R version 2.6.1 (2007-11-26)
Copyright (C) 2007 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(106
+ ,87
+ ,1
+ ,65.3
+ ,2.2
+ ,70
+ ,1
+ ,65.73
+ ,62.3
+ ,75
+ ,1
+ ,69.44
+ ,14.7
+ ,79
+ ,1
+ ,73.74
+ ,5
+ ,64.5
+ ,1
+ ,74.31
+ ,74.4
+ ,75
+ ,0
+ ,70.53
+ ,66.1
+ ,70
+ ,0
+ ,69.42
+ ,22
+ ,67
+ ,1
+ ,69.77
+ ,3.4
+ ,52
+ ,0
+ ,65.47
+ ,0.3
+ ,67.2
+ ,1
+ ,66.2
+ ,53.2
+ ,47
+ ,0
+ ,70.46
+ ,0
+ ,46.4
+ ,0
+ ,74.44
+ ,57.2
+ ,76
+ ,0
+ ,69.28
+ ,9.2
+ ,71.6
+ ,1
+ ,67.67
+ ,15.9
+ ,63.8
+ ,1
+ ,67.22
+ ,17.6
+ ,48.2
+ ,1
+ ,64.85
+ ,21
+ ,64.5
+ ,1
+ ,71.35
+ ,7.6
+ ,75.9
+ ,1
+ ,72.28
+ ,71.6
+ ,80
+ ,1
+ ,71.87
+ ,12.9
+ ,56
+ ,1
+ ,67.34
+ ,10.5
+ ,75.5
+ ,0
+ ,73.5
+ ,25.7
+ ,77
+ ,1
+ ,64.91
+ ,26.8
+ ,88
+ ,0
+ ,68.13
+ ,7.3
+ ,48
+ ,0
+ ,72.5
+ ,17.1
+ ,73
+ ,1
+ ,72.36
+ ,27.3
+ ,72
+ ,1
+ ,70.59
+ ,16.5
+ ,64
+ ,1
+ ,74.76
+ ,5.4
+ ,76
+ ,0
+ ,65.63
+ ,5.6
+ ,67.4
+ ,1
+ ,67.04
+ ,36.5
+ ,73.7
+ ,1
+ ,66.72
+ ,1.1
+ ,59.2
+ ,0
+ ,65.8
+ ,3.9
+ ,53
+ ,0
+ ,72.44
+ ,34.2
+ ,41.9
+ ,1
+ ,71.83
+ ,40.3
+ ,65.5
+ ,1
+ ,72.67
+ ,15.6
+ ,63
+ ,1
+ ,69.56
+ ,15.5
+ ,54
+ ,0
+ ,67
+ ,52.9
+ ,77.7
+ ,0
+ ,68.86
+ ,1.6
+ ,47.6
+ ,0
+ ,71.25
+ ,14.2
+ ,53.1
+ ,1
+ ,69.88
+ ,7.5
+ ,55.5
+ ,1
+ ,67.18
+ ,2
+ ,64
+ ,1
+ ,67.47
+ ,71.4
+ ,75.6
+ ,1
+ ,73.2
+ ,3.2
+ ,57
+ ,0
+ ,69.6
+ ,20
+ ,63
+ ,0
+ ,71.24
+ ,2.8
+ ,59.5
+ ,1
+ ,73.83
+ ,15.3
+ ,84.5
+ ,1
+ ,66.07
+ ,8
+ ,59.9
+ ,0
+ ,70.68
+ ,36.6
+ ,60
+ ,1
+ ,74.01
+ ,3.8
+ ,64
+ ,0
+ ,68.53
+ ,25.5
+ ,54
+ ,0
+ ,66.72
+ ,3.2
+ ,53.8
+ ,0
+ ,72.69
+ ,33.1
+ ,84
+ ,1
+ ,67.46
+ ,42
+ ,63.2
+ ,0
+ ,73.81
+ ,16.2
+ ,54.3
+ ,1
+ ,72.96
+ ,0
+ ,60
+ ,0
+ ,71.65
+ ,22.7
+ ,68
+ ,1
+ ,72.79
+ ,36.4
+ ,74
+ ,1
+ ,73.83
+ ,69
+ ,74
+ ,1
+ ,66.74
+ ,11.2
+ ,68.5
+ ,1
+ ,65.62
+ ,12.5
+ ,76
+ ,0
+ ,66.18
+ ,51.7
+ ,83
+ ,0
+ ,67.78
+ ,3.6
+ ,62.5
+ ,0
+ ,68.84
+ ,22.2
+ ,57
+ ,1
+ ,65.27
+ ,39.2
+ ,85
+ ,1
+ ,72.84
+ ,27.9
+ ,50
+ ,1
+ ,75.36
+ ,58.8
+ ,53
+ ,1
+ ,76.88
+ ,1
+ ,57
+ ,0
+ ,76.51
+ ,4.7
+ ,46
+ ,1
+ ,80.63
+ ,25.6
+ ,65.4
+ ,1
+ ,75.27
+ ,5.3
+ ,71.4
+ ,1
+ ,81.19
+ ,38.7
+ ,41
+ ,1
+ ,81.3
+ ,31.6
+ ,66
+ ,1
+ ,77.77
+ ,19.3
+ ,69.5
+ ,1
+ ,75.51
+ ,26.5
+ ,59
+ ,1
+ ,78.64
+ ,12.8
+ ,80
+ ,1
+ ,80.68
+ ,18.3
+ ,72
+ ,1
+ ,77.4
+ ,13.2
+ ,73
+ ,0
+ ,80.71
+ ,36
+ ,66.4
+ ,0
+ ,83.16
+ ,34.1
+ ,37
+ ,0
+ ,87.99
+ ,71.5
+ ,70
+ ,1
+ ,72.21
+ ,43.3
+ ,75
+ ,1
+ ,70.24
+ ,47.7
+ ,54
+ ,1
+ ,66.06
+ ,74.9
+ ,76.2
+ ,1
+ ,68.67
+ ,0.9
+ ,74.9
+ ,1
+ ,68.77
+ ,35.9
+ ,98
+ ,1
+ ,68.07
+ ,45.8
+ ,86.5
+ ,0
+ ,67.33
+ ,54.2
+ ,72.8
+ ,1
+ ,69.47
+ ,34
+ ,65
+ ,1
+ ,70.81
+ ,7.9
+ ,50
+ ,1
+ ,73.17
+ ,54.5
+ ,81
+ ,1
+ ,71.28
+ ,8.2
+ ,52
+ ,0
+ ,69.47
+ ,49.3
+ ,68
+ ,1
+ ,65.31
+ ,46.9
+ ,58.5
+ ,1
+ ,70.23
+ ,16.8
+ ,65.5
+ ,1
+ ,73.23
+ ,2.8
+ ,62.5
+ ,0
+ ,68.67
+ ,60.9
+ ,64
+ ,1
+ ,72.66
+ ,5.6
+ ,55.7
+ ,0
+ ,74.79
+ ,6.6
+ ,84
+ ,1
+ ,73.04
+ ,22.9
+ ,63.7
+ ,1
+ ,69.95
+ ,51.1
+ ,65
+ ,0
+ ,67.51
+ ,23.3
+ ,87.5
+ ,0
+ ,67.5
+ ,11.5
+ ,79
+ ,1
+ ,71.32
+ ,79.1
+ ,58.5
+ ,0
+ ,71.23
+ ,53.6
+ ,75
+ ,1
+ ,67.49
+ ,1.5
+ ,52.5
+ ,0
+ ,68.62
+ ,40.4
+ ,57.5
+ ,1
+ ,72.53
+ ,25.4
+ ,70
+ ,1
+ ,66.67
+ ,6.7
+ ,72
+ ,1
+ ,66.19
+ ,76
+ ,88
+ ,1
+ ,78.4
+ ,0.6
+ ,58
+ ,1
+ ,75.67
+ ,43.4
+ ,73
+ ,1
+ ,76.07
+ ,13
+ ,56
+ ,1
+ ,82.88
+ ,27.8
+ ,49
+ ,0
+ ,77.14
+ ,6.5
+ ,54.7
+ ,0
+ ,77.31
+ ,7.1
+ ,67
+ ,1
+ ,76.58
+ ,6
+ ,47
+ ,0
+ ,82.86
+ ,6.5
+ ,47
+ ,0
+ ,76.64)
+ ,dim=c(4
+ ,117)
+ ,dimnames=list(c('y'
+ ,'weight'
+ ,'sex'
+ ,'age')
+ ,1:117))
> y <- array(NA,dim=c(4,117),dimnames=list(c('y','weight','sex','age'),1:117))
> 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)
> 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 weight sex age
1 106.0 87.0 1 65.30
2 2.2 70.0 1 65.73
3 62.3 75.0 1 69.44
4 14.7 79.0 1 73.74
5 5.0 64.5 1 74.31
6 74.4 75.0 0 70.53
7 66.1 70.0 0 69.42
8 22.0 67.0 1 69.77
9 3.4 52.0 0 65.47
10 0.3 67.2 1 66.20
11 53.2 47.0 0 70.46
12 0.0 46.4 0 74.44
13 57.2 76.0 0 69.28
14 9.2 71.6 1 67.67
15 15.9 63.8 1 67.22
16 17.6 48.2 1 64.85
17 21.0 64.5 1 71.35
18 7.6 75.9 1 72.28
19 71.6 80.0 1 71.87
20 12.9 56.0 1 67.34
21 10.5 75.5 0 73.50
22 25.7 77.0 1 64.91
23 26.8 88.0 0 68.13
24 7.3 48.0 0 72.50
25 17.1 73.0 1 72.36
26 27.3 72.0 1 70.59
27 16.5 64.0 1 74.76
28 5.4 76.0 0 65.63
29 5.6 67.4 1 67.04
30 36.5 73.7 1 66.72
31 1.1 59.2 0 65.80
32 3.9 53.0 0 72.44
33 34.2 41.9 1 71.83
34 40.3 65.5 1 72.67
35 15.6 63.0 1 69.56
36 15.5 54.0 0 67.00
37 52.9 77.7 0 68.86
38 1.6 47.6 0 71.25
39 14.2 53.1 1 69.88
40 7.5 55.5 1 67.18
41 2.0 64.0 1 67.47
42 71.4 75.6 1 73.20
43 3.2 57.0 0 69.60
44 20.0 63.0 0 71.24
45 2.8 59.5 1 73.83
46 15.3 84.5 1 66.07
47 8.0 59.9 0 70.68
48 36.6 60.0 1 74.01
49 3.8 64.0 0 68.53
50 25.5 54.0 0 66.72
51 3.2 53.8 0 72.69
52 33.1 84.0 1 67.46
53 42.0 63.2 0 73.81
54 16.2 54.3 1 72.96
55 0.0 60.0 0 71.65
56 22.7 68.0 1 72.79
57 36.4 74.0 1 73.83
58 69.0 74.0 1 66.74
59 11.2 68.5 1 65.62
60 12.5 76.0 0 66.18
61 51.7 83.0 0 67.78
62 3.6 62.5 0 68.84
63 22.2 57.0 1 65.27
64 39.2 85.0 1 72.84
65 27.9 50.0 1 75.36
66 58.8 53.0 1 76.88
67 1.0 57.0 0 76.51
68 4.7 46.0 1 80.63
69 25.6 65.4 1 75.27
70 5.3 71.4 1 81.19
71 38.7 41.0 1 81.30
72 31.6 66.0 1 77.77
73 19.3 69.5 1 75.51
74 26.5 59.0 1 78.64
75 12.8 80.0 1 80.68
76 18.3 72.0 1 77.40
77 13.2 73.0 0 80.71
78 36.0 66.4 0 83.16
79 34.1 37.0 0 87.99
80 71.5 70.0 1 72.21
81 43.3 75.0 1 70.24
82 47.7 54.0 1 66.06
83 74.9 76.2 1 68.67
84 0.9 74.9 1 68.77
85 35.9 98.0 1 68.07
86 45.8 86.5 0 67.33
87 54.2 72.8 1 69.47
88 34.0 65.0 1 70.81
89 7.9 50.0 1 73.17
90 54.5 81.0 1 71.28
91 8.2 52.0 0 69.47
92 49.3 68.0 1 65.31
93 46.9 58.5 1 70.23
94 16.8 65.5 1 73.23
95 2.8 62.5 0 68.67
96 60.9 64.0 1 72.66
97 5.6 55.7 0 74.79
98 6.6 84.0 1 73.04
99 22.9 63.7 1 69.95
100 51.1 65.0 0 67.51
101 23.3 87.5 0 67.50
102 11.5 79.0 1 71.32
103 79.1 58.5 0 71.23
104 53.6 75.0 1 67.49
105 1.5 52.5 0 68.62
106 40.4 57.5 1 72.53
107 25.4 70.0 1 66.67
108 6.7 72.0 1 66.19
109 76.0 88.0 1 78.40
110 0.6 58.0 1 75.67
111 43.4 73.0 1 76.07
112 13.0 56.0 1 82.88
113 27.8 49.0 0 77.14
114 6.5 54.7 0 77.31
115 7.1 67.0 1 76.58
116 6.0 47.0 0 82.86
117 6.5 47.0 0 76.64
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) weight sex age
-27.7994 0.6366 3.6297 0.1389
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-32.852 -15.254 -6.266 13.691 65.714
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -27.7994 37.1803 -0.748 0.456200
weight 0.6366 0.1813 3.511 0.000643 ***
sex 3.6297 4.3239 0.839 0.402993
age 0.1389 0.4483 0.310 0.757276
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21.76 on 113 degrees of freedom
Multiple R-Squared: 0.1241, Adjusted R-squared: 0.1008
F-statistic: 5.335 on 3 and 113 DF, p-value: 0.001787
> postscript(file="/var/www/html/rcomp/tmp/1cr6x1200395909.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/2hhaw1200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/33pg01200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lao71200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51ony1200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 117
Frequency = 1
1 2 3 4 5 6
65.7135034 -27.3234254 29.0781501 -21.6655798 -22.2135389 44.6564352
7 8 9 10 11 12
39.6937674 -6.1746030 -10.9982251 -27.5061225 41.2919292 -12.0788390
13 14 15 16 17 18
26.9934025 -21.6114713 -9.8832237 2.0774275 -5.8024492 -26.5892450
19 20 21 22 23 24
34.8574941 -7.9341387 -19.9743607 -8.1659855 -10.8865003 -5.5280241
25 26 27 28 29 30
-15.2541148 -4.1716596 -10.4577183 -24.2996795 -22.4501100 4.4835333
31 32 33 34 35 36
-17.9278260 -12.1028648 21.7188323 12.6775923 -9.9988990 -0.3839834
37 38 39 40 41 42
21.6694538 -10.7997682 -5.1406574 -12.9936003 -23.9452711 37.2739743
43 44 45 46 47 48
-14.9549799 -2.2025541 -21.1637021 -23.5018486 -12.1512127 12.2929819
49 50 51 52 53 54
-18.6628196 9.6549034 -13.3468930 -5.5765767 19.3131931 -4.3323745
55 56 57 58 59 60
-20.3495914 -6.5306603 3.2050944 36.7897653 -17.3531963 -17.2760644
61 62 63 64 65 66
17.2452819 -17.9509208 1.0167116 -0.8603947 9.7718389 38.5508346
67 68 69 70 71 72
-18.1146520 -11.6135285 -2.3198365 -27.2618242 25.4765944 2.9509785
73 74 75 76 77 78
-11.2633705 2.1865946 -25.1660532 -14.1174436 -16.6841105 9.9774186
79 80 81 82 83 84
26.1236812 41.0766216 9.9670448 28.3168993 41.0211273 -32.1651357
85 86 87 88 89 90
-11.7741807 9.1795571 22.3745801 6.9542295 -9.9240103 17.2027996
91 92 93 94 95 96
-6.7537516 21.1081744 24.0729066 -10.9001814 -18.7273109 34.2339332
97 98 99 100 101 102
-12.4481505 -32.8515363 -3.1987071 28.1422050 -13.9806875 -24.5294863
103 104 105 106 107 108
59.7636910 20.6489693 -13.6540196 17.8901135 -4.2539741 -24.1605804
109 110 111 112 113 114
33.2575192 -22.6642922 10.5306343 -9.9923594 13.6909303 -11.2614975
115 116 117
-22.0203870 -7.6302032 -6.2663594
> postscript(file="/var/www/html/rcomp/tmp/6ixnj1200395909.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 = 117
Frequency = 1
lag(myerror, k = 1) myerror
0 65.7135034 NA
1 -27.3234254 65.7135034
2 29.0781501 -27.3234254
3 -21.6655798 29.0781501
4 -22.2135389 -21.6655798
5 44.6564352 -22.2135389
6 39.6937674 44.6564352
7 -6.1746030 39.6937674
8 -10.9982251 -6.1746030
9 -27.5061225 -10.9982251
10 41.2919292 -27.5061225
11 -12.0788390 41.2919292
12 26.9934025 -12.0788390
13 -21.6114713 26.9934025
14 -9.8832237 -21.6114713
15 2.0774275 -9.8832237
16 -5.8024492 2.0774275
17 -26.5892450 -5.8024492
18 34.8574941 -26.5892450
19 -7.9341387 34.8574941
20 -19.9743607 -7.9341387
21 -8.1659855 -19.9743607
22 -10.8865003 -8.1659855
23 -5.5280241 -10.8865003
24 -15.2541148 -5.5280241
25 -4.1716596 -15.2541148
26 -10.4577183 -4.1716596
27 -24.2996795 -10.4577183
28 -22.4501100 -24.2996795
29 4.4835333 -22.4501100
30 -17.9278260 4.4835333
31 -12.1028648 -17.9278260
32 21.7188323 -12.1028648
33 12.6775923 21.7188323
34 -9.9988990 12.6775923
35 -0.3839834 -9.9988990
36 21.6694538 -0.3839834
37 -10.7997682 21.6694538
38 -5.1406574 -10.7997682
39 -12.9936003 -5.1406574
40 -23.9452711 -12.9936003
41 37.2739743 -23.9452711
42 -14.9549799 37.2739743
43 -2.2025541 -14.9549799
44 -21.1637021 -2.2025541
45 -23.5018486 -21.1637021
46 -12.1512127 -23.5018486
47 12.2929819 -12.1512127
48 -18.6628196 12.2929819
49 9.6549034 -18.6628196
50 -13.3468930 9.6549034
51 -5.5765767 -13.3468930
52 19.3131931 -5.5765767
53 -4.3323745 19.3131931
54 -20.3495914 -4.3323745
55 -6.5306603 -20.3495914
56 3.2050944 -6.5306603
57 36.7897653 3.2050944
58 -17.3531963 36.7897653
59 -17.2760644 -17.3531963
60 17.2452819 -17.2760644
61 -17.9509208 17.2452819
62 1.0167116 -17.9509208
63 -0.8603947 1.0167116
64 9.7718389 -0.8603947
65 38.5508346 9.7718389
66 -18.1146520 38.5508346
67 -11.6135285 -18.1146520
68 -2.3198365 -11.6135285
69 -27.2618242 -2.3198365
70 25.4765944 -27.2618242
71 2.9509785 25.4765944
72 -11.2633705 2.9509785
73 2.1865946 -11.2633705
74 -25.1660532 2.1865946
75 -14.1174436 -25.1660532
76 -16.6841105 -14.1174436
77 9.9774186 -16.6841105
78 26.1236812 9.9774186
79 41.0766216 26.1236812
80 9.9670448 41.0766216
81 28.3168993 9.9670448
82 41.0211273 28.3168993
83 -32.1651357 41.0211273
84 -11.7741807 -32.1651357
85 9.1795571 -11.7741807
86 22.3745801 9.1795571
87 6.9542295 22.3745801
88 -9.9240103 6.9542295
89 17.2027996 -9.9240103
90 -6.7537516 17.2027996
91 21.1081744 -6.7537516
92 24.0729066 21.1081744
93 -10.9001814 24.0729066
94 -18.7273109 -10.9001814
95 34.2339332 -18.7273109
96 -12.4481505 34.2339332
97 -32.8515363 -12.4481505
98 -3.1987071 -32.8515363
99 28.1422050 -3.1987071
100 -13.9806875 28.1422050
101 -24.5294863 -13.9806875
102 59.7636910 -24.5294863
103 20.6489693 59.7636910
104 -13.6540196 20.6489693
105 17.8901135 -13.6540196
106 -4.2539741 17.8901135
107 -24.1605804 -4.2539741
108 33.2575192 -24.1605804
109 -22.6642922 33.2575192
110 10.5306343 -22.6642922
111 -9.9923594 10.5306343
112 13.6909303 -9.9923594
113 -11.2614975 13.6909303
114 -22.0203870 -11.2614975
115 -7.6302032 -22.0203870
116 -6.2663594 -7.6302032
117 NA -6.2663594
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -27.3234254 65.7135034
[2,] 29.0781501 -27.3234254
[3,] -21.6655798 29.0781501
[4,] -22.2135389 -21.6655798
[5,] 44.6564352 -22.2135389
[6,] 39.6937674 44.6564352
[7,] -6.1746030 39.6937674
[8,] -10.9982251 -6.1746030
[9,] -27.5061225 -10.9982251
[10,] 41.2919292 -27.5061225
[11,] -12.0788390 41.2919292
[12,] 26.9934025 -12.0788390
[13,] -21.6114713 26.9934025
[14,] -9.8832237 -21.6114713
[15,] 2.0774275 -9.8832237
[16,] -5.8024492 2.0774275
[17,] -26.5892450 -5.8024492
[18,] 34.8574941 -26.5892450
[19,] -7.9341387 34.8574941
[20,] -19.9743607 -7.9341387
[21,] -8.1659855 -19.9743607
[22,] -10.8865003 -8.1659855
[23,] -5.5280241 -10.8865003
[24,] -15.2541148 -5.5280241
[25,] -4.1716596 -15.2541148
[26,] -10.4577183 -4.1716596
[27,] -24.2996795 -10.4577183
[28,] -22.4501100 -24.2996795
[29,] 4.4835333 -22.4501100
[30,] -17.9278260 4.4835333
[31,] -12.1028648 -17.9278260
[32,] 21.7188323 -12.1028648
[33,] 12.6775923 21.7188323
[34,] -9.9988990 12.6775923
[35,] -0.3839834 -9.9988990
[36,] 21.6694538 -0.3839834
[37,] -10.7997682 21.6694538
[38,] -5.1406574 -10.7997682
[39,] -12.9936003 -5.1406574
[40,] -23.9452711 -12.9936003
[41,] 37.2739743 -23.9452711
[42,] -14.9549799 37.2739743
[43,] -2.2025541 -14.9549799
[44,] -21.1637021 -2.2025541
[45,] -23.5018486 -21.1637021
[46,] -12.1512127 -23.5018486
[47,] 12.2929819 -12.1512127
[48,] -18.6628196 12.2929819
[49,] 9.6549034 -18.6628196
[50,] -13.3468930 9.6549034
[51,] -5.5765767 -13.3468930
[52,] 19.3131931 -5.5765767
[53,] -4.3323745 19.3131931
[54,] -20.3495914 -4.3323745
[55,] -6.5306603 -20.3495914
[56,] 3.2050944 -6.5306603
[57,] 36.7897653 3.2050944
[58,] -17.3531963 36.7897653
[59,] -17.2760644 -17.3531963
[60,] 17.2452819 -17.2760644
[61,] -17.9509208 17.2452819
[62,] 1.0167116 -17.9509208
[63,] -0.8603947 1.0167116
[64,] 9.7718389 -0.8603947
[65,] 38.5508346 9.7718389
[66,] -18.1146520 38.5508346
[67,] -11.6135285 -18.1146520
[68,] -2.3198365 -11.6135285
[69,] -27.2618242 -2.3198365
[70,] 25.4765944 -27.2618242
[71,] 2.9509785 25.4765944
[72,] -11.2633705 2.9509785
[73,] 2.1865946 -11.2633705
[74,] -25.1660532 2.1865946
[75,] -14.1174436 -25.1660532
[76,] -16.6841105 -14.1174436
[77,] 9.9774186 -16.6841105
[78,] 26.1236812 9.9774186
[79,] 41.0766216 26.1236812
[80,] 9.9670448 41.0766216
[81,] 28.3168993 9.9670448
[82,] 41.0211273 28.3168993
[83,] -32.1651357 41.0211273
[84,] -11.7741807 -32.1651357
[85,] 9.1795571 -11.7741807
[86,] 22.3745801 9.1795571
[87,] 6.9542295 22.3745801
[88,] -9.9240103 6.9542295
[89,] 17.2027996 -9.9240103
[90,] -6.7537516 17.2027996
[91,] 21.1081744 -6.7537516
[92,] 24.0729066 21.1081744
[93,] -10.9001814 24.0729066
[94,] -18.7273109 -10.9001814
[95,] 34.2339332 -18.7273109
[96,] -12.4481505 34.2339332
[97,] -32.8515363 -12.4481505
[98,] -3.1987071 -32.8515363
[99,] 28.1422050 -3.1987071
[100,] -13.9806875 28.1422050
[101,] -24.5294863 -13.9806875
[102,] 59.7636910 -24.5294863
[103,] 20.6489693 59.7636910
[104,] -13.6540196 20.6489693
[105,] 17.8901135 -13.6540196
[106,] -4.2539741 17.8901135
[107,] -24.1605804 -4.2539741
[108,] 33.2575192 -24.1605804
[109,] -22.6642922 33.2575192
[110,] 10.5306343 -22.6642922
[111,] -9.9923594 10.5306343
[112,] 13.6909303 -9.9923594
[113,] -11.2614975 13.6909303
[114,] -22.0203870 -11.2614975
[115,] -7.6302032 -22.0203870
[116,] -6.2663594 -7.6302032
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -27.3234254 65.7135034
2 29.0781501 -27.3234254
3 -21.6655798 29.0781501
4 -22.2135389 -21.6655798
5 44.6564352 -22.2135389
6 39.6937674 44.6564352
7 -6.1746030 39.6937674
8 -10.9982251 -6.1746030
9 -27.5061225 -10.9982251
10 41.2919292 -27.5061225
11 -12.0788390 41.2919292
12 26.9934025 -12.0788390
13 -21.6114713 26.9934025
14 -9.8832237 -21.6114713
15 2.0774275 -9.8832237
16 -5.8024492 2.0774275
17 -26.5892450 -5.8024492
18 34.8574941 -26.5892450
19 -7.9341387 34.8574941
20 -19.9743607 -7.9341387
21 -8.1659855 -19.9743607
22 -10.8865003 -8.1659855
23 -5.5280241 -10.8865003
24 -15.2541148 -5.5280241
25 -4.1716596 -15.2541148
26 -10.4577183 -4.1716596
27 -24.2996795 -10.4577183
28 -22.4501100 -24.2996795
29 4.4835333 -22.4501100
30 -17.9278260 4.4835333
31 -12.1028648 -17.9278260
32 21.7188323 -12.1028648
33 12.6775923 21.7188323
34 -9.9988990 12.6775923
35 -0.3839834 -9.9988990
36 21.6694538 -0.3839834
37 -10.7997682 21.6694538
38 -5.1406574 -10.7997682
39 -12.9936003 -5.1406574
40 -23.9452711 -12.9936003
41 37.2739743 -23.9452711
42 -14.9549799 37.2739743
43 -2.2025541 -14.9549799
44 -21.1637021 -2.2025541
45 -23.5018486 -21.1637021
46 -12.1512127 -23.5018486
47 12.2929819 -12.1512127
48 -18.6628196 12.2929819
49 9.6549034 -18.6628196
50 -13.3468930 9.6549034
51 -5.5765767 -13.3468930
52 19.3131931 -5.5765767
53 -4.3323745 19.3131931
54 -20.3495914 -4.3323745
55 -6.5306603 -20.3495914
56 3.2050944 -6.5306603
57 36.7897653 3.2050944
58 -17.3531963 36.7897653
59 -17.2760644 -17.3531963
60 17.2452819 -17.2760644
61 -17.9509208 17.2452819
62 1.0167116 -17.9509208
63 -0.8603947 1.0167116
64 9.7718389 -0.8603947
65 38.5508346 9.7718389
66 -18.1146520 38.5508346
67 -11.6135285 -18.1146520
68 -2.3198365 -11.6135285
69 -27.2618242 -2.3198365
70 25.4765944 -27.2618242
71 2.9509785 25.4765944
72 -11.2633705 2.9509785
73 2.1865946 -11.2633705
74 -25.1660532 2.1865946
75 -14.1174436 -25.1660532
76 -16.6841105 -14.1174436
77 9.9774186 -16.6841105
78 26.1236812 9.9774186
79 41.0766216 26.1236812
80 9.9670448 41.0766216
81 28.3168993 9.9670448
82 41.0211273 28.3168993
83 -32.1651357 41.0211273
84 -11.7741807 -32.1651357
85 9.1795571 -11.7741807
86 22.3745801 9.1795571
87 6.9542295 22.3745801
88 -9.9240103 6.9542295
89 17.2027996 -9.9240103
90 -6.7537516 17.2027996
91 21.1081744 -6.7537516
92 24.0729066 21.1081744
93 -10.9001814 24.0729066
94 -18.7273109 -10.9001814
95 34.2339332 -18.7273109
96 -12.4481505 34.2339332
97 -32.8515363 -12.4481505
98 -3.1987071 -32.8515363
99 28.1422050 -3.1987071
100 -13.9806875 28.1422050
101 -24.5294863 -13.9806875
102 59.7636910 -24.5294863
103 20.6489693 59.7636910
104 -13.6540196 20.6489693
105 17.8901135 -13.6540196
106 -4.2539741 17.8901135
107 -24.1605804 -4.2539741
108 33.2575192 -24.1605804
109 -22.6642922 33.2575192
110 10.5306343 -22.6642922
111 -9.9923594 10.5306343
112 13.6909303 -9.9923594
113 -11.2614975 13.6909303
114 -22.0203870 -11.2614975
115 -7.6302032 -22.0203870
116 -6.2663594 -7.6302032
> 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/791dr1200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ibrd1200395909.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gm221200395910.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10iuhc1200395910.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/11f2yi1200395910.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/12orrt1200395910.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/13l6bj1200395910.tab")
>
> system("convert tmp/1cr6x1200395909.ps tmp/1cr6x1200395909.png")
> system("convert tmp/2hhaw1200395909.ps tmp/2hhaw1200395909.png")
> system("convert tmp/33pg01200395909.ps tmp/33pg01200395909.png")
> system("convert tmp/4lao71200395909.ps tmp/4lao71200395909.png")
> system("convert tmp/51ony1200395909.ps tmp/51ony1200395909.png")
> system("convert tmp/6ixnj1200395909.ps tmp/6ixnj1200395909.png")
> system("convert tmp/791dr1200395909.ps tmp/791dr1200395909.png")
> system("convert tmp/8ibrd1200395909.ps tmp/8ibrd1200395909.png")
> system("convert tmp/9gm221200395910.ps tmp/9gm221200395910.png")
>
>
> proc.time()
user system elapsed
4.371 2.569 4.730