R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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(100.0
+ ,114.1
+ ,141.7
+ ,100.0
+ ,93.5
+ ,110.3
+ ,153.4
+ ,117.5
+ ,88.2
+ ,103.9
+ ,145
+ ,95.5
+ ,89.2
+ ,101.6
+ ,137.7
+ ,100.2
+ ,91.4
+ ,94.6
+ ,148.3
+ ,104.9
+ ,92.5
+ ,95.9
+ ,152.2
+ ,115.9
+ ,91.4
+ ,104.7
+ ,169.4
+ ,125.1
+ ,88.2
+ ,102.8
+ ,168.6
+ ,129.9
+ ,87.1
+ ,98.1
+ ,161.1
+ ,136.8
+ ,84.9
+ ,113.9
+ ,174.1
+ ,136.0
+ ,92.5
+ ,80.9
+ ,179
+ ,107.6
+ ,93.5
+ ,95.7
+ ,190.6
+ ,117.9
+ ,93.5
+ ,113.2
+ ,190
+ ,119.3
+ ,91.4
+ ,105.9
+ ,181.6
+ ,123.9
+ ,90.3
+ ,108.8
+ ,174.8
+ ,113.7
+ ,91.4
+ ,102.3
+ ,180.5
+ ,131.9
+ ,93.5
+ ,99
+ ,196.8
+ ,159.6
+ ,93.5
+ ,100.7
+ ,193.8
+ ,124.3
+ ,92.5
+ ,115.5
+ ,197
+ ,138.3
+ ,91.4
+ ,100.7
+ ,216.3
+ ,104.9
+ ,89.2
+ ,109.9
+ ,221.4
+ ,132.0
+ ,86.0
+ ,114.6
+ ,217.9
+ ,118.1
+ ,88.2
+ ,85.4
+ ,229.7
+ ,114.0
+ ,87.1
+ ,100.5
+ ,227.4
+ ,106.5
+ ,87.1
+ ,114.8
+ ,204.2
+ ,110.4
+ ,86.0
+ ,116.5
+ ,196.6
+ ,115.0
+ ,84.9
+ ,112.9
+ ,198.8
+ ,95.5
+ ,84.9
+ ,102
+ ,207.5
+ ,105.8
+ ,86.0
+ ,106
+ ,190.7
+ ,109.1
+ ,86.0
+ ,105.3
+ ,201.6
+ ,105.6
+ ,84.9
+ ,118.8
+ ,210.5
+ ,118.2
+ ,86.0
+ ,106.1
+ ,223.5
+ ,107.2
+ ,82.8
+ ,109.3
+ ,223.8
+ ,102.1
+ ,77.4
+ ,117.2
+ ,231.2
+ ,126.5
+ ,80.6
+ ,92.5
+ ,244
+ ,111.7
+ ,78.5
+ ,104.2
+ ,234.7
+ ,99.3
+ ,75.3
+ ,112.5
+ ,250.2
+ ,88.1
+ ,75.3
+ ,122.4
+ ,265.7
+ ,117.7
+ ,75.3
+ ,113.3
+ ,287.6
+ ,96.0
+ ,77.4
+ ,100
+ ,283.3
+ ,95.7
+ ,78.5
+ ,110.7
+ ,295.4
+ ,117.2
+ ,76.3
+ ,112.8
+ ,312.3
+ ,113.2
+ ,73.1
+ ,109.8
+ ,333.8
+ ,101.7
+ ,68.8
+ ,117.3
+ ,347.7
+ ,129.8
+ ,65.6
+ ,109.1
+ ,383.2
+ ,96.2
+ ,69.9
+ ,115.9
+ ,407.1
+ ,121.9
+ ,82.8
+ ,96
+ ,413.6
+ ,106.1
+ ,84.9
+ ,99.8
+ ,362.7
+ ,99.6
+ ,80.6
+ ,116.8
+ ,321.9
+ ,112.8
+ ,74.2
+ ,115.7
+ ,239.4
+ ,99.4
+ ,71.0
+ ,99.4
+ ,191
+ ,84.8
+ ,74.2
+ ,94.3
+ ,159.7
+ ,96.6
+ ,82.8
+ ,91
+ ,163.4
+ ,83.0
+ ,86.0
+ ,93.2
+ ,157.6
+ ,80.9
+ ,86.0
+ ,103.1
+ ,166.2
+ ,104.2
+ ,82.8
+ ,94.1
+ ,176.7
+ ,91.1
+ ,78.5
+ ,91.8
+ ,198.3
+ ,84.8
+ ,79.6
+ ,102.7
+ ,226.2
+ ,117.3
+ ,87.1
+ ,82.6
+ ,216.2
+ ,98.1
+ ,89.2
+ ,89.1
+ ,235.9
+ ,112.5)
+ ,dim=c(4
+ ,60)
+ ,dimnames=list(c('wrk'
+ ,'indpr'
+ ,'grn'
+ ,'bw')
+ ,1:60))
> y <- array(NA,dim=c(4,60),dimnames=list(c('wrk','indpr','grn','bw'),1:60))
> 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
wrk indpr grn bw
1 100.0 114.1 141.7 100.0
2 93.5 110.3 153.4 117.5
3 88.2 103.9 145.0 95.5
4 89.2 101.6 137.7 100.2
5 91.4 94.6 148.3 104.9
6 92.5 95.9 152.2 115.9
7 91.4 104.7 169.4 125.1
8 88.2 102.8 168.6 129.9
9 87.1 98.1 161.1 136.8
10 84.9 113.9 174.1 136.0
11 92.5 80.9 179.0 107.6
12 93.5 95.7 190.6 117.9
13 93.5 113.2 190.0 119.3
14 91.4 105.9 181.6 123.9
15 90.3 108.8 174.8 113.7
16 91.4 102.3 180.5 131.9
17 93.5 99.0 196.8 159.6
18 93.5 100.7 193.8 124.3
19 92.5 115.5 197.0 138.3
20 91.4 100.7 216.3 104.9
21 89.2 109.9 221.4 132.0
22 86.0 114.6 217.9 118.1
23 88.2 85.4 229.7 114.0
24 87.1 100.5 227.4 106.5
25 87.1 114.8 204.2 110.4
26 86.0 116.5 196.6 115.0
27 84.9 112.9 198.8 95.5
28 84.9 102.0 207.5 105.8
29 86.0 106.0 190.7 109.1
30 86.0 105.3 201.6 105.6
31 84.9 118.8 210.5 118.2
32 86.0 106.1 223.5 107.2
33 82.8 109.3 223.8 102.1
34 77.4 117.2 231.2 126.5
35 80.6 92.5 244.0 111.7
36 78.5 104.2 234.7 99.3
37 75.3 112.5 250.2 88.1
38 75.3 122.4 265.7 117.7
39 75.3 113.3 287.6 96.0
40 77.4 100.0 283.3 95.7
41 78.5 110.7 295.4 117.2
42 76.3 112.8 312.3 113.2
43 73.1 109.8 333.8 101.7
44 68.8 117.3 347.7 129.8
45 65.6 109.1 383.2 96.2
46 69.9 115.9 407.1 121.9
47 82.8 96.0 413.6 106.1
48 84.9 99.8 362.7 99.6
49 80.6 116.8 321.9 112.8
50 74.2 115.7 239.4 99.4
51 71.0 99.4 191.0 84.8
52 74.2 94.3 159.7 96.6
53 82.8 91.0 163.4 83.0
54 86.0 93.2 157.6 80.9
55 86.0 103.1 166.2 104.2
56 82.8 94.1 176.7 91.1
57 78.5 91.8 198.3 84.8
58 79.6 102.7 226.2 117.3
59 87.1 82.6 216.2 98.1
60 89.2 89.1 235.9 112.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) indpr grn bw
95.98180 -0.16234 -0.06474 0.17827
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13.3548 -2.6574 0.7625 2.6763 13.8880
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 95.98180 7.72749 12.421 < 2e-16 ***
indpr -0.16234 0.07366 -2.204 0.03167 *
grn -0.06474 0.01028 -6.297 4.98e-08 ***
bw 0.17827 0.04461 3.996 0.00019 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.03 on 56 degrees of freedom
Multiple R-squared: 0.5565, Adjusted R-squared: 0.5328
F-statistic: 23.43 on 3 and 56 DF, p-value: 5.918e-10
> 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,] 0.445034141 0.89006828 0.55496586
[2,] 0.354710840 0.70942168 0.64528916
[3,] 0.284078189 0.56815638 0.71592181
[4,] 0.376360967 0.75272193 0.62363903
[5,] 0.328608853 0.65721771 0.67139115
[6,] 0.246729364 0.49345873 0.75327064
[7,] 0.190222342 0.38044468 0.80977766
[8,] 0.126493273 0.25298655 0.87350673
[9,] 0.100643083 0.20128617 0.89935692
[10,] 0.068800954 0.13760191 0.93119905
[11,] 0.101748563 0.20349713 0.89825144
[12,] 0.071028326 0.14205665 0.92897167
[13,] 0.047864546 0.09572909 0.95213545
[14,] 0.052538857 0.10507771 0.94746114
[15,] 0.042173498 0.08434700 0.95782650
[16,] 0.057153335 0.11430667 0.94284667
[17,] 0.040599782 0.08119956 0.95940022
[18,] 0.034081546 0.06816309 0.96591845
[19,] 0.033609716 0.06721943 0.96639028
[20,] 0.034459803 0.06891961 0.96554020
[21,] 0.043807255 0.08761451 0.95619275
[22,] 0.039945752 0.07989150 0.96005425
[23,] 0.036081000 0.07216200 0.96391900
[24,] 0.032475960 0.06495192 0.96752404
[25,] 0.038895920 0.07779184 0.96110408
[26,] 0.040820377 0.08164075 0.95917962
[27,] 0.046217876 0.09243575 0.95378212
[28,] 0.081477347 0.16295469 0.91852265
[29,] 0.083841207 0.16768241 0.91615879
[30,] 0.078001523 0.15600305 0.92199848
[31,] 0.071355211 0.14271042 0.92864479
[32,] 0.059708770 0.11941754 0.94029123
[33,] 0.044321004 0.08864201 0.95567900
[34,] 0.028317813 0.05663563 0.97168219
[35,] 0.019003764 0.03800753 0.98099624
[36,] 0.012212021 0.02442404 0.98778798
[37,] 0.007003085 0.01400617 0.99299691
[38,] 0.009354842 0.01870968 0.99064516
[39,] 0.018774018 0.03754804 0.98122598
[40,] 0.055883446 0.11176689 0.94411655
[41,] 0.160503355 0.32100671 0.83949665
[42,] 0.176360781 0.35272156 0.82363922
[43,] 0.168360940 0.33672188 0.83163906
[44,] 0.154786506 0.30957301 0.84521349
[45,] 0.277203407 0.55440681 0.72279659
[46,] 0.937814337 0.12437133 0.06218566
[47,] 0.898051548 0.20389690 0.10194845
> postscript(file="/var/www/html/rcomp/tmp/1rygz1261145091.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wxqh1261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bsgl1261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ualr1261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5i2i71261145091.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 = 60
Frequency = 1
1 2 3 4 5 6
13.88797111 4.40888167 1.44800045 0.76414091 1.67619741 1.27877599
7 8 9 10 11 12
1.08084127 -3.33508201 -6.91368866 -5.56450141 2.05846885 4.37589696
13 14 15 16 17 18
6.92836208 2.27943026 3.02829531 0.19765234 -2.12079266 4.25383633
19 20 21 22 23 24
3.36783020 7.06896368 1.86156494 1.67588119 0.63052568 3.16991216
25 26 27 28 29 30
3.29404045 1.15793054 3.09219373 0.04982202 0.12320089 1.33920304
31 32 33 34 35 36
0.76077007 2.60171077 0.84978056 -7.13842139 -4.48104497 -3.07328555
37 38 39 40 41 42
-1.92576952 -4.59187886 -0.78284044 -1.06682825 -1.27921758 -1.33108201
43 44 45 46 47 48
-1.57602957 -8.76793177 -5.01089002 -2.64115422 10.26582565 10.84603925
49 50 51 52 53 54
4.31110251 -5.21995237 -11.59686671 -13.35480461 -2.62651163 0.92948419
55 56 57 58 59 60
-1.06025795 -2.70616540 -4.85800052 -5.97594132 1.03642778 2.89997915
> postscript(file="/var/www/html/rcomp/tmp/6zpjk1261145091.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 13.88797111 NA
1 4.40888167 13.88797111
2 1.44800045 4.40888167
3 0.76414091 1.44800045
4 1.67619741 0.76414091
5 1.27877599 1.67619741
6 1.08084127 1.27877599
7 -3.33508201 1.08084127
8 -6.91368866 -3.33508201
9 -5.56450141 -6.91368866
10 2.05846885 -5.56450141
11 4.37589696 2.05846885
12 6.92836208 4.37589696
13 2.27943026 6.92836208
14 3.02829531 2.27943026
15 0.19765234 3.02829531
16 -2.12079266 0.19765234
17 4.25383633 -2.12079266
18 3.36783020 4.25383633
19 7.06896368 3.36783020
20 1.86156494 7.06896368
21 1.67588119 1.86156494
22 0.63052568 1.67588119
23 3.16991216 0.63052568
24 3.29404045 3.16991216
25 1.15793054 3.29404045
26 3.09219373 1.15793054
27 0.04982202 3.09219373
28 0.12320089 0.04982202
29 1.33920304 0.12320089
30 0.76077007 1.33920304
31 2.60171077 0.76077007
32 0.84978056 2.60171077
33 -7.13842139 0.84978056
34 -4.48104497 -7.13842139
35 -3.07328555 -4.48104497
36 -1.92576952 -3.07328555
37 -4.59187886 -1.92576952
38 -0.78284044 -4.59187886
39 -1.06682825 -0.78284044
40 -1.27921758 -1.06682825
41 -1.33108201 -1.27921758
42 -1.57602957 -1.33108201
43 -8.76793177 -1.57602957
44 -5.01089002 -8.76793177
45 -2.64115422 -5.01089002
46 10.26582565 -2.64115422
47 10.84603925 10.26582565
48 4.31110251 10.84603925
49 -5.21995237 4.31110251
50 -11.59686671 -5.21995237
51 -13.35480461 -11.59686671
52 -2.62651163 -13.35480461
53 0.92948419 -2.62651163
54 -1.06025795 0.92948419
55 -2.70616540 -1.06025795
56 -4.85800052 -2.70616540
57 -5.97594132 -4.85800052
58 1.03642778 -5.97594132
59 2.89997915 1.03642778
60 NA 2.89997915
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.40888167 13.88797111
[2,] 1.44800045 4.40888167
[3,] 0.76414091 1.44800045
[4,] 1.67619741 0.76414091
[5,] 1.27877599 1.67619741
[6,] 1.08084127 1.27877599
[7,] -3.33508201 1.08084127
[8,] -6.91368866 -3.33508201
[9,] -5.56450141 -6.91368866
[10,] 2.05846885 -5.56450141
[11,] 4.37589696 2.05846885
[12,] 6.92836208 4.37589696
[13,] 2.27943026 6.92836208
[14,] 3.02829531 2.27943026
[15,] 0.19765234 3.02829531
[16,] -2.12079266 0.19765234
[17,] 4.25383633 -2.12079266
[18,] 3.36783020 4.25383633
[19,] 7.06896368 3.36783020
[20,] 1.86156494 7.06896368
[21,] 1.67588119 1.86156494
[22,] 0.63052568 1.67588119
[23,] 3.16991216 0.63052568
[24,] 3.29404045 3.16991216
[25,] 1.15793054 3.29404045
[26,] 3.09219373 1.15793054
[27,] 0.04982202 3.09219373
[28,] 0.12320089 0.04982202
[29,] 1.33920304 0.12320089
[30,] 0.76077007 1.33920304
[31,] 2.60171077 0.76077007
[32,] 0.84978056 2.60171077
[33,] -7.13842139 0.84978056
[34,] -4.48104497 -7.13842139
[35,] -3.07328555 -4.48104497
[36,] -1.92576952 -3.07328555
[37,] -4.59187886 -1.92576952
[38,] -0.78284044 -4.59187886
[39,] -1.06682825 -0.78284044
[40,] -1.27921758 -1.06682825
[41,] -1.33108201 -1.27921758
[42,] -1.57602957 -1.33108201
[43,] -8.76793177 -1.57602957
[44,] -5.01089002 -8.76793177
[45,] -2.64115422 -5.01089002
[46,] 10.26582565 -2.64115422
[47,] 10.84603925 10.26582565
[48,] 4.31110251 10.84603925
[49,] -5.21995237 4.31110251
[50,] -11.59686671 -5.21995237
[51,] -13.35480461 -11.59686671
[52,] -2.62651163 -13.35480461
[53,] 0.92948419 -2.62651163
[54,] -1.06025795 0.92948419
[55,] -2.70616540 -1.06025795
[56,] -4.85800052 -2.70616540
[57,] -5.97594132 -4.85800052
[58,] 1.03642778 -5.97594132
[59,] 2.89997915 1.03642778
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.40888167 13.88797111
2 1.44800045 4.40888167
3 0.76414091 1.44800045
4 1.67619741 0.76414091
5 1.27877599 1.67619741
6 1.08084127 1.27877599
7 -3.33508201 1.08084127
8 -6.91368866 -3.33508201
9 -5.56450141 -6.91368866
10 2.05846885 -5.56450141
11 4.37589696 2.05846885
12 6.92836208 4.37589696
13 2.27943026 6.92836208
14 3.02829531 2.27943026
15 0.19765234 3.02829531
16 -2.12079266 0.19765234
17 4.25383633 -2.12079266
18 3.36783020 4.25383633
19 7.06896368 3.36783020
20 1.86156494 7.06896368
21 1.67588119 1.86156494
22 0.63052568 1.67588119
23 3.16991216 0.63052568
24 3.29404045 3.16991216
25 1.15793054 3.29404045
26 3.09219373 1.15793054
27 0.04982202 3.09219373
28 0.12320089 0.04982202
29 1.33920304 0.12320089
30 0.76077007 1.33920304
31 2.60171077 0.76077007
32 0.84978056 2.60171077
33 -7.13842139 0.84978056
34 -4.48104497 -7.13842139
35 -3.07328555 -4.48104497
36 -1.92576952 -3.07328555
37 -4.59187886 -1.92576952
38 -0.78284044 -4.59187886
39 -1.06682825 -0.78284044
40 -1.27921758 -1.06682825
41 -1.33108201 -1.27921758
42 -1.57602957 -1.33108201
43 -8.76793177 -1.57602957
44 -5.01089002 -8.76793177
45 -2.64115422 -5.01089002
46 10.26582565 -2.64115422
47 10.84603925 10.26582565
48 4.31110251 10.84603925
49 -5.21995237 4.31110251
50 -11.59686671 -5.21995237
51 -13.35480461 -11.59686671
52 -2.62651163 -13.35480461
53 0.92948419 -2.62651163
54 -1.06025795 0.92948419
55 -2.70616540 -1.06025795
56 -4.85800052 -2.70616540
57 -5.97594132 -4.85800052
58 1.03642778 -5.97594132
59 2.89997915 1.03642778
> 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/7k6621261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/87wvr1261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91ot21261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10tgng1261145091.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/111u3i1261145091.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/120q9a1261145091.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/1367jd1261145091.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/14oqz81261145091.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/155swc1261145091.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/165z2e1261145091.tab")
+ }
>
> try(system("convert tmp/1rygz1261145091.ps tmp/1rygz1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wxqh1261145091.ps tmp/2wxqh1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bsgl1261145091.ps tmp/3bsgl1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ualr1261145091.ps tmp/4ualr1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/5i2i71261145091.ps tmp/5i2i71261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/6zpjk1261145091.ps tmp/6zpjk1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/7k6621261145091.ps tmp/7k6621261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/87wvr1261145091.ps tmp/87wvr1261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/91ot21261145091.ps tmp/91ot21261145091.png",intern=TRUE))
character(0)
> try(system("convert tmp/10tgng1261145091.ps tmp/10tgng1261145091.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.585 1.644 24.210