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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(474605,0,470390,0,461251,0,454724,0,455626,0,516847,0,525192,0,522975,0,518585,0,509239,0,512238,0,519164,0,517009,0,509933,0,509127,0,500875,0,506971,0,569323,0,579714,0,577992,0,565644,0,547344,0,554788,0,562325,0,560854,0,555332,0,543599,0,536662,0,542722,0,593530,0,610763,0,612613,0,611324,0,594167,0,595454,0,590865,0,589379,0,584428,0,573100,0,567456,0,569028,0,620735,0,628884,0,628232,0,612117,0,595404,0,597141,0,593408,0,590072,0,579799,0,574205,0,572775,0,572942,0,619567,0,625809,0,619916,0,587625,0,565724,0,557274,0,560576,0,548854,0,531673,0,525919,0,511038,0,498662,0,555362,0,564591,0,541667,0,527070,0,509846,0,514258,0,516922,0,507561,0,492622,0,490243,0,469357,0,477580,0,528379,0,533590,0,517945,1,506174,1,501866,1,516441,1,528222,1,532638,1),dim=c(2,85),dimnames=list(c('Werkzoekend','Crisis'),1:85))
> y <- array(NA,dim=c(2,85),dimnames=list(c('Werkzoekend','Crisis'),1:85))
> 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
Werkzoekend Crisis
1 474605 0
2 470390 0
3 461251 0
4 454724 0
5 455626 0
6 516847 0
7 525192 0
8 522975 0
9 518585 0
10 509239 0
11 512238 0
12 519164 0
13 517009 0
14 509933 0
15 509127 0
16 500875 0
17 506971 0
18 569323 0
19 579714 0
20 577992 0
21 565644 0
22 547344 0
23 554788 0
24 562325 0
25 560854 0
26 555332 0
27 543599 0
28 536662 0
29 542722 0
30 593530 0
31 610763 0
32 612613 0
33 611324 0
34 594167 0
35 595454 0
36 590865 0
37 589379 0
38 584428 0
39 573100 0
40 567456 0
41 569028 0
42 620735 0
43 628884 0
44 628232 0
45 612117 0
46 595404 0
47 597141 0
48 593408 0
49 590072 0
50 579799 0
51 574205 0
52 572775 0
53 572942 0
54 619567 0
55 625809 0
56 619916 0
57 587625 0
58 565724 0
59 557274 0
60 560576 0
61 548854 0
62 531673 0
63 525919 0
64 511038 0
65 498662 0
66 555362 0
67 564591 0
68 541667 0
69 527070 0
70 509846 0
71 514258 0
72 516922 0
73 507561 0
74 492622 0
75 490243 0
76 469357 0
77 477580 0
78 528379 0
79 533590 0
80 517945 1
81 506174 1
82 501866 1
83 516441 1
84 528222 1
85 532638 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Crisis
549627 -32413
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-94903 -32705 5161 30172 79257
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 549627 4944 111.160 <2e-16 ***
Crisis -32413 18610 -1.742 0.0853 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 43950 on 83 degrees of freedom
Multiple R-squared: 0.03526, Adjusted R-squared: 0.02363
F-statistic: 3.033 on 1 and 83 DF, p-value: 0.08527
> 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,] 0.02325514 0.0465102882 0.9767448559
[2,] 0.21937802 0.4387560336 0.7806219832
[3,] 0.34444049 0.6888809704 0.6555595148
[4,] 0.36688453 0.7337690599 0.6331154700
[5,] 0.33598494 0.6719698767 0.6640150617
[6,] 0.27133995 0.5426798958 0.7286600521
[7,] 0.21991951 0.4398390159 0.7800804921
[8,] 0.18753582 0.3750716368 0.8124641816
[9,] 0.15264413 0.3052882601 0.8473558700
[10,] 0.11594214 0.2318842889 0.8840578555
[11,] 0.08687852 0.1737570389 0.9131214805
[12,] 0.06454551 0.1290910142 0.9354544929
[13,] 0.04795771 0.0959154157 0.9520422921
[14,] 0.14714243 0.2942848660 0.8528575670
[15,] 0.31495096 0.6299019130 0.6850490435
[16,] 0.44598986 0.8919797216 0.5540101392
[17,] 0.48416383 0.9683276656 0.5158361672
[18,] 0.45403680 0.9080736056 0.5459631972
[19,] 0.43723705 0.8744741080 0.5627629460
[20,] 0.43509240 0.8701848018 0.5649075991
[21,] 0.42180501 0.8436100154 0.5781949923
[22,] 0.39158674 0.7831734825 0.6084132588
[23,] 0.34453026 0.6890605237 0.6554697381
[24,] 0.29654080 0.5930815934 0.7034592033
[25,] 0.25436453 0.5087290519 0.7456354741
[26,] 0.32767174 0.6553434808 0.6723282596
[27,] 0.47093031 0.9418606222 0.5290696889
[28,] 0.59976417 0.8004716585 0.4002358292
[29,] 0.69484289 0.6103142181 0.3051571090
[30,] 0.71393896 0.5721220783 0.2860610392
[31,] 0.73109920 0.5378016056 0.2689008028
[32,] 0.73262561 0.5347487750 0.2673743875
[33,] 0.72814617 0.5437076539 0.2718538269
[34,] 0.71125117 0.5774976639 0.2887488320
[35,] 0.67330382 0.6533923613 0.3266961806
[36,] 0.62568950 0.7486209903 0.3743104952
[37,] 0.57748233 0.8450353490 0.4225176745
[38,] 0.67019241 0.6596151759 0.3298075879
[39,] 0.78161426 0.4367714875 0.2183857437
[40,] 0.86693229 0.2661354162 0.1330677081
[41,] 0.89851038 0.2029792482 0.1014896241
[42,] 0.90182086 0.1963582792 0.0981791396
[43,] 0.90862977 0.1827404631 0.0913702315
[44,] 0.91179934 0.1764013119 0.0882006559
[45,] 0.91232914 0.1753417285 0.0876708642
[46,] 0.90257345 0.1948530983 0.0974265492
[47,] 0.88710691 0.2257861776 0.1128930888
[48,] 0.86938912 0.2612217571 0.1306108785
[49,] 0.85126894 0.2974621177 0.1487310588
[50,] 0.92822313 0.1435537376 0.0717768688
[51,] 0.98303491 0.0339301813 0.0169650906
[52,] 0.99808867 0.0038226588 0.0019113294
[53,] 0.99936686 0.0012662789 0.0006331394
[54,] 0.99951793 0.0009641497 0.0004820748
[55,] 0.99953812 0.0009237509 0.0004618755
[56,] 0.99967024 0.0006595174 0.0003297587
[57,] 0.99964927 0.0007014555 0.0003507277
[58,] 0.99941128 0.0011774316 0.0005887158
[59,] 0.99895344 0.0020931255 0.0010465627
[60,] 0.99816645 0.0036670982 0.0018335491
[61,] 0.99744155 0.0051168970 0.0025584485
[62,] 0.99815056 0.0036988796 0.0018494398
[63,] 0.99960115 0.0007977100 0.0003988550
[64,] 0.99972592 0.0005481502 0.0002740751
[65,] 0.99962634 0.0007473274 0.0003736637
[66,] 0.99917752 0.0016449638 0.0008224819
[67,] 0.99836723 0.0032655473 0.0016327736
[68,] 0.99713612 0.0057277570 0.0028638785
[69,] 0.99410308 0.0117938433 0.0058969217
[70,] 0.98829605 0.0234078920 0.0117039460
[71,] 0.97848106 0.0430378846 0.0215189423
[72,] 0.98843526 0.0231294800 0.0115647400
[73,] 0.99919328 0.0016134464 0.0008067232
[74,] 0.99663608 0.0067278337 0.0033639169
[75,] 0.98636617 0.0272676545 0.0136338273
[76,] 0.94999121 0.1000175713 0.0500087857
> postscript(file="/var/www/html/rcomp/tmp/1jcr21258750534.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2uy5j1258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vbl41258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4oysb1258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5slv71258750534.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 = 85
Frequency = 1
1 2 3 4 5 6
-75022.2911 -79237.2911 -88376.2911 -94903.2911 -94001.2911 -32780.2911
7 8 9 10 11 12
-24435.2911 -26652.2911 -31042.2911 -40388.2911 -37389.2911 -30463.2911
13 14 15 16 17 18
-32618.2911 -39694.2911 -40500.2911 -48752.2911 -42656.2911 19695.7089
19 20 21 22 23 24
30086.7089 28364.7089 16016.7089 -2283.2911 5160.7089 12697.7089
25 26 27 28 29 30
11226.7089 5704.7089 -6028.2911 -12965.2911 -6905.2911 43902.7089
31 32 33 34 35 36
61135.7089 62985.7089 61696.7089 44539.7089 45826.7089 41237.7089
37 38 39 40 41 42
39751.7089 34800.7089 23472.7089 17828.7089 19400.7089 71107.7089
43 44 45 46 47 48
79256.7089 78604.7089 62489.7089 45776.7089 47513.7089 43780.7089
49 50 51 52 53 54
40444.7089 30171.7089 24577.7089 23147.7089 23314.7089 69939.7089
55 56 57 58 59 60
76181.7089 70288.7089 37997.7089 16096.7089 7646.7089 10948.7089
61 62 63 64 65 66
-773.2911 -17954.2911 -23708.2911 -38589.2911 -50965.2911 5734.7089
67 68 69 70 71 72
14963.7089 -7960.2911 -22557.2911 -39781.2911 -35369.2911 -32705.2911
73 74 75 76 77 78
-42066.2911 -57005.2911 -59384.2911 -80270.2911 -72047.2911 -21248.2911
79 80 81 82 83 84
-16037.2911 730.6667 -11040.3333 -15348.3333 -773.3333 11007.6667
85
15423.6667
> postscript(file="/var/www/html/rcomp/tmp/6959i1258750534.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 = 85
Frequency = 1
lag(myerror, k = 1) myerror
0 -75022.2911 NA
1 -79237.2911 -75022.2911
2 -88376.2911 -79237.2911
3 -94903.2911 -88376.2911
4 -94001.2911 -94903.2911
5 -32780.2911 -94001.2911
6 -24435.2911 -32780.2911
7 -26652.2911 -24435.2911
8 -31042.2911 -26652.2911
9 -40388.2911 -31042.2911
10 -37389.2911 -40388.2911
11 -30463.2911 -37389.2911
12 -32618.2911 -30463.2911
13 -39694.2911 -32618.2911
14 -40500.2911 -39694.2911
15 -48752.2911 -40500.2911
16 -42656.2911 -48752.2911
17 19695.7089 -42656.2911
18 30086.7089 19695.7089
19 28364.7089 30086.7089
20 16016.7089 28364.7089
21 -2283.2911 16016.7089
22 5160.7089 -2283.2911
23 12697.7089 5160.7089
24 11226.7089 12697.7089
25 5704.7089 11226.7089
26 -6028.2911 5704.7089
27 -12965.2911 -6028.2911
28 -6905.2911 -12965.2911
29 43902.7089 -6905.2911
30 61135.7089 43902.7089
31 62985.7089 61135.7089
32 61696.7089 62985.7089
33 44539.7089 61696.7089
34 45826.7089 44539.7089
35 41237.7089 45826.7089
36 39751.7089 41237.7089
37 34800.7089 39751.7089
38 23472.7089 34800.7089
39 17828.7089 23472.7089
40 19400.7089 17828.7089
41 71107.7089 19400.7089
42 79256.7089 71107.7089
43 78604.7089 79256.7089
44 62489.7089 78604.7089
45 45776.7089 62489.7089
46 47513.7089 45776.7089
47 43780.7089 47513.7089
48 40444.7089 43780.7089
49 30171.7089 40444.7089
50 24577.7089 30171.7089
51 23147.7089 24577.7089
52 23314.7089 23147.7089
53 69939.7089 23314.7089
54 76181.7089 69939.7089
55 70288.7089 76181.7089
56 37997.7089 70288.7089
57 16096.7089 37997.7089
58 7646.7089 16096.7089
59 10948.7089 7646.7089
60 -773.2911 10948.7089
61 -17954.2911 -773.2911
62 -23708.2911 -17954.2911
63 -38589.2911 -23708.2911
64 -50965.2911 -38589.2911
65 5734.7089 -50965.2911
66 14963.7089 5734.7089
67 -7960.2911 14963.7089
68 -22557.2911 -7960.2911
69 -39781.2911 -22557.2911
70 -35369.2911 -39781.2911
71 -32705.2911 -35369.2911
72 -42066.2911 -32705.2911
73 -57005.2911 -42066.2911
74 -59384.2911 -57005.2911
75 -80270.2911 -59384.2911
76 -72047.2911 -80270.2911
77 -21248.2911 -72047.2911
78 -16037.2911 -21248.2911
79 730.6667 -16037.2911
80 -11040.3333 730.6667
81 -15348.3333 -11040.3333
82 -773.3333 -15348.3333
83 11007.6667 -773.3333
84 15423.6667 11007.6667
85 NA 15423.6667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -79237.2911 -75022.2911
[2,] -88376.2911 -79237.2911
[3,] -94903.2911 -88376.2911
[4,] -94001.2911 -94903.2911
[5,] -32780.2911 -94001.2911
[6,] -24435.2911 -32780.2911
[7,] -26652.2911 -24435.2911
[8,] -31042.2911 -26652.2911
[9,] -40388.2911 -31042.2911
[10,] -37389.2911 -40388.2911
[11,] -30463.2911 -37389.2911
[12,] -32618.2911 -30463.2911
[13,] -39694.2911 -32618.2911
[14,] -40500.2911 -39694.2911
[15,] -48752.2911 -40500.2911
[16,] -42656.2911 -48752.2911
[17,] 19695.7089 -42656.2911
[18,] 30086.7089 19695.7089
[19,] 28364.7089 30086.7089
[20,] 16016.7089 28364.7089
[21,] -2283.2911 16016.7089
[22,] 5160.7089 -2283.2911
[23,] 12697.7089 5160.7089
[24,] 11226.7089 12697.7089
[25,] 5704.7089 11226.7089
[26,] -6028.2911 5704.7089
[27,] -12965.2911 -6028.2911
[28,] -6905.2911 -12965.2911
[29,] 43902.7089 -6905.2911
[30,] 61135.7089 43902.7089
[31,] 62985.7089 61135.7089
[32,] 61696.7089 62985.7089
[33,] 44539.7089 61696.7089
[34,] 45826.7089 44539.7089
[35,] 41237.7089 45826.7089
[36,] 39751.7089 41237.7089
[37,] 34800.7089 39751.7089
[38,] 23472.7089 34800.7089
[39,] 17828.7089 23472.7089
[40,] 19400.7089 17828.7089
[41,] 71107.7089 19400.7089
[42,] 79256.7089 71107.7089
[43,] 78604.7089 79256.7089
[44,] 62489.7089 78604.7089
[45,] 45776.7089 62489.7089
[46,] 47513.7089 45776.7089
[47,] 43780.7089 47513.7089
[48,] 40444.7089 43780.7089
[49,] 30171.7089 40444.7089
[50,] 24577.7089 30171.7089
[51,] 23147.7089 24577.7089
[52,] 23314.7089 23147.7089
[53,] 69939.7089 23314.7089
[54,] 76181.7089 69939.7089
[55,] 70288.7089 76181.7089
[56,] 37997.7089 70288.7089
[57,] 16096.7089 37997.7089
[58,] 7646.7089 16096.7089
[59,] 10948.7089 7646.7089
[60,] -773.2911 10948.7089
[61,] -17954.2911 -773.2911
[62,] -23708.2911 -17954.2911
[63,] -38589.2911 -23708.2911
[64,] -50965.2911 -38589.2911
[65,] 5734.7089 -50965.2911
[66,] 14963.7089 5734.7089
[67,] -7960.2911 14963.7089
[68,] -22557.2911 -7960.2911
[69,] -39781.2911 -22557.2911
[70,] -35369.2911 -39781.2911
[71,] -32705.2911 -35369.2911
[72,] -42066.2911 -32705.2911
[73,] -57005.2911 -42066.2911
[74,] -59384.2911 -57005.2911
[75,] -80270.2911 -59384.2911
[76,] -72047.2911 -80270.2911
[77,] -21248.2911 -72047.2911
[78,] -16037.2911 -21248.2911
[79,] 730.6667 -16037.2911
[80,] -11040.3333 730.6667
[81,] -15348.3333 -11040.3333
[82,] -773.3333 -15348.3333
[83,] 11007.6667 -773.3333
[84,] 15423.6667 11007.6667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -79237.2911 -75022.2911
2 -88376.2911 -79237.2911
3 -94903.2911 -88376.2911
4 -94001.2911 -94903.2911
5 -32780.2911 -94001.2911
6 -24435.2911 -32780.2911
7 -26652.2911 -24435.2911
8 -31042.2911 -26652.2911
9 -40388.2911 -31042.2911
10 -37389.2911 -40388.2911
11 -30463.2911 -37389.2911
12 -32618.2911 -30463.2911
13 -39694.2911 -32618.2911
14 -40500.2911 -39694.2911
15 -48752.2911 -40500.2911
16 -42656.2911 -48752.2911
17 19695.7089 -42656.2911
18 30086.7089 19695.7089
19 28364.7089 30086.7089
20 16016.7089 28364.7089
21 -2283.2911 16016.7089
22 5160.7089 -2283.2911
23 12697.7089 5160.7089
24 11226.7089 12697.7089
25 5704.7089 11226.7089
26 -6028.2911 5704.7089
27 -12965.2911 -6028.2911
28 -6905.2911 -12965.2911
29 43902.7089 -6905.2911
30 61135.7089 43902.7089
31 62985.7089 61135.7089
32 61696.7089 62985.7089
33 44539.7089 61696.7089
34 45826.7089 44539.7089
35 41237.7089 45826.7089
36 39751.7089 41237.7089
37 34800.7089 39751.7089
38 23472.7089 34800.7089
39 17828.7089 23472.7089
40 19400.7089 17828.7089
41 71107.7089 19400.7089
42 79256.7089 71107.7089
43 78604.7089 79256.7089
44 62489.7089 78604.7089
45 45776.7089 62489.7089
46 47513.7089 45776.7089
47 43780.7089 47513.7089
48 40444.7089 43780.7089
49 30171.7089 40444.7089
50 24577.7089 30171.7089
51 23147.7089 24577.7089
52 23314.7089 23147.7089
53 69939.7089 23314.7089
54 76181.7089 69939.7089
55 70288.7089 76181.7089
56 37997.7089 70288.7089
57 16096.7089 37997.7089
58 7646.7089 16096.7089
59 10948.7089 7646.7089
60 -773.2911 10948.7089
61 -17954.2911 -773.2911
62 -23708.2911 -17954.2911
63 -38589.2911 -23708.2911
64 -50965.2911 -38589.2911
65 5734.7089 -50965.2911
66 14963.7089 5734.7089
67 -7960.2911 14963.7089
68 -22557.2911 -7960.2911
69 -39781.2911 -22557.2911
70 -35369.2911 -39781.2911
71 -32705.2911 -35369.2911
72 -42066.2911 -32705.2911
73 -57005.2911 -42066.2911
74 -59384.2911 -57005.2911
75 -80270.2911 -59384.2911
76 -72047.2911 -80270.2911
77 -21248.2911 -72047.2911
78 -16037.2911 -21248.2911
79 730.6667 -16037.2911
80 -11040.3333 730.6667
81 -15348.3333 -11040.3333
82 -773.3333 -15348.3333
83 11007.6667 -773.3333
84 15423.6667 11007.6667
> 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/77r361258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/87j1s1258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9lbcy1258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jj1p1258750534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mr3h1258750534.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/125at01258750534.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/13xtya1258750534.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/14warb1258750534.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/152nhu1258750534.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/16r8231258750534.tab")
+ }
>
> system("convert tmp/1jcr21258750534.ps tmp/1jcr21258750534.png")
> system("convert tmp/2uy5j1258750534.ps tmp/2uy5j1258750534.png")
> system("convert tmp/3vbl41258750534.ps tmp/3vbl41258750534.png")
> system("convert tmp/4oysb1258750534.ps tmp/4oysb1258750534.png")
> system("convert tmp/5slv71258750534.ps tmp/5slv71258750534.png")
> system("convert tmp/6959i1258750534.ps tmp/6959i1258750534.png")
> system("convert tmp/77r361258750534.ps tmp/77r361258750534.png")
> system("convert tmp/87j1s1258750534.ps tmp/87j1s1258750534.png")
> system("convert tmp/9lbcy1258750534.ps tmp/9lbcy1258750534.png")
> system("convert tmp/10jj1p1258750534.ps tmp/10jj1p1258750534.png")
>
>
> proc.time()
user system elapsed
2.703 1.566 3.220