R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.1608
+ ,0
+ ,1.1208
+ ,0
+ ,1.0883
+ ,0
+ ,1.0704
+ ,0
+ ,1.0628
+ ,0
+ ,1.0378
+ ,0
+ ,1.0353
+ ,0
+ ,1.0604
+ ,0
+ ,1.0501
+ ,0
+ ,1.0706
+ ,0
+ ,1.0338
+ ,0
+ ,1.011
+ ,0
+ ,1.0137
+ ,0
+ ,0.9834
+ ,0
+ ,0.9643
+ ,0
+ ,0.947
+ ,0
+ ,0.906
+ ,0
+ ,0.9492
+ ,0
+ ,0.9397
+ ,0
+ ,0.9041
+ ,0
+ ,0.8721
+ ,0
+ ,0.8552
+ ,0
+ ,0.8564
+ ,0
+ ,0.8973
+ ,0
+ ,0.9383
+ ,0
+ ,0.9217
+ ,0
+ ,0.9095
+ ,0
+ ,0.892
+ ,0
+ ,0.8742
+ ,0
+ ,0.8532
+ ,0
+ ,0.8607
+ ,0
+ ,0.9005
+ ,0
+ ,0.9111
+ ,0
+ ,0.9059
+ ,0
+ ,0.8883
+ ,0
+ ,0.8924
+ ,0
+ ,0.8833
+ ,0
+ ,0.87
+ ,0
+ ,0.8758
+ ,0
+ ,0.8858
+ ,0
+ ,0.917
+ ,0
+ ,0.9554
+ ,0
+ ,0.9922
+ ,0
+ ,0.9778
+ ,0
+ ,0.9808
+ ,0
+ ,0.9811
+ ,0
+ ,1.0014
+ ,0
+ ,1.0183
+ ,0
+ ,1.0622
+ ,0
+ ,1.0773
+ ,0
+ ,1.0807
+ ,0
+ ,1.0848
+ ,0
+ ,1.1582
+ ,0
+ ,1.1663
+ ,0
+ ,1.1372
+ ,0
+ ,1.1139
+ ,0
+ ,1.1222
+ ,0
+ ,1.1692
+ ,0
+ ,1.1702
+ ,0
+ ,1.2286
+ ,0
+ ,1.2613
+ ,0
+ ,1.2646
+ ,0
+ ,1.2262
+ ,0
+ ,1.1985
+ ,0
+ ,1.2007
+ ,0
+ ,1.2138
+ ,0
+ ,1.2266
+ ,0
+ ,1.2176
+ ,0
+ ,1.2218
+ ,0
+ ,1.249
+ ,0
+ ,1.2991
+ ,0
+ ,1.3408
+ ,0
+ ,1.3119
+ ,0
+ ,1.3014
+ ,0
+ ,1.3201
+ ,0
+ ,1.2938
+ ,0
+ ,1.2694
+ ,0
+ ,1.2165
+ ,0
+ ,1.2037
+ ,0
+ ,1.2292
+ ,0
+ ,1.2256
+ ,0
+ ,1.2015
+ ,0
+ ,1.1786
+ ,0
+ ,1.1856
+ ,0
+ ,1.2103
+ ,0
+ ,1.1938
+ ,0
+ ,1.202
+ ,0
+ ,1.2271
+ ,0
+ ,1.277
+ ,0
+ ,1.265
+ ,0
+ ,1.2684
+ ,0
+ ,1.2811
+ ,0
+ ,1.2727
+ ,0
+ ,1.2611
+ ,0
+ ,1.2881
+ ,0
+ ,1.3213
+ ,0
+ ,1.2999
+ ,0
+ ,1.3074
+ ,0
+ ,1.3242
+ ,0
+ ,1.3516
+ ,0
+ ,1.3511
+ ,0
+ ,1.3419
+ ,1
+ ,1.3716
+ ,1
+ ,1.3622
+ ,1
+ ,1.3896
+ ,1
+ ,1.4227
+ ,1
+ ,1.4684
+ ,1
+ ,1.457
+ ,1
+ ,1.4718
+ ,1
+ ,1.4748
+ ,1
+ ,1.5527
+ ,1
+ ,1.5751
+ ,1
+ ,1.5557
+ ,1
+ ,1.5553
+ ,1
+ ,1.577
+ ,1)
+ ,dim=c(2
+ ,115)
+ ,dimnames=list(c('y'
+ ,'x')
+ ,1:115))
> y <- array(NA,dim=c(2,115),dimnames=list(c('y','x'),1:115))
> 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 x
1 1.1608 0
2 1.1208 0
3 1.0883 0
4 1.0704 0
5 1.0628 0
6 1.0378 0
7 1.0353 0
8 1.0604 0
9 1.0501 0
10 1.0706 0
11 1.0338 0
12 1.0110 0
13 1.0137 0
14 0.9834 0
15 0.9643 0
16 0.9470 0
17 0.9060 0
18 0.9492 0
19 0.9397 0
20 0.9041 0
21 0.8721 0
22 0.8552 0
23 0.8564 0
24 0.8973 0
25 0.9383 0
26 0.9217 0
27 0.9095 0
28 0.8920 0
29 0.8742 0
30 0.8532 0
31 0.8607 0
32 0.9005 0
33 0.9111 0
34 0.9059 0
35 0.8883 0
36 0.8924 0
37 0.8833 0
38 0.8700 0
39 0.8758 0
40 0.8858 0
41 0.9170 0
42 0.9554 0
43 0.9922 0
44 0.9778 0
45 0.9808 0
46 0.9811 0
47 1.0014 0
48 1.0183 0
49 1.0622 0
50 1.0773 0
51 1.0807 0
52 1.0848 0
53 1.1582 0
54 1.1663 0
55 1.1372 0
56 1.1139 0
57 1.1222 0
58 1.1692 0
59 1.1702 0
60 1.2286 0
61 1.2613 0
62 1.2646 0
63 1.2262 0
64 1.1985 0
65 1.2007 0
66 1.2138 0
67 1.2266 0
68 1.2176 0
69 1.2218 0
70 1.2490 0
71 1.2991 0
72 1.3408 0
73 1.3119 0
74 1.3014 0
75 1.3201 0
76 1.2938 0
77 1.2694 0
78 1.2165 0
79 1.2037 0
80 1.2292 0
81 1.2256 0
82 1.2015 0
83 1.1786 0
84 1.1856 0
85 1.2103 0
86 1.1938 0
87 1.2020 0
88 1.2271 0
89 1.2770 0
90 1.2650 0
91 1.2684 0
92 1.2811 0
93 1.2727 0
94 1.2611 0
95 1.2881 0
96 1.3213 0
97 1.2999 0
98 1.3074 0
99 1.3242 0
100 1.3516 0
101 1.3511 0
102 1.3419 1
103 1.3716 1
104 1.3622 1
105 1.3896 1
106 1.4227 1
107 1.4684 1
108 1.4570 1
109 1.4718 1
110 1.4748 1
111 1.5527 1
112 1.5751 1
113 1.5557 1
114 1.5553 1
115 1.5770 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
1.1001 0.3696
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.2469 -0.1250 0.0021 0.1236 0.2515
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.10007 0.01481 74.266 < 2e-16 ***
x 0.36963 0.04245 8.707 2.96e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1489 on 113 degrees of freedom
Multiple R-squared: 0.4015, Adjusted R-squared: 0.3962
F-statistic: 75.81 on 1 and 113 DF, p-value: 2.96e-14
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zfd51227462902.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/freestat/rcomp/tmp/2agdc1227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/32zcy1227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/46hjm1227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5uhe51227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 115
Frequency = 1
1 2 3 4 5 6
0.06072673 0.02072673 -0.01177327 -0.02967327 -0.03727327 -0.06227327
7 8 9 10 11 12
-0.06477327 -0.03967327 -0.04997327 -0.02947327 -0.06627327 -0.08907327
13 14 15 16 17 18
-0.08637327 -0.11667327 -0.13577327 -0.15307327 -0.19407327 -0.15087327
19 20 21 22 23 24
-0.16037327 -0.19597327 -0.22797327 -0.24487327 -0.24367327 -0.20277327
25 26 27 28 29 30
-0.16177327 -0.17837327 -0.19057327 -0.20807327 -0.22587327 -0.24687327
31 32 33 34 35 36
-0.23937327 -0.19957327 -0.18897327 -0.19417327 -0.21177327 -0.20767327
37 38 39 40 41 42
-0.21677327 -0.23007327 -0.22427327 -0.21427327 -0.18307327 -0.14467327
43 44 45 46 47 48
-0.10787327 -0.12227327 -0.11927327 -0.11897327 -0.09867327 -0.08177327
49 50 51 52 53 54
-0.03787327 -0.02277327 -0.01937327 -0.01527327 0.05812673 0.06622673
55 56 57 58 59 60
0.03712673 0.01382673 0.02212673 0.06912673 0.07012673 0.12852673
61 62 63 64 65 66
0.16122673 0.16452673 0.12612673 0.09842673 0.10062673 0.11372673
67 68 69 70 71 72
0.12652673 0.11752673 0.12172673 0.14892673 0.19902673 0.24072673
73 74 75 76 77 78
0.21182673 0.20132673 0.22002673 0.19372673 0.16932673 0.11642673
79 80 81 82 83 84
0.10362673 0.12912673 0.12552673 0.10142673 0.07852673 0.08552673
85 86 87 88 89 90
0.11022673 0.09372673 0.10192673 0.12702673 0.17692673 0.16492673
91 92 93 94 95 96
0.16832673 0.18102673 0.17262673 0.16102673 0.18802673 0.22122673
97 98 99 100 101 102
0.19982673 0.20732673 0.22412673 0.25152673 0.25102673 -0.12780000
103 104 105 106 107 108
-0.09810000 -0.10750000 -0.08010000 -0.04700000 -0.00130000 -0.01270000
109 110 111 112 113 114
0.00210000 0.00510000 0.08300000 0.10540000 0.08600000 0.08560000
115
0.10730000
> postscript(file="/var/www/html/freestat/rcomp/tmp/6p1gi1227462902.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 = 115
Frequency = 1
lag(myerror, k = 1) myerror
0 0.06072673 NA
1 0.02072673 0.06072673
2 -0.01177327 0.02072673
3 -0.02967327 -0.01177327
4 -0.03727327 -0.02967327
5 -0.06227327 -0.03727327
6 -0.06477327 -0.06227327
7 -0.03967327 -0.06477327
8 -0.04997327 -0.03967327
9 -0.02947327 -0.04997327
10 -0.06627327 -0.02947327
11 -0.08907327 -0.06627327
12 -0.08637327 -0.08907327
13 -0.11667327 -0.08637327
14 -0.13577327 -0.11667327
15 -0.15307327 -0.13577327
16 -0.19407327 -0.15307327
17 -0.15087327 -0.19407327
18 -0.16037327 -0.15087327
19 -0.19597327 -0.16037327
20 -0.22797327 -0.19597327
21 -0.24487327 -0.22797327
22 -0.24367327 -0.24487327
23 -0.20277327 -0.24367327
24 -0.16177327 -0.20277327
25 -0.17837327 -0.16177327
26 -0.19057327 -0.17837327
27 -0.20807327 -0.19057327
28 -0.22587327 -0.20807327
29 -0.24687327 -0.22587327
30 -0.23937327 -0.24687327
31 -0.19957327 -0.23937327
32 -0.18897327 -0.19957327
33 -0.19417327 -0.18897327
34 -0.21177327 -0.19417327
35 -0.20767327 -0.21177327
36 -0.21677327 -0.20767327
37 -0.23007327 -0.21677327
38 -0.22427327 -0.23007327
39 -0.21427327 -0.22427327
40 -0.18307327 -0.21427327
41 -0.14467327 -0.18307327
42 -0.10787327 -0.14467327
43 -0.12227327 -0.10787327
44 -0.11927327 -0.12227327
45 -0.11897327 -0.11927327
46 -0.09867327 -0.11897327
47 -0.08177327 -0.09867327
48 -0.03787327 -0.08177327
49 -0.02277327 -0.03787327
50 -0.01937327 -0.02277327
51 -0.01527327 -0.01937327
52 0.05812673 -0.01527327
53 0.06622673 0.05812673
54 0.03712673 0.06622673
55 0.01382673 0.03712673
56 0.02212673 0.01382673
57 0.06912673 0.02212673
58 0.07012673 0.06912673
59 0.12852673 0.07012673
60 0.16122673 0.12852673
61 0.16452673 0.16122673
62 0.12612673 0.16452673
63 0.09842673 0.12612673
64 0.10062673 0.09842673
65 0.11372673 0.10062673
66 0.12652673 0.11372673
67 0.11752673 0.12652673
68 0.12172673 0.11752673
69 0.14892673 0.12172673
70 0.19902673 0.14892673
71 0.24072673 0.19902673
72 0.21182673 0.24072673
73 0.20132673 0.21182673
74 0.22002673 0.20132673
75 0.19372673 0.22002673
76 0.16932673 0.19372673
77 0.11642673 0.16932673
78 0.10362673 0.11642673
79 0.12912673 0.10362673
80 0.12552673 0.12912673
81 0.10142673 0.12552673
82 0.07852673 0.10142673
83 0.08552673 0.07852673
84 0.11022673 0.08552673
85 0.09372673 0.11022673
86 0.10192673 0.09372673
87 0.12702673 0.10192673
88 0.17692673 0.12702673
89 0.16492673 0.17692673
90 0.16832673 0.16492673
91 0.18102673 0.16832673
92 0.17262673 0.18102673
93 0.16102673 0.17262673
94 0.18802673 0.16102673
95 0.22122673 0.18802673
96 0.19982673 0.22122673
97 0.20732673 0.19982673
98 0.22412673 0.20732673
99 0.25152673 0.22412673
100 0.25102673 0.25152673
101 -0.12780000 0.25102673
102 -0.09810000 -0.12780000
103 -0.10750000 -0.09810000
104 -0.08010000 -0.10750000
105 -0.04700000 -0.08010000
106 -0.00130000 -0.04700000
107 -0.01270000 -0.00130000
108 0.00210000 -0.01270000
109 0.00510000 0.00210000
110 0.08300000 0.00510000
111 0.10540000 0.08300000
112 0.08600000 0.10540000
113 0.08560000 0.08600000
114 0.10730000 0.08560000
115 NA 0.10730000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.02072673 0.06072673
[2,] -0.01177327 0.02072673
[3,] -0.02967327 -0.01177327
[4,] -0.03727327 -0.02967327
[5,] -0.06227327 -0.03727327
[6,] -0.06477327 -0.06227327
[7,] -0.03967327 -0.06477327
[8,] -0.04997327 -0.03967327
[9,] -0.02947327 -0.04997327
[10,] -0.06627327 -0.02947327
[11,] -0.08907327 -0.06627327
[12,] -0.08637327 -0.08907327
[13,] -0.11667327 -0.08637327
[14,] -0.13577327 -0.11667327
[15,] -0.15307327 -0.13577327
[16,] -0.19407327 -0.15307327
[17,] -0.15087327 -0.19407327
[18,] -0.16037327 -0.15087327
[19,] -0.19597327 -0.16037327
[20,] -0.22797327 -0.19597327
[21,] -0.24487327 -0.22797327
[22,] -0.24367327 -0.24487327
[23,] -0.20277327 -0.24367327
[24,] -0.16177327 -0.20277327
[25,] -0.17837327 -0.16177327
[26,] -0.19057327 -0.17837327
[27,] -0.20807327 -0.19057327
[28,] -0.22587327 -0.20807327
[29,] -0.24687327 -0.22587327
[30,] -0.23937327 -0.24687327
[31,] -0.19957327 -0.23937327
[32,] -0.18897327 -0.19957327
[33,] -0.19417327 -0.18897327
[34,] -0.21177327 -0.19417327
[35,] -0.20767327 -0.21177327
[36,] -0.21677327 -0.20767327
[37,] -0.23007327 -0.21677327
[38,] -0.22427327 -0.23007327
[39,] -0.21427327 -0.22427327
[40,] -0.18307327 -0.21427327
[41,] -0.14467327 -0.18307327
[42,] -0.10787327 -0.14467327
[43,] -0.12227327 -0.10787327
[44,] -0.11927327 -0.12227327
[45,] -0.11897327 -0.11927327
[46,] -0.09867327 -0.11897327
[47,] -0.08177327 -0.09867327
[48,] -0.03787327 -0.08177327
[49,] -0.02277327 -0.03787327
[50,] -0.01937327 -0.02277327
[51,] -0.01527327 -0.01937327
[52,] 0.05812673 -0.01527327
[53,] 0.06622673 0.05812673
[54,] 0.03712673 0.06622673
[55,] 0.01382673 0.03712673
[56,] 0.02212673 0.01382673
[57,] 0.06912673 0.02212673
[58,] 0.07012673 0.06912673
[59,] 0.12852673 0.07012673
[60,] 0.16122673 0.12852673
[61,] 0.16452673 0.16122673
[62,] 0.12612673 0.16452673
[63,] 0.09842673 0.12612673
[64,] 0.10062673 0.09842673
[65,] 0.11372673 0.10062673
[66,] 0.12652673 0.11372673
[67,] 0.11752673 0.12652673
[68,] 0.12172673 0.11752673
[69,] 0.14892673 0.12172673
[70,] 0.19902673 0.14892673
[71,] 0.24072673 0.19902673
[72,] 0.21182673 0.24072673
[73,] 0.20132673 0.21182673
[74,] 0.22002673 0.20132673
[75,] 0.19372673 0.22002673
[76,] 0.16932673 0.19372673
[77,] 0.11642673 0.16932673
[78,] 0.10362673 0.11642673
[79,] 0.12912673 0.10362673
[80,] 0.12552673 0.12912673
[81,] 0.10142673 0.12552673
[82,] 0.07852673 0.10142673
[83,] 0.08552673 0.07852673
[84,] 0.11022673 0.08552673
[85,] 0.09372673 0.11022673
[86,] 0.10192673 0.09372673
[87,] 0.12702673 0.10192673
[88,] 0.17692673 0.12702673
[89,] 0.16492673 0.17692673
[90,] 0.16832673 0.16492673
[91,] 0.18102673 0.16832673
[92,] 0.17262673 0.18102673
[93,] 0.16102673 0.17262673
[94,] 0.18802673 0.16102673
[95,] 0.22122673 0.18802673
[96,] 0.19982673 0.22122673
[97,] 0.20732673 0.19982673
[98,] 0.22412673 0.20732673
[99,] 0.25152673 0.22412673
[100,] 0.25102673 0.25152673
[101,] -0.12780000 0.25102673
[102,] -0.09810000 -0.12780000
[103,] -0.10750000 -0.09810000
[104,] -0.08010000 -0.10750000
[105,] -0.04700000 -0.08010000
[106,] -0.00130000 -0.04700000
[107,] -0.01270000 -0.00130000
[108,] 0.00210000 -0.01270000
[109,] 0.00510000 0.00210000
[110,] 0.08300000 0.00510000
[111,] 0.10540000 0.08300000
[112,] 0.08600000 0.10540000
[113,] 0.08560000 0.08600000
[114,] 0.10730000 0.08560000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.02072673 0.06072673
2 -0.01177327 0.02072673
3 -0.02967327 -0.01177327
4 -0.03727327 -0.02967327
5 -0.06227327 -0.03727327
6 -0.06477327 -0.06227327
7 -0.03967327 -0.06477327
8 -0.04997327 -0.03967327
9 -0.02947327 -0.04997327
10 -0.06627327 -0.02947327
11 -0.08907327 -0.06627327
12 -0.08637327 -0.08907327
13 -0.11667327 -0.08637327
14 -0.13577327 -0.11667327
15 -0.15307327 -0.13577327
16 -0.19407327 -0.15307327
17 -0.15087327 -0.19407327
18 -0.16037327 -0.15087327
19 -0.19597327 -0.16037327
20 -0.22797327 -0.19597327
21 -0.24487327 -0.22797327
22 -0.24367327 -0.24487327
23 -0.20277327 -0.24367327
24 -0.16177327 -0.20277327
25 -0.17837327 -0.16177327
26 -0.19057327 -0.17837327
27 -0.20807327 -0.19057327
28 -0.22587327 -0.20807327
29 -0.24687327 -0.22587327
30 -0.23937327 -0.24687327
31 -0.19957327 -0.23937327
32 -0.18897327 -0.19957327
33 -0.19417327 -0.18897327
34 -0.21177327 -0.19417327
35 -0.20767327 -0.21177327
36 -0.21677327 -0.20767327
37 -0.23007327 -0.21677327
38 -0.22427327 -0.23007327
39 -0.21427327 -0.22427327
40 -0.18307327 -0.21427327
41 -0.14467327 -0.18307327
42 -0.10787327 -0.14467327
43 -0.12227327 -0.10787327
44 -0.11927327 -0.12227327
45 -0.11897327 -0.11927327
46 -0.09867327 -0.11897327
47 -0.08177327 -0.09867327
48 -0.03787327 -0.08177327
49 -0.02277327 -0.03787327
50 -0.01937327 -0.02277327
51 -0.01527327 -0.01937327
52 0.05812673 -0.01527327
53 0.06622673 0.05812673
54 0.03712673 0.06622673
55 0.01382673 0.03712673
56 0.02212673 0.01382673
57 0.06912673 0.02212673
58 0.07012673 0.06912673
59 0.12852673 0.07012673
60 0.16122673 0.12852673
61 0.16452673 0.16122673
62 0.12612673 0.16452673
63 0.09842673 0.12612673
64 0.10062673 0.09842673
65 0.11372673 0.10062673
66 0.12652673 0.11372673
67 0.11752673 0.12652673
68 0.12172673 0.11752673
69 0.14892673 0.12172673
70 0.19902673 0.14892673
71 0.24072673 0.19902673
72 0.21182673 0.24072673
73 0.20132673 0.21182673
74 0.22002673 0.20132673
75 0.19372673 0.22002673
76 0.16932673 0.19372673
77 0.11642673 0.16932673
78 0.10362673 0.11642673
79 0.12912673 0.10362673
80 0.12552673 0.12912673
81 0.10142673 0.12552673
82 0.07852673 0.10142673
83 0.08552673 0.07852673
84 0.11022673 0.08552673
85 0.09372673 0.11022673
86 0.10192673 0.09372673
87 0.12702673 0.10192673
88 0.17692673 0.12702673
89 0.16492673 0.17692673
90 0.16832673 0.16492673
91 0.18102673 0.16832673
92 0.17262673 0.18102673
93 0.16102673 0.17262673
94 0.18802673 0.16102673
95 0.22122673 0.18802673
96 0.19982673 0.22122673
97 0.20732673 0.19982673
98 0.22412673 0.20732673
99 0.25152673 0.22412673
100 0.25102673 0.25152673
101 -0.12780000 0.25102673
102 -0.09810000 -0.12780000
103 -0.10750000 -0.09810000
104 -0.08010000 -0.10750000
105 -0.04700000 -0.08010000
106 -0.00130000 -0.04700000
107 -0.01270000 -0.00130000
108 0.00210000 -0.01270000
109 0.00510000 0.00210000
110 0.08300000 0.00510000
111 0.10540000 0.08300000
112 0.08600000 0.10540000
113 0.08560000 0.08600000
114 0.10730000 0.08560000
> 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/freestat/rcomp/tmp/7k9561227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/853og1227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9d7du1227462902.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/10vnmx1227462902.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/freestat/rcomp/tmp/11a3nh1227462902.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/freestat/rcomp/tmp/12342h1227462902.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/freestat/rcomp/tmp/13fntu1227462902.tab")
>
> system("convert tmp/1zfd51227462902.ps tmp/1zfd51227462902.png")
> system("convert tmp/2agdc1227462902.ps tmp/2agdc1227462902.png")
> system("convert tmp/32zcy1227462902.ps tmp/32zcy1227462902.png")
> system("convert tmp/46hjm1227462902.ps tmp/46hjm1227462902.png")
> system("convert tmp/5uhe51227462902.ps tmp/5uhe51227462902.png")
> system("convert tmp/6p1gi1227462902.ps tmp/6p1gi1227462902.png")
> system("convert tmp/7k9561227462902.ps tmp/7k9561227462902.png")
> system("convert tmp/853og1227462902.ps tmp/853og1227462902.png")
> system("convert tmp/9d7du1227462902.ps tmp/9d7du1227462902.png")
>
>
> proc.time()
user system elapsed
3.160 2.273 3.895