R version 2.7.2 (2008-08-25)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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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(69.97
+ ,6911
+ ,8488
+ ,72.13
+ ,7030.6
+ ,10900
+ ,78.27
+ ,7115.1
+ ,10456
+ ,80.31
+ ,7232.2
+ ,18508
+ ,79.06
+ ,7298.3
+ ,12880
+ ,78.98
+ ,7337.7
+ ,14034
+ ,87.35
+ ,7432.1
+ ,12419
+ ,86.16
+ ,7522.5
+ ,17256
+ ,88.71
+ ,7624.1
+ ,10407
+ ,90.16
+ ,7776.6
+ ,12245
+ ,94.09
+ ,7866.2
+ ,13394
+ ,93.57
+ ,8000.4
+ ,18333
+ ,96.73
+ ,8113.8
+ ,14076
+ ,94.67
+ ,8250.4
+ ,15359
+ ,101.05
+ ,8381.9
+ ,16592
+ ,105.16
+ ,8471.2
+ ,19188
+ ,105.27
+ ,8586.7
+ ,15428
+ ,104.88
+ ,8657.9
+ ,15564
+ ,107.11
+ ,8789.5
+ ,15451
+ ,99.41
+ ,8953.8
+ ,19825
+ ,101.37
+ ,9066.6
+ ,14813
+ ,98.86
+ ,9174.1
+ ,15309
+ ,100.64
+ ,9313.5
+ ,18573
+ ,97.16
+ ,9519.5
+ ,20255
+ ,98.1
+ ,9629.4
+ ,20138
+ ,96.79
+ ,9822.8
+ ,22204
+ ,102.71
+ ,9862.1
+ ,22981
+ ,102.95
+ ,9953.6
+ ,21986
+ ,104.07
+ ,10021.5
+ ,23139
+ ,104.31
+ ,10128.9
+ ,22081
+ ,105.02
+ ,10135.1
+ ,23989
+ ,106.08
+ ,10226.3
+ ,24503
+ ,105.28
+ ,10333.3
+ ,23818
+ ,99.36
+ ,10426.6
+ ,26013
+ ,101.53
+ ,10527.4
+ ,31911
+ ,99.32
+ ,10591.1
+ ,31889
+ ,96.91
+ ,10705.6
+ ,32091
+ ,92.65
+ ,10831.8
+ ,34476
+ ,95.7
+ ,11086.1
+ ,41941
+ ,93.2
+ ,11219.5
+ ,48062
+ ,91.93
+ ,11405.5
+ ,45848
+ ,92.24
+ ,11610.3
+ ,50496
+ ,95.32
+ ,11779.4
+ ,55803
+ ,88.72
+ ,11948.5
+ ,63784
+ ,87.99
+ ,12155.4
+ ,60869
+ ,89.2
+ ,12297.5
+ ,65960
+ ,93.78
+ ,12538.2
+ ,70186
+ ,94.99
+ ,12696.4
+ ,75412
+ ,92.9
+ ,12959.6
+ ,78046
+ ,90.61
+ ,13134.1
+ ,81311
+ ,94.26
+ ,13249.6
+ ,91629
+ ,94.17
+ ,13370.1
+ ,94094
+ ,94.81
+ ,13510.9
+ ,83424
+ ,95.77
+ ,13737.5
+ ,103268
+ ,99.4
+ ,13950.6
+ ,112481
+ ,98.76
+ ,14031.2
+ ,114416
+ ,99.37
+ ,14150.8
+ ,108963
+ ,101.02
+ ,14294.5
+ ,121533)
+ ,dim=c(3
+ ,58)
+ ,dimnames=list(c('reer'
+ ,'GDP'
+ ,'exp')
+ ,1:58))
> y <- array(NA,dim=c(3,58),dimnames=list(c('reer','GDP','exp'),1:58))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Quarterly Dummies'
> par1 = '3'
> #'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
exp reer GDP Q1 Q2 Q3 t
1 8488 69.97 6911.0 1 0 0 1
2 10900 72.13 7030.6 0 1 0 2
3 10456 78.27 7115.1 0 0 1 3
4 18508 80.31 7232.2 0 0 0 4
5 12880 79.06 7298.3 1 0 0 5
6 14034 78.98 7337.7 0 1 0 6
7 12419 87.35 7432.1 0 0 1 7
8 17256 86.16 7522.5 0 0 0 8
9 10407 88.71 7624.1 1 0 0 9
10 12245 90.16 7776.6 0 1 0 10
11 13394 94.09 7866.2 0 0 1 11
12 18333 93.57 8000.4 0 0 0 12
13 14076 96.73 8113.8 1 0 0 13
14 15359 94.67 8250.4 0 1 0 14
15 16592 101.05 8381.9 0 0 1 15
16 19188 105.16 8471.2 0 0 0 16
17 15428 105.27 8586.7 1 0 0 17
18 15564 104.88 8657.9 0 1 0 18
19 15451 107.11 8789.5 0 0 1 19
20 19825 99.41 8953.8 0 0 0 20
21 14813 101.37 9066.6 1 0 0 21
22 15309 98.86 9174.1 0 1 0 22
23 18573 100.64 9313.5 0 0 1 23
24 20255 97.16 9519.5 0 0 0 24
25 20138 98.10 9629.4 1 0 0 25
26 22204 96.79 9822.8 0 1 0 26
27 22981 102.71 9862.1 0 0 1 27
28 21986 102.95 9953.6 0 0 0 28
29 23139 104.07 10021.5 1 0 0 29
30 22081 104.31 10128.9 0 1 0 30
31 23989 105.02 10135.1 0 0 1 31
32 24503 106.08 10226.3 0 0 0 32
33 23818 105.28 10333.3 1 0 0 33
34 26013 99.36 10426.6 0 1 0 34
35 31911 101.53 10527.4 0 0 1 35
36 31889 99.32 10591.1 0 0 0 36
37 32091 96.91 10705.6 1 0 0 37
38 34476 92.65 10831.8 0 1 0 38
39 41941 95.70 11086.1 0 0 1 39
40 48062 93.20 11219.5 0 0 0 40
41 45848 91.93 11405.5 1 0 0 41
42 50496 92.24 11610.3 0 1 0 42
43 55803 95.32 11779.4 0 0 1 43
44 63784 88.72 11948.5 0 0 0 44
45 60869 87.99 12155.4 1 0 0 45
46 65960 89.20 12297.5 0 1 0 46
47 70186 93.78 12538.2 0 0 1 47
48 75412 94.99 12696.4 0 0 0 48
49 78046 92.90 12959.6 1 0 0 49
50 81311 90.61 13134.1 0 1 0 50
51 91629 94.26 13249.6 0 0 1 51
52 94094 94.17 13370.1 0 0 0 52
53 83424 94.81 13510.9 1 0 0 53
54 103268 95.77 13737.5 0 1 0 54
55 112481 99.40 13950.6 0 0 1 55
56 114416 98.76 14031.2 0 0 0 56
57 108963 99.37 14150.8 1 0 0 57
58 121533 101.02 14294.5 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) reer GDP Q1 Q2 Q3
-299135.53 -323.77 49.84 -5204.27 -3671.18 -1741.21
t
-4652.51
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-12219.4 -4000.7 843.5 4165.2 14505.8
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.991e+05 2.780e+04 -10.762 9.95e-15 ***
reer -3.238e+02 1.102e+02 -2.939 0.00493 **
GDP 4.984e+01 3.418e+00 14.580 < 2e-16 ***
Q1 -5.204e+03 2.138e+03 -2.435 0.01844 *
Q2 -3.671e+03 2.144e+03 -1.712 0.09299 .
Q3 -1.741e+03 2.175e+03 -0.800 0.42717
t -4.653e+03 4.507e+02 -10.322 4.33e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5739 on 51 degrees of freedom
Multiple R-squared: 0.9718, Adjusted R-squared: 0.9684
F-statistic: 292.5 on 6 and 51 DF, p-value: < 2.2e-16
> 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,] 6.125692e-02 1.225138e-01 0.9387431
[2,] 1.874784e-02 3.749569e-02 0.9812522
[3,] 6.766528e-03 1.353306e-02 0.9932335
[4,] 3.030364e-03 6.060728e-03 0.9969696
[5,] 1.060274e-03 2.120548e-03 0.9989397
[6,] 4.315577e-04 8.631155e-04 0.9995684
[7,] 2.482624e-04 4.965248e-04 0.9997517
[8,] 1.302212e-04 2.604425e-04 0.9998698
[9,] 7.747027e-05 1.549405e-04 0.9999225
[10,] 5.117280e-05 1.023456e-04 0.9999488
[11,] 4.513619e-05 9.027238e-05 0.9999549
[12,] 3.007120e-05 6.014240e-05 0.9999699
[13,] 1.665287e-05 3.330574e-05 0.9999833
[14,] 3.211323e-05 6.422647e-05 0.9999679
[15,] 1.826256e-05 3.652513e-05 0.9999817
[16,] 1.873190e-04 3.746380e-04 0.9998127
[17,] 3.594577e-04 7.189154e-04 0.9996405
[18,] 6.364545e-04 1.272909e-03 0.9993635
[19,] 4.970567e-04 9.941133e-04 0.9995029
[20,] 4.561714e-03 9.123428e-03 0.9954383
[21,] 3.182905e-03 6.365810e-03 0.9968171
[22,] 3.442301e-03 6.884603e-03 0.9965577
[23,] 1.897682e-03 3.795364e-03 0.9981023
[24,] 1.438326e-03 2.876651e-03 0.9985617
[25,] 9.558025e-04 1.911605e-03 0.9990442
[26,] 3.750682e-03 7.501365e-03 0.9962493
[27,] 2.308578e-03 4.617156e-03 0.9976914
[28,] 2.466920e-03 4.933841e-03 0.9975331
[29,] 1.878566e-03 3.757133e-03 0.9981214
[30,] 1.584789e-02 3.169579e-02 0.9841521
[31,] 6.069302e-02 1.213860e-01 0.9393070
[32,] 1.393609e-01 2.787219e-01 0.8606391
[33,] 2.085349e-01 4.170698e-01 0.7914651
[34,] 2.496322e-01 4.992645e-01 0.7503678
[35,] 3.130688e-01 6.261376e-01 0.6869312
[36,] 5.814458e-01 8.371085e-01 0.4185542
[37,] 7.769414e-01 4.461171e-01 0.2230586
[38,] 6.566282e-01 6.867436e-01 0.3433718
[39,] 7.741576e-01 4.516849e-01 0.2258424
> postscript(file="/var/www/html/rcomp/tmp/1zlnr1225638108.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20vwu1225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3v05e1225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/438d51225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5wr7l1225638108.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 = 58
Frequency = 1
1 2 3 4 5 6
-4284.84358 -4014.51681 -3959.19603 1828.75230 2358.62735 4642.58414
7 8 9 10 11 12
3755.53805 6613.33225 5383.35146 3210.18093 3888.79763 4882.68420
13 14 15 16 17 18
5854.13508 2781.92057 2249.63476 4637.24586 5013.53263 4594.32139
19 20 21 22 23 24
1367.39405 -2028.48590 -2170.66075 -4725.33305 -5109.68237 -11909.41936
25 26 27 28 29 30
-7342.31701 -12219.41089 -8761.71362 -11327.74412 -3339.23266 -6552.54561
31 32 33 34 35 36
-2001.11983 -2777.70555 802.55744 -449.50346 3850.10479 2849.28318
37 38 39 40 41 42
6421.49846 4257.28223 2758.91904 4333.60423 2295.61612 -43.10079
43 44 45 46 47 48
556.31286 884.36834 -2721.36370 -1200.94090 -4765.15601 -4120.21645
49 50 51 52 53 54
-5423.07063 -8476.55355 -10.35676 -668.48875 -8291.46392 3689.83748
55 56 57 58
6180.52345 6802.78979 5443.63370 14505.77833
> postscript(file="/var/www/html/rcomp/tmp/6co581225638108.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -4284.84358 NA
1 -4014.51681 -4284.84358
2 -3959.19603 -4014.51681
3 1828.75230 -3959.19603
4 2358.62735 1828.75230
5 4642.58414 2358.62735
6 3755.53805 4642.58414
7 6613.33225 3755.53805
8 5383.35146 6613.33225
9 3210.18093 5383.35146
10 3888.79763 3210.18093
11 4882.68420 3888.79763
12 5854.13508 4882.68420
13 2781.92057 5854.13508
14 2249.63476 2781.92057
15 4637.24586 2249.63476
16 5013.53263 4637.24586
17 4594.32139 5013.53263
18 1367.39405 4594.32139
19 -2028.48590 1367.39405
20 -2170.66075 -2028.48590
21 -4725.33305 -2170.66075
22 -5109.68237 -4725.33305
23 -11909.41936 -5109.68237
24 -7342.31701 -11909.41936
25 -12219.41089 -7342.31701
26 -8761.71362 -12219.41089
27 -11327.74412 -8761.71362
28 -3339.23266 -11327.74412
29 -6552.54561 -3339.23266
30 -2001.11983 -6552.54561
31 -2777.70555 -2001.11983
32 802.55744 -2777.70555
33 -449.50346 802.55744
34 3850.10479 -449.50346
35 2849.28318 3850.10479
36 6421.49846 2849.28318
37 4257.28223 6421.49846
38 2758.91904 4257.28223
39 4333.60423 2758.91904
40 2295.61612 4333.60423
41 -43.10079 2295.61612
42 556.31286 -43.10079
43 884.36834 556.31286
44 -2721.36370 884.36834
45 -1200.94090 -2721.36370
46 -4765.15601 -1200.94090
47 -4120.21645 -4765.15601
48 -5423.07063 -4120.21645
49 -8476.55355 -5423.07063
50 -10.35676 -8476.55355
51 -668.48875 -10.35676
52 -8291.46392 -668.48875
53 3689.83748 -8291.46392
54 6180.52345 3689.83748
55 6802.78979 6180.52345
56 5443.63370 6802.78979
57 14505.77833 5443.63370
58 NA 14505.77833
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4014.51681 -4284.84358
[2,] -3959.19603 -4014.51681
[3,] 1828.75230 -3959.19603
[4,] 2358.62735 1828.75230
[5,] 4642.58414 2358.62735
[6,] 3755.53805 4642.58414
[7,] 6613.33225 3755.53805
[8,] 5383.35146 6613.33225
[9,] 3210.18093 5383.35146
[10,] 3888.79763 3210.18093
[11,] 4882.68420 3888.79763
[12,] 5854.13508 4882.68420
[13,] 2781.92057 5854.13508
[14,] 2249.63476 2781.92057
[15,] 4637.24586 2249.63476
[16,] 5013.53263 4637.24586
[17,] 4594.32139 5013.53263
[18,] 1367.39405 4594.32139
[19,] -2028.48590 1367.39405
[20,] -2170.66075 -2028.48590
[21,] -4725.33305 -2170.66075
[22,] -5109.68237 -4725.33305
[23,] -11909.41936 -5109.68237
[24,] -7342.31701 -11909.41936
[25,] -12219.41089 -7342.31701
[26,] -8761.71362 -12219.41089
[27,] -11327.74412 -8761.71362
[28,] -3339.23266 -11327.74412
[29,] -6552.54561 -3339.23266
[30,] -2001.11983 -6552.54561
[31,] -2777.70555 -2001.11983
[32,] 802.55744 -2777.70555
[33,] -449.50346 802.55744
[34,] 3850.10479 -449.50346
[35,] 2849.28318 3850.10479
[36,] 6421.49846 2849.28318
[37,] 4257.28223 6421.49846
[38,] 2758.91904 4257.28223
[39,] 4333.60423 2758.91904
[40,] 2295.61612 4333.60423
[41,] -43.10079 2295.61612
[42,] 556.31286 -43.10079
[43,] 884.36834 556.31286
[44,] -2721.36370 884.36834
[45,] -1200.94090 -2721.36370
[46,] -4765.15601 -1200.94090
[47,] -4120.21645 -4765.15601
[48,] -5423.07063 -4120.21645
[49,] -8476.55355 -5423.07063
[50,] -10.35676 -8476.55355
[51,] -668.48875 -10.35676
[52,] -8291.46392 -668.48875
[53,] 3689.83748 -8291.46392
[54,] 6180.52345 3689.83748
[55,] 6802.78979 6180.52345
[56,] 5443.63370 6802.78979
[57,] 14505.77833 5443.63370
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4014.51681 -4284.84358
2 -3959.19603 -4014.51681
3 1828.75230 -3959.19603
4 2358.62735 1828.75230
5 4642.58414 2358.62735
6 3755.53805 4642.58414
7 6613.33225 3755.53805
8 5383.35146 6613.33225
9 3210.18093 5383.35146
10 3888.79763 3210.18093
11 4882.68420 3888.79763
12 5854.13508 4882.68420
13 2781.92057 5854.13508
14 2249.63476 2781.92057
15 4637.24586 2249.63476
16 5013.53263 4637.24586
17 4594.32139 5013.53263
18 1367.39405 4594.32139
19 -2028.48590 1367.39405
20 -2170.66075 -2028.48590
21 -4725.33305 -2170.66075
22 -5109.68237 -4725.33305
23 -11909.41936 -5109.68237
24 -7342.31701 -11909.41936
25 -12219.41089 -7342.31701
26 -8761.71362 -12219.41089
27 -11327.74412 -8761.71362
28 -3339.23266 -11327.74412
29 -6552.54561 -3339.23266
30 -2001.11983 -6552.54561
31 -2777.70555 -2001.11983
32 802.55744 -2777.70555
33 -449.50346 802.55744
34 3850.10479 -449.50346
35 2849.28318 3850.10479
36 6421.49846 2849.28318
37 4257.28223 6421.49846
38 2758.91904 4257.28223
39 4333.60423 2758.91904
40 2295.61612 4333.60423
41 -43.10079 2295.61612
42 556.31286 -43.10079
43 884.36834 556.31286
44 -2721.36370 884.36834
45 -1200.94090 -2721.36370
46 -4765.15601 -1200.94090
47 -4120.21645 -4765.15601
48 -5423.07063 -4120.21645
49 -8476.55355 -5423.07063
50 -10.35676 -8476.55355
51 -668.48875 -10.35676
52 -8291.46392 -668.48875
53 3689.83748 -8291.46392
54 6180.52345 3689.83748
55 6802.78979 6180.52345
56 5443.63370 6802.78979
57 14505.77833 5443.63370
> 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/7qh261225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8grti1225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9si6y1225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ie6w1225638108.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11rs2m1225638108.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/1202291225638108.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/13p2in1225638108.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/140ww91225638108.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/1526e51225638108.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/16jmzs1225638108.tab")
+ }
>
> system("convert tmp/1zlnr1225638108.ps tmp/1zlnr1225638108.png")
> system("convert tmp/20vwu1225638108.ps tmp/20vwu1225638108.png")
> system("convert tmp/3v05e1225638108.ps tmp/3v05e1225638108.png")
> system("convert tmp/438d51225638108.ps tmp/438d51225638108.png")
> system("convert tmp/5wr7l1225638108.ps tmp/5wr7l1225638108.png")
> system("convert tmp/6co581225638108.ps tmp/6co581225638108.png")
> system("convert tmp/7qh261225638108.ps tmp/7qh261225638108.png")
> system("convert tmp/8grti1225638108.ps tmp/8grti1225638108.png")
> system("convert tmp/9si6y1225638108.ps tmp/9si6y1225638108.png")
> system("convert tmp/10ie6w1225638108.ps tmp/10ie6w1225638108.png")
>
>
> proc.time()
user system elapsed
2.847 1.641 5.663