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.
Natural language support but running in an English locale
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(41
+ ,12
+ ,14
+ ,12
+ ,39
+ ,11
+ ,18
+ ,11
+ ,30
+ ,15
+ ,11
+ ,14
+ ,31
+ ,6
+ ,12
+ ,12
+ ,34
+ ,13
+ ,16
+ ,21
+ ,35
+ ,10
+ ,18
+ ,12
+ ,39
+ ,12
+ ,14
+ ,22
+ ,34
+ ,14
+ ,14
+ ,11
+ ,36
+ ,12
+ ,15
+ ,10
+ ,37
+ ,6
+ ,15
+ ,13
+ ,38
+ ,10
+ ,17
+ ,10
+ ,36
+ ,12
+ ,19
+ ,8
+ ,38
+ ,12
+ ,10
+ ,15
+ ,39
+ ,11
+ ,16
+ ,14
+ ,33
+ ,15
+ ,18
+ ,10
+ ,32
+ ,12
+ ,14
+ ,14
+ ,36
+ ,10
+ ,14
+ ,14
+ ,38
+ ,12
+ ,17
+ ,11
+ ,39
+ ,11
+ ,14
+ ,10
+ ,32
+ ,12
+ ,16
+ ,13
+ ,32
+ ,11
+ ,18
+ ,7
+ ,31
+ ,12
+ ,11
+ ,14
+ ,39
+ ,13
+ ,14
+ ,12
+ ,37
+ ,11
+ ,12
+ ,14
+ ,39
+ ,9
+ ,17
+ ,11
+ ,41
+ ,13
+ ,9
+ ,9
+ ,36
+ ,10
+ ,16
+ ,11
+ ,33
+ ,14
+ ,14
+ ,15
+ ,33
+ ,12
+ ,15
+ ,14
+ ,34
+ ,10
+ ,11
+ ,13
+ ,31
+ ,12
+ ,16
+ ,9
+ ,27
+ ,8
+ ,13
+ ,15
+ ,37
+ ,10
+ ,17
+ ,10
+ ,34
+ ,12
+ ,15
+ ,11
+ ,34
+ ,12
+ ,14
+ ,13
+ ,32
+ ,7
+ ,16
+ ,8
+ ,29
+ ,6
+ ,9
+ ,20
+ ,36
+ ,12
+ ,15
+ ,12
+ ,29
+ ,10
+ ,17
+ ,10
+ ,35
+ ,10
+ ,13
+ ,10
+ ,37
+ ,10
+ ,15
+ ,9
+ ,34
+ ,12
+ ,16
+ ,14
+ ,38
+ ,15
+ ,16
+ ,8
+ ,35
+ ,10
+ ,12
+ ,14
+ ,38
+ ,10
+ ,12
+ ,11
+ ,37
+ ,12
+ ,11
+ ,13
+ ,38
+ ,13
+ ,15
+ ,9
+ ,33
+ ,11
+ ,15
+ ,11
+ ,36
+ ,11
+ ,17
+ ,15
+ ,38
+ ,12
+ ,13
+ ,11
+ ,32
+ ,14
+ ,16
+ ,10
+ ,32
+ ,10
+ ,14
+ ,14
+ ,32
+ ,12
+ ,11
+ ,18
+ ,34
+ ,13
+ ,12
+ ,14
+ ,32
+ ,5
+ ,12
+ ,11
+ ,37
+ ,6
+ ,15
+ ,12
+ ,39
+ ,12
+ ,16
+ ,13
+ ,29
+ ,12
+ ,15
+ ,9
+ ,37
+ ,11
+ ,12
+ ,10
+ ,35
+ ,10
+ ,12
+ ,15
+ ,30
+ ,7
+ ,8
+ ,20
+ ,38
+ ,12
+ ,13
+ ,12
+ ,34
+ ,14
+ ,11
+ ,12
+ ,31
+ ,11
+ ,14
+ ,14
+ ,34
+ ,12
+ ,15
+ ,13
+ ,35
+ ,13
+ ,10
+ ,11
+ ,36
+ ,14
+ ,11
+ ,17
+ ,30
+ ,11
+ ,12
+ ,12
+ ,39
+ ,12
+ ,15
+ ,13
+ ,35
+ ,12
+ ,15
+ ,14
+ ,38
+ ,8
+ ,14
+ ,13
+ ,31
+ ,11
+ ,16
+ ,15
+ ,34
+ ,14
+ ,15
+ ,13
+ ,38
+ ,14
+ ,15
+ ,10
+ ,34
+ ,12
+ ,13
+ ,11
+ ,39
+ ,9
+ ,12
+ ,19
+ ,37
+ ,13
+ ,17
+ ,13
+ ,34
+ ,11
+ ,13
+ ,17
+ ,28
+ ,12
+ ,15
+ ,13
+ ,37
+ ,12
+ ,13
+ ,9
+ ,33
+ ,12
+ ,15
+ ,11
+ ,37
+ ,12
+ ,16
+ ,10
+ ,35
+ ,12
+ ,15
+ ,9
+ ,37
+ ,12
+ ,16
+ ,12
+ ,32
+ ,11
+ ,15
+ ,12
+ ,33
+ ,10
+ ,14
+ ,13
+ ,38
+ ,9
+ ,15
+ ,13
+ ,33
+ ,12
+ ,14
+ ,12
+ ,29
+ ,12
+ ,13
+ ,15
+ ,33
+ ,12
+ ,7
+ ,22
+ ,31
+ ,9
+ ,17
+ ,13
+ ,36
+ ,15
+ ,13
+ ,15
+ ,35
+ ,12
+ ,15
+ ,13
+ ,32
+ ,12
+ ,14
+ ,15
+ ,29
+ ,12
+ ,13
+ ,10
+ ,39
+ ,10
+ ,16
+ ,11
+ ,37
+ ,13
+ ,12
+ ,16
+ ,35
+ ,9
+ ,14
+ ,11
+ ,37
+ ,12
+ ,17
+ ,11
+ ,32
+ ,10
+ ,15
+ ,10
+ ,38
+ ,14
+ ,17
+ ,10
+ ,37
+ ,11
+ ,12
+ ,16
+ ,36
+ ,15
+ ,16
+ ,12
+ ,32
+ ,11
+ ,11
+ ,11
+ ,33
+ ,11
+ ,15
+ ,16
+ ,40
+ ,12
+ ,9
+ ,19
+ ,38
+ ,12
+ ,16
+ ,11
+ ,41
+ ,12
+ ,15
+ ,16
+ ,36
+ ,11
+ ,10
+ ,15
+ ,43
+ ,7
+ ,10
+ ,24
+ ,30
+ ,12
+ ,15
+ ,14
+ ,31
+ ,14
+ ,11
+ ,15
+ ,32
+ ,11
+ ,13
+ ,11
+ ,32
+ ,11
+ ,14
+ ,15
+ ,37
+ ,10
+ ,18
+ ,12
+ ,37
+ ,13
+ ,16
+ ,10
+ ,33
+ ,13
+ ,14
+ ,14
+ ,34
+ ,8
+ ,14
+ ,13
+ ,33
+ ,11
+ ,14
+ ,9
+ ,38
+ ,12
+ ,14
+ ,15
+ ,33
+ ,11
+ ,12
+ ,15
+ ,31
+ ,13
+ ,14
+ ,14
+ ,38
+ ,12
+ ,15
+ ,11
+ ,37
+ ,14
+ ,15
+ ,8
+ ,33
+ ,13
+ ,15
+ ,11
+ ,31
+ ,15
+ ,13
+ ,11
+ ,39
+ ,10
+ ,17
+ ,8
+ ,44
+ ,11
+ ,17
+ ,10
+ ,33
+ ,9
+ ,19
+ ,11
+ ,35
+ ,11
+ ,15
+ ,13
+ ,32
+ ,10
+ ,13
+ ,11
+ ,28
+ ,11
+ ,9
+ ,20
+ ,40
+ ,8
+ ,15
+ ,10
+ ,27
+ ,11
+ ,15
+ ,15
+ ,37
+ ,12
+ ,15
+ ,12
+ ,32
+ ,12
+ ,16
+ ,14
+ ,28
+ ,9
+ ,11
+ ,23
+ ,34
+ ,11
+ ,14
+ ,14
+ ,30
+ ,10
+ ,11
+ ,16
+ ,35
+ ,8
+ ,15
+ ,11
+ ,31
+ ,9
+ ,13
+ ,12
+ ,32
+ ,8
+ ,15
+ ,10
+ ,30
+ ,9
+ ,16
+ ,14
+ ,30
+ ,15
+ ,14
+ ,12
+ ,31
+ ,11
+ ,15
+ ,12
+ ,40
+ ,8
+ ,16
+ ,11
+ ,32
+ ,13
+ ,16
+ ,12
+ ,36
+ ,12
+ ,11
+ ,13
+ ,32
+ ,12
+ ,12
+ ,11
+ ,35
+ ,9
+ ,9
+ ,19
+ ,38
+ ,7
+ ,16
+ ,12
+ ,42
+ ,13
+ ,13
+ ,17
+ ,34
+ ,9
+ ,16
+ ,9
+ ,35
+ ,6
+ ,12
+ ,12
+ ,35
+ ,8
+ ,9
+ ,19
+ ,33
+ ,8
+ ,13
+ ,18
+ ,36
+ ,15
+ ,13
+ ,15
+ ,32
+ ,6
+ ,14
+ ,14
+ ,33
+ ,9
+ ,19
+ ,11
+ ,34
+ ,11
+ ,13
+ ,9
+ ,32
+ ,8
+ ,12
+ ,18
+ ,34
+ ,8
+ ,13
+ ,16)
+ ,dim=c(4
+ ,162)
+ ,dimnames=list(c('Connected'
+ ,'Software'
+ ,'Happiness'
+ ,'Depression')
+ ,1:162))
> y <- array(NA,dim=c(4,162),dimnames=list(c('Connected','Software','Happiness','Depression'),1:162))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Connected Software Happiness Depression
1 41 12 14 12
2 39 11 18 11
3 30 15 11 14
4 31 6 12 12
5 34 13 16 21
6 35 10 18 12
7 39 12 14 22
8 34 14 14 11
9 36 12 15 10
10 37 6 15 13
11 38 10 17 10
12 36 12 19 8
13 38 12 10 15
14 39 11 16 14
15 33 15 18 10
16 32 12 14 14
17 36 10 14 14
18 38 12 17 11
19 39 11 14 10
20 32 12 16 13
21 32 11 18 7
22 31 12 11 14
23 39 13 14 12
24 37 11 12 14
25 39 9 17 11
26 41 13 9 9
27 36 10 16 11
28 33 14 14 15
29 33 12 15 14
30 34 10 11 13
31 31 12 16 9
32 27 8 13 15
33 37 10 17 10
34 34 12 15 11
35 34 12 14 13
36 32 7 16 8
37 29 6 9 20
38 36 12 15 12
39 29 10 17 10
40 35 10 13 10
41 37 10 15 9
42 34 12 16 14
43 38 15 16 8
44 35 10 12 14
45 38 10 12 11
46 37 12 11 13
47 38 13 15 9
48 33 11 15 11
49 36 11 17 15
50 38 12 13 11
51 32 14 16 10
52 32 10 14 14
53 32 12 11 18
54 34 13 12 14
55 32 5 12 11
56 37 6 15 12
57 39 12 16 13
58 29 12 15 9
59 37 11 12 10
60 35 10 12 15
61 30 7 8 20
62 38 12 13 12
63 34 14 11 12
64 31 11 14 14
65 34 12 15 13
66 35 13 10 11
67 36 14 11 17
68 30 11 12 12
69 39 12 15 13
70 35 12 15 14
71 38 8 14 13
72 31 11 16 15
73 34 14 15 13
74 38 14 15 10
75 34 12 13 11
76 39 9 12 19
77 37 13 17 13
78 34 11 13 17
79 28 12 15 13
80 37 12 13 9
81 33 12 15 11
82 37 12 16 10
83 35 12 15 9
84 37 12 16 12
85 32 11 15 12
86 33 10 14 13
87 38 9 15 13
88 33 12 14 12
89 29 12 13 15
90 33 12 7 22
91 31 9 17 13
92 36 15 13 15
93 35 12 15 13
94 32 12 14 15
95 29 12 13 10
96 39 10 16 11
97 37 13 12 16
98 35 9 14 11
99 37 12 17 11
100 32 10 15 10
101 38 14 17 10
102 37 11 12 16
103 36 15 16 12
104 32 11 11 11
105 33 11 15 16
106 40 12 9 19
107 38 12 16 11
108 41 12 15 16
109 36 11 10 15
110 43 7 10 24
111 30 12 15 14
112 31 14 11 15
113 32 11 13 11
114 32 11 14 15
115 37 10 18 12
116 37 13 16 10
117 33 13 14 14
118 34 8 14 13
119 33 11 14 9
120 38 12 14 15
121 33 11 12 15
122 31 13 14 14
123 38 12 15 11
124 37 14 15 8
125 33 13 15 11
126 31 15 13 11
127 39 10 17 8
128 44 11 17 10
129 33 9 19 11
130 35 11 15 13
131 32 10 13 11
132 28 11 9 20
133 40 8 15 10
134 27 11 15 15
135 37 12 15 12
136 32 12 16 14
137 28 9 11 23
138 34 11 14 14
139 30 10 11 16
140 35 8 15 11
141 31 9 13 12
142 32 8 15 10
143 30 9 16 14
144 30 15 14 12
145 31 11 15 12
146 40 8 16 11
147 32 13 16 12
148 36 12 11 13
149 32 12 12 11
150 35 9 9 19
151 38 7 16 12
152 42 13 13 17
153 34 9 16 9
154 35 6 12 12
155 35 8 9 19
156 33 8 13 18
157 36 15 13 15
158 32 6 14 14
159 33 9 19 11
160 34 11 13 9
161 32 8 12 18
162 34 8 13 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Software Happiness Depression
32.33199 0.07369 0.15841 -0.05781
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.65165 -2.54786 -0.06607 2.53125 9.95551
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.33199 3.21373 10.061 <2e-16 ***
Software 0.07369 0.12493 0.590 0.556
Happiness 0.15841 0.13519 1.172 0.243
Depression -0.05781 0.10046 -0.575 0.566
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.364 on 158 degrees of freedom
Multiple R-squared: 0.02509, Adjusted R-squared: 0.006576
F-statistic: 1.355 on 3 and 158 DF, p-value: 0.2586
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.92965908 0.14068185 0.070340925
[2,] 0.87065910 0.25868181 0.129340904
[3,] 0.78924780 0.42150440 0.210752199
[4,] 0.70925744 0.58148511 0.290742555
[5,] 0.61171628 0.77656745 0.388283725
[6,] 0.54641413 0.90717174 0.453585868
[7,] 0.61550242 0.76899516 0.384497582
[8,] 0.57228355 0.85543290 0.427716450
[9,] 0.56264312 0.87471376 0.437356880
[10,] 0.56367515 0.87264970 0.436324849
[11,] 0.48045303 0.96090606 0.519546972
[12,] 0.42704442 0.85408884 0.572955582
[13,] 0.44554170 0.89108340 0.554458301
[14,] 0.47777609 0.95555219 0.522223907
[15,] 0.50318223 0.99363554 0.496817770
[16,] 0.50402607 0.99194786 0.495973928
[17,] 0.54238850 0.91522299 0.457611497
[18,] 0.49833186 0.99666372 0.501668140
[19,] 0.47411112 0.94822225 0.525888877
[20,] 0.63711736 0.72576528 0.362882639
[21,] 0.57650189 0.84699623 0.423498114
[22,] 0.54167557 0.91664886 0.458324431
[23,] 0.51334779 0.97330442 0.486652210
[24,] 0.46956396 0.93912792 0.530436039
[25,] 0.52157943 0.95684114 0.478420568
[26,] 0.77557833 0.44884334 0.224421671
[27,] 0.73809667 0.52380666 0.261903328
[28,] 0.69692863 0.60614275 0.303071374
[29,] 0.65061558 0.69876884 0.349384422
[30,] 0.64541360 0.70917280 0.354586401
[31,] 0.66413922 0.67172156 0.335860780
[32,] 0.61542631 0.76914738 0.384573691
[33,] 0.72509472 0.54981057 0.274905283
[34,] 0.67892283 0.64215434 0.321077171
[35,] 0.64644229 0.70711542 0.353557708
[36,] 0.60073036 0.79853929 0.399269644
[37,] 0.56490673 0.87018653 0.435093267
[38,] 0.51548157 0.96903686 0.484518429
[39,] 0.51522376 0.96955247 0.484776235
[40,] 0.48706717 0.97413435 0.512932827
[41,] 0.46021890 0.92043780 0.539781098
[42,] 0.43010249 0.86020498 0.569897508
[43,] 0.38711741 0.77423483 0.612882587
[44,] 0.37449959 0.74899919 0.625500407
[45,] 0.39116689 0.78233379 0.608833107
[46,] 0.37018286 0.74036572 0.629817140
[47,] 0.34296153 0.68592306 0.657038471
[48,] 0.30197694 0.60395388 0.698023060
[49,] 0.27107799 0.54215599 0.728922006
[50,] 0.26181980 0.52363959 0.738180203
[51,] 0.27604962 0.55209925 0.723950376
[52,] 0.38877068 0.77754137 0.611229317
[53,] 0.36472047 0.72944094 0.635279532
[54,] 0.32321722 0.64643444 0.676782781
[55,] 0.31040808 0.62081617 0.689591915
[56,] 0.30685008 0.61370017 0.693149917
[57,] 0.27128550 0.54257100 0.728714500
[58,] 0.27647224 0.55294448 0.723527759
[59,] 0.24122640 0.48245281 0.758773597
[60,] 0.20902790 0.41805580 0.790972099
[61,] 0.18570925 0.37141850 0.814290751
[62,] 0.21001288 0.42002577 0.789987117
[63,] 0.22674341 0.45348683 0.773256586
[64,] 0.19337658 0.38675316 0.806623420
[65,] 0.20063740 0.40127480 0.799362601
[66,] 0.20986935 0.41973871 0.790130646
[67,] 0.18183350 0.36366700 0.818166501
[68,] 0.17222638 0.34445275 0.827773624
[69,] 0.14637130 0.29274261 0.853628696
[70,] 0.18849778 0.37699556 0.811502218
[71,] 0.16630932 0.33261864 0.833690680
[72,] 0.13938949 0.27877899 0.860610506
[73,] 0.23487826 0.46975653 0.765121736
[74,] 0.21762896 0.43525793 0.782371037
[75,] 0.19603474 0.39206949 0.803965257
[76,] 0.17484221 0.34968442 0.825157788
[77,] 0.14764573 0.29529147 0.852354266
[78,] 0.13078010 0.26156020 0.869219901
[79,] 0.12317556 0.24635111 0.876824443
[80,] 0.10532630 0.21065260 0.894673701
[81,] 0.10560908 0.21121816 0.894390921
[82,] 0.09089040 0.18178080 0.909109600
[83,] 0.12230715 0.24461429 0.877692854
[84,] 0.10055413 0.20110825 0.899445873
[85,] 0.10833350 0.21666700 0.891666500
[86,] 0.09199909 0.18399819 0.908000907
[87,] 0.07446526 0.14893053 0.925534737
[88,] 0.06755507 0.13511013 0.932444934
[89,] 0.09589483 0.19178967 0.904105166
[90,] 0.10386974 0.20773949 0.896130257
[91,] 0.09726994 0.19453988 0.902730061
[92,] 0.07912689 0.15825377 0.920873114
[93,] 0.06725960 0.13451921 0.932740397
[94,] 0.06211529 0.12423058 0.937884709
[95,] 0.05687968 0.11375937 0.943120316
[96,] 0.05350741 0.10701481 0.946492594
[97,] 0.04319802 0.08639605 0.956801975
[98,] 0.03681199 0.07362397 0.963188013
[99,] 0.02973715 0.05947429 0.970262853
[100,] 0.06000665 0.12001330 0.939993352
[101,] 0.05731937 0.11463874 0.942680629
[102,] 0.10645547 0.21291094 0.893544532
[103,] 0.09691343 0.19382686 0.903086571
[104,] 0.40948838 0.81897676 0.590511618
[105,] 0.43818037 0.87636074 0.561819631
[106,] 0.41686454 0.83372909 0.583135456
[107,] 0.39448038 0.78896077 0.605519615
[108,] 0.36333251 0.72666503 0.636667485
[109,] 0.33155195 0.66310390 0.668448051
[110,] 0.30111959 0.60223918 0.698880409
[111,] 0.26327629 0.52655258 0.736723708
[112,] 0.22344773 0.44689546 0.776552271
[113,] 0.20057705 0.40115410 0.799422951
[114,] 0.22601161 0.45202322 0.773988391
[115,] 0.19073330 0.38146660 0.809266700
[116,] 0.18040091 0.36080181 0.819599095
[117,] 0.17759401 0.35518803 0.822405987
[118,] 0.15341865 0.30683731 0.846581347
[119,] 0.12892876 0.25785751 0.871071243
[120,] 0.12723403 0.25446807 0.872765966
[121,] 0.12452806 0.24905612 0.875471938
[122,] 0.39051647 0.78103293 0.609483533
[123,] 0.34624517 0.69249033 0.653754833
[124,] 0.30236038 0.60472077 0.697639617
[125,] 0.27800572 0.55601143 0.721994284
[126,] 0.31802922 0.63605844 0.681970781
[127,] 0.40619892 0.81239783 0.593801084
[128,] 0.56936147 0.86127707 0.430638534
[129,] 0.56005390 0.87989219 0.439946096
[130,] 0.51095473 0.97809054 0.489045270
[131,] 0.62826718 0.74346564 0.371732822
[132,] 0.56186395 0.87627209 0.438136045
[133,] 0.60002797 0.79994406 0.399972031
[134,] 0.54064922 0.91870157 0.459350785
[135,] 0.52255680 0.95488640 0.477443199
[136,] 0.47077706 0.94155411 0.529222944
[137,] 0.52077045 0.95845911 0.479229555
[138,] 0.58945842 0.82108317 0.410541584
[139,] 0.62103274 0.75793452 0.378967261
[140,] 0.79303722 0.41392556 0.206962781
[141,] 0.81835607 0.36328786 0.181643931
[142,] 0.75278378 0.49443244 0.247216221
[143,] 0.76599194 0.46801612 0.234008059
[144,] 0.67605694 0.64788613 0.323943063
[145,] 0.81185227 0.37629546 0.188147730
[146,] 0.99596561 0.00806877 0.004034385
[147,] 0.98707857 0.02584286 0.012921431
[148,] 0.98591172 0.02817655 0.014088277
[149,] 0.98014788 0.03970424 0.019852119
> postscript(file="/var/www/html/freestat/rcomp/tmp/1jcg91290549709.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2c3fu1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3c3fu1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4c3fu1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5c3fu1290549709.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 = 162
Frequency = 1
1 2 3 4 5 6
6.25963825 3.64185977 -4.37057169 -2.98137391 -0.61057226 -0.22663473
7 8 9 10 11 12
4.83776278 -0.94556031 0.98559857 2.60119424 2.81615514 0.23631459
13 14 15 16 17 18
4.06673469 4.13212667 -2.71072489 -2.62473684 1.52264926 2.72658149
19 20 21 22 23 24
4.21770639 -2.99937884 -3.58939004 -3.14949254 4.18594520 2.76578575
25 26 27 28 29 30
3.94766064 6.80458169 1.03238236 -1.71431049 -1.78315161 -0.05991889
31 32 33 34 35 36
-4.23062865 -7.11373742 1.81615514 -0.95658897 -0.68254930 -2.91997585
37 38 39 40 41 42
-4.04362997 1.10122348 -6.18384486 0.44981421 2.07517222 -0.94156638
43 44 45 46 47 48
2.49047974 0.83947880 3.66604144 2.79269501 2.85409307 -1.88289592
49 50 51 52 53 54
1.03152435 3.36024057 -3.32020230 -2.47735074 -1.91824272 -0.38160036
55 56 57 58 59 60
-1.96549331 2.54338178 4.00062116 -6.07221388 2.53453593 0.89729125
61 62 63 64 65 66
-2.95890825 3.41805302 -0.41250354 -3.55104379 -0.84096407 0.76179182
67 68 69 70 71 72
1.87655872 -4.34983916 4.15903593 0.21684839 3.61222291 -3.81006088
73 74 75 76 77 78
-0.98835017 2.83821247 -0.63975943 5.20223411 1.76851334 -0.21919167
79 80 81 82 83 84
-6.84096407 2.24461566 -1.95658897 1.82718380 -0.07221388 1.94280871
85 86 87 88 89 90
-2.82508347 -1.53516320 3.38011508 -1.74036175 -5.40850962 -0.05333383
91 92 93 94 95 96
-3.93671446 1.37041123 0.15903593 -2.56692439 -5.69757189 4.03238236
97 98 99 100 101 102
2.73402455 0.42290495 1.72658149 -2.86701533 2.52138293 2.88141065
103 104 105 106 107 108
0.72172956 -2.24923684 -1.59383366 6.45639927 2.88499626 6.33247329
109 110 111 112 113 114
2.14042774 9.95551202 -4.78315161 -3.23906618 -2.56606638 -2.49323134
115 116 117 118 119 120
1.77336527 1.75349075 -1.69842990 -0.38777709 -1.84010606 3.43307561
121 122 123 124 125 126
-1.17640180 -3.69842990 3.04341103 1.72258757 -2.03028202 -3.86083859
127 128 129 130 131 132
3.70053023 8.74246208 -2.36916890 0.23272898 -2.49237333 -5.41209523
133 134 135 136 137 138
5.28037078 -7.65164611 2.10122348 -2.94156638 -5.40810131 -0.55104379
139 140 141 142 143 144
-3.88648153 0.33818323 -3.36086783 -2.71962922 -4.72048723 -4.96144090
145 146 147 148 149 150
-3.82508347 5.17976846 -3.13088434 1.79269501 -2.48134466 1.67747842
151 152 153 154 155 156
3.31127396 7.63342223 -1.00954950 1.01862609 1.75117147 -0.94030006
157 158 159 160 161 162
1.37041123 -2.18257854 -2.36916890 -0.68169129 -1.78188529 -0.05592497
> postscript(file="/var/www/html/freestat/rcomp/tmp/6muex1290549709.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 = 162
Frequency = 1
lag(myerror, k = 1) myerror
0 6.25963825 NA
1 3.64185977 6.25963825
2 -4.37057169 3.64185977
3 -2.98137391 -4.37057169
4 -0.61057226 -2.98137391
5 -0.22663473 -0.61057226
6 4.83776278 -0.22663473
7 -0.94556031 4.83776278
8 0.98559857 -0.94556031
9 2.60119424 0.98559857
10 2.81615514 2.60119424
11 0.23631459 2.81615514
12 4.06673469 0.23631459
13 4.13212667 4.06673469
14 -2.71072489 4.13212667
15 -2.62473684 -2.71072489
16 1.52264926 -2.62473684
17 2.72658149 1.52264926
18 4.21770639 2.72658149
19 -2.99937884 4.21770639
20 -3.58939004 -2.99937884
21 -3.14949254 -3.58939004
22 4.18594520 -3.14949254
23 2.76578575 4.18594520
24 3.94766064 2.76578575
25 6.80458169 3.94766064
26 1.03238236 6.80458169
27 -1.71431049 1.03238236
28 -1.78315161 -1.71431049
29 -0.05991889 -1.78315161
30 -4.23062865 -0.05991889
31 -7.11373742 -4.23062865
32 1.81615514 -7.11373742
33 -0.95658897 1.81615514
34 -0.68254930 -0.95658897
35 -2.91997585 -0.68254930
36 -4.04362997 -2.91997585
37 1.10122348 -4.04362997
38 -6.18384486 1.10122348
39 0.44981421 -6.18384486
40 2.07517222 0.44981421
41 -0.94156638 2.07517222
42 2.49047974 -0.94156638
43 0.83947880 2.49047974
44 3.66604144 0.83947880
45 2.79269501 3.66604144
46 2.85409307 2.79269501
47 -1.88289592 2.85409307
48 1.03152435 -1.88289592
49 3.36024057 1.03152435
50 -3.32020230 3.36024057
51 -2.47735074 -3.32020230
52 -1.91824272 -2.47735074
53 -0.38160036 -1.91824272
54 -1.96549331 -0.38160036
55 2.54338178 -1.96549331
56 4.00062116 2.54338178
57 -6.07221388 4.00062116
58 2.53453593 -6.07221388
59 0.89729125 2.53453593
60 -2.95890825 0.89729125
61 3.41805302 -2.95890825
62 -0.41250354 3.41805302
63 -3.55104379 -0.41250354
64 -0.84096407 -3.55104379
65 0.76179182 -0.84096407
66 1.87655872 0.76179182
67 -4.34983916 1.87655872
68 4.15903593 -4.34983916
69 0.21684839 4.15903593
70 3.61222291 0.21684839
71 -3.81006088 3.61222291
72 -0.98835017 -3.81006088
73 2.83821247 -0.98835017
74 -0.63975943 2.83821247
75 5.20223411 -0.63975943
76 1.76851334 5.20223411
77 -0.21919167 1.76851334
78 -6.84096407 -0.21919167
79 2.24461566 -6.84096407
80 -1.95658897 2.24461566
81 1.82718380 -1.95658897
82 -0.07221388 1.82718380
83 1.94280871 -0.07221388
84 -2.82508347 1.94280871
85 -1.53516320 -2.82508347
86 3.38011508 -1.53516320
87 -1.74036175 3.38011508
88 -5.40850962 -1.74036175
89 -0.05333383 -5.40850962
90 -3.93671446 -0.05333383
91 1.37041123 -3.93671446
92 0.15903593 1.37041123
93 -2.56692439 0.15903593
94 -5.69757189 -2.56692439
95 4.03238236 -5.69757189
96 2.73402455 4.03238236
97 0.42290495 2.73402455
98 1.72658149 0.42290495
99 -2.86701533 1.72658149
100 2.52138293 -2.86701533
101 2.88141065 2.52138293
102 0.72172956 2.88141065
103 -2.24923684 0.72172956
104 -1.59383366 -2.24923684
105 6.45639927 -1.59383366
106 2.88499626 6.45639927
107 6.33247329 2.88499626
108 2.14042774 6.33247329
109 9.95551202 2.14042774
110 -4.78315161 9.95551202
111 -3.23906618 -4.78315161
112 -2.56606638 -3.23906618
113 -2.49323134 -2.56606638
114 1.77336527 -2.49323134
115 1.75349075 1.77336527
116 -1.69842990 1.75349075
117 -0.38777709 -1.69842990
118 -1.84010606 -0.38777709
119 3.43307561 -1.84010606
120 -1.17640180 3.43307561
121 -3.69842990 -1.17640180
122 3.04341103 -3.69842990
123 1.72258757 3.04341103
124 -2.03028202 1.72258757
125 -3.86083859 -2.03028202
126 3.70053023 -3.86083859
127 8.74246208 3.70053023
128 -2.36916890 8.74246208
129 0.23272898 -2.36916890
130 -2.49237333 0.23272898
131 -5.41209523 -2.49237333
132 5.28037078 -5.41209523
133 -7.65164611 5.28037078
134 2.10122348 -7.65164611
135 -2.94156638 2.10122348
136 -5.40810131 -2.94156638
137 -0.55104379 -5.40810131
138 -3.88648153 -0.55104379
139 0.33818323 -3.88648153
140 -3.36086783 0.33818323
141 -2.71962922 -3.36086783
142 -4.72048723 -2.71962922
143 -4.96144090 -4.72048723
144 -3.82508347 -4.96144090
145 5.17976846 -3.82508347
146 -3.13088434 5.17976846
147 1.79269501 -3.13088434
148 -2.48134466 1.79269501
149 1.67747842 -2.48134466
150 3.31127396 1.67747842
151 7.63342223 3.31127396
152 -1.00954950 7.63342223
153 1.01862609 -1.00954950
154 1.75117147 1.01862609
155 -0.94030006 1.75117147
156 1.37041123 -0.94030006
157 -2.18257854 1.37041123
158 -2.36916890 -2.18257854
159 -0.68169129 -2.36916890
160 -1.78188529 -0.68169129
161 -0.05592497 -1.78188529
162 NA -0.05592497
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.64185977 6.25963825
[2,] -4.37057169 3.64185977
[3,] -2.98137391 -4.37057169
[4,] -0.61057226 -2.98137391
[5,] -0.22663473 -0.61057226
[6,] 4.83776278 -0.22663473
[7,] -0.94556031 4.83776278
[8,] 0.98559857 -0.94556031
[9,] 2.60119424 0.98559857
[10,] 2.81615514 2.60119424
[11,] 0.23631459 2.81615514
[12,] 4.06673469 0.23631459
[13,] 4.13212667 4.06673469
[14,] -2.71072489 4.13212667
[15,] -2.62473684 -2.71072489
[16,] 1.52264926 -2.62473684
[17,] 2.72658149 1.52264926
[18,] 4.21770639 2.72658149
[19,] -2.99937884 4.21770639
[20,] -3.58939004 -2.99937884
[21,] -3.14949254 -3.58939004
[22,] 4.18594520 -3.14949254
[23,] 2.76578575 4.18594520
[24,] 3.94766064 2.76578575
[25,] 6.80458169 3.94766064
[26,] 1.03238236 6.80458169
[27,] -1.71431049 1.03238236
[28,] -1.78315161 -1.71431049
[29,] -0.05991889 -1.78315161
[30,] -4.23062865 -0.05991889
[31,] -7.11373742 -4.23062865
[32,] 1.81615514 -7.11373742
[33,] -0.95658897 1.81615514
[34,] -0.68254930 -0.95658897
[35,] -2.91997585 -0.68254930
[36,] -4.04362997 -2.91997585
[37,] 1.10122348 -4.04362997
[38,] -6.18384486 1.10122348
[39,] 0.44981421 -6.18384486
[40,] 2.07517222 0.44981421
[41,] -0.94156638 2.07517222
[42,] 2.49047974 -0.94156638
[43,] 0.83947880 2.49047974
[44,] 3.66604144 0.83947880
[45,] 2.79269501 3.66604144
[46,] 2.85409307 2.79269501
[47,] -1.88289592 2.85409307
[48,] 1.03152435 -1.88289592
[49,] 3.36024057 1.03152435
[50,] -3.32020230 3.36024057
[51,] -2.47735074 -3.32020230
[52,] -1.91824272 -2.47735074
[53,] -0.38160036 -1.91824272
[54,] -1.96549331 -0.38160036
[55,] 2.54338178 -1.96549331
[56,] 4.00062116 2.54338178
[57,] -6.07221388 4.00062116
[58,] 2.53453593 -6.07221388
[59,] 0.89729125 2.53453593
[60,] -2.95890825 0.89729125
[61,] 3.41805302 -2.95890825
[62,] -0.41250354 3.41805302
[63,] -3.55104379 -0.41250354
[64,] -0.84096407 -3.55104379
[65,] 0.76179182 -0.84096407
[66,] 1.87655872 0.76179182
[67,] -4.34983916 1.87655872
[68,] 4.15903593 -4.34983916
[69,] 0.21684839 4.15903593
[70,] 3.61222291 0.21684839
[71,] -3.81006088 3.61222291
[72,] -0.98835017 -3.81006088
[73,] 2.83821247 -0.98835017
[74,] -0.63975943 2.83821247
[75,] 5.20223411 -0.63975943
[76,] 1.76851334 5.20223411
[77,] -0.21919167 1.76851334
[78,] -6.84096407 -0.21919167
[79,] 2.24461566 -6.84096407
[80,] -1.95658897 2.24461566
[81,] 1.82718380 -1.95658897
[82,] -0.07221388 1.82718380
[83,] 1.94280871 -0.07221388
[84,] -2.82508347 1.94280871
[85,] -1.53516320 -2.82508347
[86,] 3.38011508 -1.53516320
[87,] -1.74036175 3.38011508
[88,] -5.40850962 -1.74036175
[89,] -0.05333383 -5.40850962
[90,] -3.93671446 -0.05333383
[91,] 1.37041123 -3.93671446
[92,] 0.15903593 1.37041123
[93,] -2.56692439 0.15903593
[94,] -5.69757189 -2.56692439
[95,] 4.03238236 -5.69757189
[96,] 2.73402455 4.03238236
[97,] 0.42290495 2.73402455
[98,] 1.72658149 0.42290495
[99,] -2.86701533 1.72658149
[100,] 2.52138293 -2.86701533
[101,] 2.88141065 2.52138293
[102,] 0.72172956 2.88141065
[103,] -2.24923684 0.72172956
[104,] -1.59383366 -2.24923684
[105,] 6.45639927 -1.59383366
[106,] 2.88499626 6.45639927
[107,] 6.33247329 2.88499626
[108,] 2.14042774 6.33247329
[109,] 9.95551202 2.14042774
[110,] -4.78315161 9.95551202
[111,] -3.23906618 -4.78315161
[112,] -2.56606638 -3.23906618
[113,] -2.49323134 -2.56606638
[114,] 1.77336527 -2.49323134
[115,] 1.75349075 1.77336527
[116,] -1.69842990 1.75349075
[117,] -0.38777709 -1.69842990
[118,] -1.84010606 -0.38777709
[119,] 3.43307561 -1.84010606
[120,] -1.17640180 3.43307561
[121,] -3.69842990 -1.17640180
[122,] 3.04341103 -3.69842990
[123,] 1.72258757 3.04341103
[124,] -2.03028202 1.72258757
[125,] -3.86083859 -2.03028202
[126,] 3.70053023 -3.86083859
[127,] 8.74246208 3.70053023
[128,] -2.36916890 8.74246208
[129,] 0.23272898 -2.36916890
[130,] -2.49237333 0.23272898
[131,] -5.41209523 -2.49237333
[132,] 5.28037078 -5.41209523
[133,] -7.65164611 5.28037078
[134,] 2.10122348 -7.65164611
[135,] -2.94156638 2.10122348
[136,] -5.40810131 -2.94156638
[137,] -0.55104379 -5.40810131
[138,] -3.88648153 -0.55104379
[139,] 0.33818323 -3.88648153
[140,] -3.36086783 0.33818323
[141,] -2.71962922 -3.36086783
[142,] -4.72048723 -2.71962922
[143,] -4.96144090 -4.72048723
[144,] -3.82508347 -4.96144090
[145,] 5.17976846 -3.82508347
[146,] -3.13088434 5.17976846
[147,] 1.79269501 -3.13088434
[148,] -2.48134466 1.79269501
[149,] 1.67747842 -2.48134466
[150,] 3.31127396 1.67747842
[151,] 7.63342223 3.31127396
[152,] -1.00954950 7.63342223
[153,] 1.01862609 -1.00954950
[154,] 1.75117147 1.01862609
[155,] -0.94030006 1.75117147
[156,] 1.37041123 -0.94030006
[157,] -2.18257854 1.37041123
[158,] -2.36916890 -2.18257854
[159,] -0.68169129 -2.36916890
[160,] -1.78188529 -0.68169129
[161,] -0.05592497 -1.78188529
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.64185977 6.25963825
2 -4.37057169 3.64185977
3 -2.98137391 -4.37057169
4 -0.61057226 -2.98137391
5 -0.22663473 -0.61057226
6 4.83776278 -0.22663473
7 -0.94556031 4.83776278
8 0.98559857 -0.94556031
9 2.60119424 0.98559857
10 2.81615514 2.60119424
11 0.23631459 2.81615514
12 4.06673469 0.23631459
13 4.13212667 4.06673469
14 -2.71072489 4.13212667
15 -2.62473684 -2.71072489
16 1.52264926 -2.62473684
17 2.72658149 1.52264926
18 4.21770639 2.72658149
19 -2.99937884 4.21770639
20 -3.58939004 -2.99937884
21 -3.14949254 -3.58939004
22 4.18594520 -3.14949254
23 2.76578575 4.18594520
24 3.94766064 2.76578575
25 6.80458169 3.94766064
26 1.03238236 6.80458169
27 -1.71431049 1.03238236
28 -1.78315161 -1.71431049
29 -0.05991889 -1.78315161
30 -4.23062865 -0.05991889
31 -7.11373742 -4.23062865
32 1.81615514 -7.11373742
33 -0.95658897 1.81615514
34 -0.68254930 -0.95658897
35 -2.91997585 -0.68254930
36 -4.04362997 -2.91997585
37 1.10122348 -4.04362997
38 -6.18384486 1.10122348
39 0.44981421 -6.18384486
40 2.07517222 0.44981421
41 -0.94156638 2.07517222
42 2.49047974 -0.94156638
43 0.83947880 2.49047974
44 3.66604144 0.83947880
45 2.79269501 3.66604144
46 2.85409307 2.79269501
47 -1.88289592 2.85409307
48 1.03152435 -1.88289592
49 3.36024057 1.03152435
50 -3.32020230 3.36024057
51 -2.47735074 -3.32020230
52 -1.91824272 -2.47735074
53 -0.38160036 -1.91824272
54 -1.96549331 -0.38160036
55 2.54338178 -1.96549331
56 4.00062116 2.54338178
57 -6.07221388 4.00062116
58 2.53453593 -6.07221388
59 0.89729125 2.53453593
60 -2.95890825 0.89729125
61 3.41805302 -2.95890825
62 -0.41250354 3.41805302
63 -3.55104379 -0.41250354
64 -0.84096407 -3.55104379
65 0.76179182 -0.84096407
66 1.87655872 0.76179182
67 -4.34983916 1.87655872
68 4.15903593 -4.34983916
69 0.21684839 4.15903593
70 3.61222291 0.21684839
71 -3.81006088 3.61222291
72 -0.98835017 -3.81006088
73 2.83821247 -0.98835017
74 -0.63975943 2.83821247
75 5.20223411 -0.63975943
76 1.76851334 5.20223411
77 -0.21919167 1.76851334
78 -6.84096407 -0.21919167
79 2.24461566 -6.84096407
80 -1.95658897 2.24461566
81 1.82718380 -1.95658897
82 -0.07221388 1.82718380
83 1.94280871 -0.07221388
84 -2.82508347 1.94280871
85 -1.53516320 -2.82508347
86 3.38011508 -1.53516320
87 -1.74036175 3.38011508
88 -5.40850962 -1.74036175
89 -0.05333383 -5.40850962
90 -3.93671446 -0.05333383
91 1.37041123 -3.93671446
92 0.15903593 1.37041123
93 -2.56692439 0.15903593
94 -5.69757189 -2.56692439
95 4.03238236 -5.69757189
96 2.73402455 4.03238236
97 0.42290495 2.73402455
98 1.72658149 0.42290495
99 -2.86701533 1.72658149
100 2.52138293 -2.86701533
101 2.88141065 2.52138293
102 0.72172956 2.88141065
103 -2.24923684 0.72172956
104 -1.59383366 -2.24923684
105 6.45639927 -1.59383366
106 2.88499626 6.45639927
107 6.33247329 2.88499626
108 2.14042774 6.33247329
109 9.95551202 2.14042774
110 -4.78315161 9.95551202
111 -3.23906618 -4.78315161
112 -2.56606638 -3.23906618
113 -2.49323134 -2.56606638
114 1.77336527 -2.49323134
115 1.75349075 1.77336527
116 -1.69842990 1.75349075
117 -0.38777709 -1.69842990
118 -1.84010606 -0.38777709
119 3.43307561 -1.84010606
120 -1.17640180 3.43307561
121 -3.69842990 -1.17640180
122 3.04341103 -3.69842990
123 1.72258757 3.04341103
124 -2.03028202 1.72258757
125 -3.86083859 -2.03028202
126 3.70053023 -3.86083859
127 8.74246208 3.70053023
128 -2.36916890 8.74246208
129 0.23272898 -2.36916890
130 -2.49237333 0.23272898
131 -5.41209523 -2.49237333
132 5.28037078 -5.41209523
133 -7.65164611 5.28037078
134 2.10122348 -7.65164611
135 -2.94156638 2.10122348
136 -5.40810131 -2.94156638
137 -0.55104379 -5.40810131
138 -3.88648153 -0.55104379
139 0.33818323 -3.88648153
140 -3.36086783 0.33818323
141 -2.71962922 -3.36086783
142 -4.72048723 -2.71962922
143 -4.96144090 -4.72048723
144 -3.82508347 -4.96144090
145 5.17976846 -3.82508347
146 -3.13088434 5.17976846
147 1.79269501 -3.13088434
148 -2.48134466 1.79269501
149 1.67747842 -2.48134466
150 3.31127396 1.67747842
151 7.63342223 3.31127396
152 -1.00954950 7.63342223
153 1.01862609 -1.00954950
154 1.75117147 1.01862609
155 -0.94030006 1.75117147
156 1.37041123 -0.94030006
157 -2.18257854 1.37041123
158 -2.36916890 -2.18257854
159 -0.68169129 -2.36916890
160 -1.78188529 -0.68169129
161 -0.05592497 -1.78188529
> 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/7fmdi1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8fmdi1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9fmdi1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10qvck1290549709.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11tet91290549709.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/12ew9e1290549709.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/133xpq1290549709.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/14wo6t1290549709.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/freestat/rcomp/tmp/150pnz1290549709.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/freestat/rcomp/tmp/16dzkq1290549709.tab")
+ }
>
> try(system("convert tmp/1jcg91290549709.ps tmp/1jcg91290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c3fu1290549709.ps tmp/2c3fu1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c3fu1290549709.ps tmp/3c3fu1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c3fu1290549709.ps tmp/4c3fu1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c3fu1290549709.ps tmp/5c3fu1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/6muex1290549709.ps tmp/6muex1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fmdi1290549709.ps tmp/7fmdi1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/8fmdi1290549709.ps tmp/8fmdi1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fmdi1290549709.ps tmp/9fmdi1290549709.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qvck1290549709.ps tmp/10qvck1290549709.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.688 2.780 6.213