 2318.72283
82 2464.36606 3556.56606
83 2651.56606 2464.36606
84 2339.99111 2651.56606
85 3753.90020 2339.99111
86 4871.90020 3753.90020
87 6228.90020 4871.90020
88 3916.62747 6228.90020
89 4546.71838 3916.62747
90 5360.44566 4546.71838
91 4649.62747 5360.44566
92 7133.90020 4649.62747
93 6981.74343 7133.90020
94 9688.54343 6981.74343
95 4955.74343 9688.54343
96 8084.16848 4955.74343
97 8670.07758 8084.16848
98 6150.07758 8670.07758
99 8249.07758 6150.07758
100 9020.80485 8249.07758
101 5910.89576 9020.80485
102 5609.62303 5910.89576
103 7571.80485 5609.62303
104 9611.07758 7571.80485
105 8185.92081 9611.07758
106 5108.72081 8185.92081
107 5122.92081 5108.72081
108 1335.34586 5122.92081
109 -1412.74505 1335.34586
110 -3880.74505 -1412.74505
111 -3248.74505 -3880.74505
112 -3971.01778 -3248.74505
113 -4302.92687 -3971.01778
114 -7410.19960 -4302.92687
115 -6070.01778 -7410.19960
116 -6903.74505 -6070.01778
117 -2861.90182 -6903.74505
118 -3553.10182 -2861.90182
119 -3009.90182 -3553.10182
120 -1959.47677 -3009.90182
121 -4305.56768 -1959.47677
122 -3983.56768 -4305.56768
123 -5661.56768 -3983.56768
124 -3297.84040 -5661.56768
125 -457.74949 -3297.84040
126 943.97778 -457.74949
127 -621.84040 943.97778
128 1886.43232 -621.84040
129 NA 1886.43232
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 5761.65859 6276.74949
[2,] 6845.65859 5761.65859
[3,] 6881.65859 6845.65859
[4,] 7773.38586 6881.65859
[5,] 7684.47677 7773.38586
[6,] 7653.20404 7684.47677
[7,] 7762.38586 7653.20404
[8,] 8668.65859 7762.38586
[9,] 8359.50182 8668.65859
[10,] 8377.30182 8359.50182
[11,] 8126.50182 8377.30182
[12,] 6555.92687 8126.50182
[13,] 5349.83596 6555.92687
[14,] 5323.83596 5349.83596
[15,] 4747.83596 5323.83596
[16,] 4551.56323 4747.83596
[17,] 2560.65414 4551.56323
[18,] 2632.38141 2560.65414
[19,] 1103.56323 2632.38141
[20,] -66.16404 1103.56323
[21,] -596.32081 -66.16404
[22,] -866.52081 -596.32081
[23,] -217.32081 -866.52081
[24,] -1941.89576 -217.32081
[25,] -1865.98667 -1941.89576
[26,] -2673.98667 -1865.98667
[27,] -3298.98667 -2673.98667
[28,] -3499.25939 -3298.98667
[29,] -5769.16848 -3499.25939
[30,] -6172.44121 -5769.16848
[31,] -6072.25939 -6172.44121
[32,] -5876.98667 -6072.25939
[33,] -6471.14343 -5876.98667
[34,] -6039.34343 -6471.14343
[35,] -4286.14343 -6039.34343
[36,] -4965.71838 -4286.14343
[37,] -4865.80929 -4965.71838
[38,] -5874.80929 -4865.80929
[39,] -7771.80929 -5874.80929
[40,] -8062.08202 -7771.80929
[41,] -8852.99111 -8062.08202
[42,] -8694.26384 -8852.99111
[43,] -8847.08202 -8694.26384
[44,] -9003.80929 -8847.08202
[45,] -9119.96606 -9003.80929
[46,] -8154.16606 -9119.96606
[47,] -6840.96606 -8154.16606
[48,] -6548.54101 -6840.96606
[49,] -5864.63192 -6548.54101
[50,] -4921.63192 -5864.63192
[51,] -5669.63192 -4921.63192
[52,] -6856.90465 -5669.63192
[53,] -4498.81374 -6856.90465
[54,] -4632.08646 -4498.81374
[55,] -4156.90465 -4632.08646
[56,] -6212.63192 -4156.90465
[57,] -6035.78869 -6212.63192
[58,] -5682.98869 -6035.78869
[59,] -5864.78869 -5682.98869
[60,] -8477.36364 -5864.78869
[61,] -7414.45455 -8477.36364
[62,] -5624.45455 -7414.45455
[63,] -3710.45455 -5624.45455
[64,] -4439.72727 -3710.45455
[65,] -2156.63636 -4439.72727
[66,] -1787.90909 -2156.63636
[67,] -1035.72727 -1787.90909
[68,] -1555.45455 -1035.72727
[69,] -1998.61131 -1555.45455
[70,] -1342.81131 -1998.61131
[71,] -637.61131 -1342.81131
[72,] -699.18626 -637.61131
[73,] 2193.72283 -699.18626
[74,] 3767.72283 2193.72283
[75,] 3253.72283 3767.72283
[76,] 4864.45010 3253.72283
[77,] 5335.54101 4864.45010
[78,] 6497.26828 5335.54101
[79,] 5716.45010 6497.26828
[80,] 2318.72283 5716.45010
[81,] 3556.56606 2318.72283
[82,] 2464.36606 3556.56606
[83,] 2651.56606 2464.36606
[84,] 2339.99111 2651.56606
[85,] 3753.90020 2339.99111
[86,] 4871.90020 3753.90020
[87,] 6228.90020 4871.90020
[88,] 3916.62747 6228.90020
[89,] 4546.71838 3916.62747
[90,] 5360.44566 4546.71838
[91,] 4649.62747 5360.44566
[92,] 7133.90020 4649.62747
[93,] 6981.74343 7133.90020
[94,] 9688.54343 6981.74343
[95,] 4955.74343 9688.54343
[96,] 8084.16848 4955.74343
[97,] 8670.07758 8084.16848
[98,] 6150.07758 8670.07758
[99,] 8249.07758 6150.07758
[100,] 9020.80485 8249.07758
[101,] 5910.89576 9020.80485
[102,] 5609.62303 5910.89576
[103,] 7571.80485 5609.62303
[104,] 9611.07758 7571.80485
[105,] 8185.92081 9611.07758
[106,] 5108.72081 8185.92081
[107,] 5122.92081 5108.72081
[108,] 1335.34586 5122.92081
[109,] -1412.74505 1335.34586
[110,] -3880.74505 -1412.74505
[111,] -3248.74505 -3880.74505
[112,] -3971.01778 -3248.74505
[113,] -4302.92687 -3971.01778
[114,] -7410.19960 -4302.92687
[115,] -6070.01778 -7410.19960
[116,] -6903.74505 -6070.01778
[117,] -2861.90182 -6903.74505
[118,] -3553.10182 -2861.90182
[119,] -3009.90182 -3553.10182
[120,] -1959.47677 -3009.90182
[121,] -4305.56768 -1959.47677
[122,] -3983.56768 -4305.56768
[123,] -5661.56768 -3983.56768
[124,] -3297.84040 -5661.56768
[125,] -457.74949 -3297.84040
[126,] 943.97778 -457.74949
[127,] -621.84040 943.97778
[128,] 1886.43232 -621.84040
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 5761.65859 6276.74949
2 6845.65859 5761.65859
3 6881.65859 6845.65859
4 7773.38586 6881.65859
5 7684.47677 7773.38586
6 7653.20404 7684.47677
7 7762.38586 7653.20404
8 8668.65859 7762.38586
9 8359.50182 8668.65859
10 8377.30182 8359.50182
11 8126.50182 8377.30182
12 6555.92687 8126.50182
13 5349.83596 6555.92687
14 5323.83596 5349.83596
15 4747.83596 5323.83596
16 4551.56323 4747.83596
17 2560.65414 4551.56323
18 2632.38141 2560.65414
19 1103.56323 2632.38141
20 -66.16404 1103.56323
21 -596.32081 -66.16404
22 -866.52081 -596.32081
23 -217.32081 -866.52081
24 -1941.89576 -217.32081
25 -1865.98667 -1941.89576
26 -2673.98667 -1865.98667
27 -3298.98667 -2673.98667
28 -3499.25939 -3298.98667
29 -5769.16848 -3499.25939
30 -6172.44121 -5769.16848
31 -6072.25939 -6172.44121
32 -5876.98667 -6072.25939
33 -6471.14343 -5876.98667
34 -6039.34343 -6471.14343
35 -4286.14343 -6039.34343
36 -4965.71838 -4286.14343
37 -4865.80929 -4965.71838
38 -5874.80929 -4865.80929
39 -7771.80929 -5874.80929
40 -8062.08202 -7771.80929
41 -8852.99111 -8062.08202
42 -8694.26384 -8852.99111
43 -8847.08202 -8694.26384
44 -9003.80929 -8847.08202
45 -9119.96606 -9003.80929
46 -8154.16606 -9119.96606
47 -6840.96606 -8154.16606
48 -6548.54101 -6840.96606
49 -5864.63192 -6548.54101
50 -4921.63192 -5864.63192
51 -5669.63192 -4921.63192
52 -6856.90465 -5669.63192
53 -4498.81374 -6856.90465
54 -4632.08646 -4498.81374
55 -4156.90465 -4632.08646
56 -6212.63192 -4156.90465
57 -6035.78869 -6212.63192
58 -5682.98869 -6035.78869
59 -5864.78869 -5682.98869
60 -8477.36364 -5864.78869
61 -7414.45455 -8477.36364
62 -5624.45455 -7414.45455
63 -3710.45455 -5624.45455
64 -4439.72727 -3710.45455
65 -2156.63636 -4439.72727
66 -1787.90909 -2156.63636
67 -1035.72727 -1787.90909
68 -1555.45455 -1035.72727
69 -1998.61131 -1555.45455
70 -1342.81131 -1998.61131
71 -637.61131 -1342.81131
72 -699.18626 -637.61131
73 2193.72283 -699.18626
74 3767.72283 2193.72283
75 3253.72283 3767.72283
76 4864.45010 3253.72283
77 5335.54101 4864.45010
78 6497.26828 5335.54101
79 5716.45010 6497.26828
80 2318.72283 5716.45010
81 3556.56606 2318.72283
82 2464.36606 3556.56606
83 2651.56606 2464.36606
84 2339.99111 2651.56606
85 3753.90020 2339.99111
86 4871.90020 3753.90020
87 6228.90020 4871.90020
88 3916.62747 6228.90020
89 4546.71838 3916.62747
90 5360.44566 4546.71838
91 4649.62747 5360.44566
92 7133.90020 4649.62747
93 6981.74343 7133.90020
94 9688.54343 6981.74343
95 4955.74343 9688.54343
96 8084.16848 4955.74343
97 8670.07758 8084.16848
98 6150.07758 8670.07758
99 8249.07758 6150.07758
100 9020.80485 8249.07758
101 5910.89576 9020.80485
102 5609.62303 5910.89576
103 7571.80485 5609.62303
104 9611.07758 7571.80485
105 8185.92081 9611.07758
106 5108.72081 8185.92081
107 5122.92081 5108.72081
108 1335.34586 5122.92081
109 -1412.74505 1335.34586
110 -3880.74505 -1412.74505
111 -3248.74505 -3880.74505
112 -3971.01778 -3248.74505
113 -4302.92687 -3971.01778
114 -7410.19960 -4302.92687
115 -6070.01778 -7410.19960
116 -6903.74505 -6070.01778
117 -2861.90182 -6903.74505
118 -3553.10182 -2861.90182
119 -3009.90182 -3553.10182
120 -1959.47677 -3009.90182
121 -4305.56768 -1959.47677
122 -3983.56768 -4305.56768
123 -5661.56768 -3983.56768
124 -3297.84040 -5661.56768
125 -457.74949 -3297.84040
126 943.97778 -457.74949
127 -621.84040 943.97778
128 1886.43232 -621.84040
> 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/7jblm1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8jblm1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9jblm1291111772.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10fliu1291111772.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/11n76p1291111772.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/12evxr1291111772.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/130wvx1291111772.tab")
>
> try(system("convert tmp/14jnv1291111772.ps tmp/14jnv1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fbmg1291111772.ps tmp/2fbmg1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fbmg1291111772.ps tmp/3fbmg1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fbmg1291111772.ps tmp/4fbmg1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fbmg1291111772.ps tmp/5fbmg1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qk3j1291111772.ps tmp/6qk3j1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jblm1291111772.ps tmp/7jblm1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/8jblm1291111772.ps tmp/8jblm1291111772.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jblm1291111772.ps tmp/9jblm1291111772.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.251 1.526 7.738