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(43880
+ ,25222
+ ,43110
+ ,21333
+ ,44496
+ ,19778
+ ,44164
+ ,25943
+ ,40399
+ ,21698
+ ,36763
+ ,20077
+ ,37903
+ ,25673
+ ,35532
+ ,19094
+ ,35533
+ ,19306
+ ,32110
+ ,15443
+ ,33374
+ ,15179
+ ,35462
+ ,18288
+ ,33508
+ ,18264
+ ,36080
+ ,16406
+ ,34560
+ ,15678
+ ,38737
+ ,19657
+ ,38144
+ ,18821
+ ,37594
+ ,19493
+ ,36424
+ ,21078
+ ,36843
+ ,19296
+ ,37246
+ ,19985
+ ,38661
+ ,16972
+ ,40454
+ ,16951
+ ,44928
+ ,23126
+ ,48441
+ ,24890
+ ,48140
+ ,21042
+ ,45998
+ ,20842
+ ,47369
+ ,23904
+ ,49554
+ ,22578
+ ,47510
+ ,25452
+ ,44873
+ ,21928
+ ,45344
+ ,25227
+ ,42413
+ ,26210
+ ,36912
+ ,17436
+ ,43452
+ ,21258
+ ,42142
+ ,25638
+ ,44382
+ ,23516
+ ,43636
+ ,23891
+ ,44167
+ ,24617
+ ,44423
+ ,26174
+ ,42868
+ ,23339
+ ,43908
+ ,23660
+ ,42013
+ ,26500
+ ,38846
+ ,22469
+ ,35087
+ ,23163
+ ,33026
+ ,16170
+ ,34646
+ ,18267
+ ,37135
+ ,20561
+ ,37985
+ ,20372
+ ,43121
+ ,19017
+ ,43722
+ ,18242
+ ,43630
+ ,20937
+ ,42234
+ ,22065
+ ,39351
+ ,16731
+ ,39327
+ ,21943
+ ,35704
+ ,19254
+ ,30466
+ ,16397
+ ,28155
+ ,13644
+ ,29257
+ ,14375
+ ,29998
+ ,14814
+ ,32529
+ ,16061
+ ,34787
+ ,14784
+ ,33855
+ ,12824
+ ,34556
+ ,18282
+ ,31348
+ ,14936
+ ,30805
+ ,15701
+ ,28353
+ ,16394
+ ,24514
+ ,13085
+ ,21106
+ ,11431
+ ,21346
+ ,9334
+ ,23335
+ ,10921
+ ,24379
+ ,11725
+ ,26290
+ ,13077
+ ,30084
+ ,11794
+ ,29429
+ ,11047
+ ,30632
+ ,16797
+ ,27349
+ ,11482
+ ,27264
+ ,12657
+ ,27474
+ ,15277
+ ,24482
+ ,12385
+ ,21453
+ ,11996
+ ,18788
+ ,8395
+ ,19282
+ ,8928
+ ,19713
+ ,9937
+ ,21917
+ ,11468
+ ,23812
+ ,9554
+ ,23785
+ ,9226
+ ,24696
+ ,11021
+ ,24562
+ ,10065
+ ,23580
+ ,9939
+ ,24939
+ ,11179
+ ,23899
+ ,11943
+ ,21454
+ ,10792
+ ,19761
+ ,8080
+ ,19815
+ ,8603
+ ,20780
+ ,11561
+ ,23462
+ ,10449
+ ,25005
+ ,8197
+ ,24725
+ ,7602
+ ,26198
+ ,9521
+ ,27543
+ ,10412
+ ,26471
+ ,10860
+ ,26558
+ ,11538
+ ,25317
+ ,11420
+ ,22896
+ ,10408
+ ,22248
+ ,5998
+ ,23406
+ ,8356
+ ,25073
+ ,10569
+ ,27691
+ ,9660
+ ,30599
+ ,9304
+ ,31948
+ ,9114
+ ,32946
+ ,10492
+ ,34012
+ ,12388
+ ,32936
+ ,10003
+ ,32974
+ ,14029
+ ,30951
+ ,12452
+ ,29812
+ ,12332
+ ,29010
+ ,8064
+ ,31068
+ ,10931
+ ,32447
+ ,12631
+ ,34844
+ ,13656
+ ,35676
+ ,11005
+ ,35387
+ ,8879
+ ,36488
+ ,11536
+ ,35652
+ ,13698
+ ,33488
+ ,10853
+ ,32914
+ ,15107
+ ,29781
+ ,13604
+ ,27951
+ ,12231)
+ ,dim=c(2
+ ,129)
+ ,dimnames=list(c('OPENVAC'
+ ,'OntvangenJobs')
+ ,1:129))
> y <- array(NA,dim=c(2,129),dimnames=list(c('OPENVAC','OntvangenJobs'),1:129))
> 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 = 'Include Monthly 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
OPENVAC OntvangenJobs M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 43880 25222 1 0 0 0 0 0 0 0 0 0 0
2 43110 21333 0 1 0 0 0 0 0 0 0 0 0
3 44496 19778 0 0 1 0 0 0 0 0 0 0 0
4 44164 25943 0 0 0 1 0 0 0 0 0 0 0
5 40399 21698 0 0 0 0 1 0 0 0 0 0 0
6 36763 20077 0 0 0 0 0 1 0 0 0 0 0
7 37903 25673 0 0 0 0 0 0 1 0 0 0 0
8 35532 19094 0 0 0 0 0 0 0 1 0 0 0
9 35533 19306 0 0 0 0 0 0 0 0 1 0 0
10 32110 15443 0 0 0 0 0 0 0 0 0 1 0
11 33374 15179 0 0 0 0 0 0 0 0 0 0 1
12 35462 18288 0 0 0 0 0 0 0 0 0 0 0
13 33508 18264 1 0 0 0 0 0 0 0 0 0 0
14 36080 16406 0 1 0 0 0 0 0 0 0 0 0
15 34560 15678 0 0 1 0 0 0 0 0 0 0 0
16 38737 19657 0 0 0 1 0 0 0 0 0 0 0
17 38144 18821 0 0 0 0 1 0 0 0 0 0 0
18 37594 19493 0 0 0 0 0 1 0 0 0 0 0
19 36424 21078 0 0 0 0 0 0 1 0 0 0 0
20 36843 19296 0 0 0 0 0 0 0 1 0 0 0
21 37246 19985 0 0 0 0 0 0 0 0 1 0 0
22 38661 16972 0 0 0 0 0 0 0 0 0 1 0
23 40454 16951 0 0 0 0 0 0 0 0 0 0 1
24 44928 23126 0 0 0 0 0 0 0 0 0 0 0
25 48441 24890 1 0 0 0 0 0 0 0 0 0 0
26 48140 21042 0 1 0 0 0 0 0 0 0 0 0
27 45998 20842 0 0 1 0 0 0 0 0 0 0 0
28 47369 23904 0 0 0 1 0 0 0 0 0 0 0
29 49554 22578 0 0 0 0 1 0 0 0 0 0 0
30 47510 25452 0 0 0 0 0 1 0 0 0 0 0
31 44873 21928 0 0 0 0 0 0 1 0 0 0 0
32 45344 25227 0 0 0 0 0 0 0 1 0 0 0
33 42413 26210 0 0 0 0 0 0 0 0 1 0 0
34 36912 17436 0 0 0 0 0 0 0 0 0 1 0
35 43452 21258 0 0 0 0 0 0 0 0 0 0 1
36 42142 25638 0 0 0 0 0 0 0 0 0 0 0
37 44382 23516 1 0 0 0 0 0 0 0 0 0 0
38 43636 23891 0 1 0 0 0 0 0 0 0 0 0
39 44167 24617 0 0 1 0 0 0 0 0 0 0 0
40 44423 26174 0 0 0 1 0 0 0 0 0 0 0
41 42868 23339 0 0 0 0 1 0 0 0 0 0 0
42 43908 23660 0 0 0 0 0 1 0 0 0 0 0
43 42013 26500 0 0 0 0 0 0 1 0 0 0 0
44 38846 22469 0 0 0 0 0 0 0 1 0 0 0
45 35087 23163 0 0 0 0 0 0 0 0 1 0 0
46 33026 16170 0 0 0 0 0 0 0 0 0 1 0
47 34646 18267 0 0 0 0 0 0 0 0 0 0 1
48 37135 20561 0 0 0 0 0 0 0 0 0 0 0
49 37985 20372 1 0 0 0 0 0 0 0 0 0 0
50 43121 19017 0 1 0 0 0 0 0 0 0 0 0
51 43722 18242 0 0 1 0 0 0 0 0 0 0 0
52 43630 20937 0 0 0 1 0 0 0 0 0 0 0
53 42234 22065 0 0 0 0 1 0 0 0 0 0 0
54 39351 16731 0 0 0 0 0 1 0 0 0 0 0
55 39327 21943 0 0 0 0 0 0 1 0 0 0 0
56 35704 19254 0 0 0 0 0 0 0 1 0 0 0
57 30466 16397 0 0 0 0 0 0 0 0 1 0 0
58 28155 13644 0 0 0 0 0 0 0 0 0 1 0
59 29257 14375 0 0 0 0 0 0 0 0 0 0 1
60 29998 14814 0 0 0 0 0 0 0 0 0 0 0
61 32529 16061 1 0 0 0 0 0 0 0 0 0 0
62 34787 14784 0 1 0 0 0 0 0 0 0 0 0
63 33855 12824 0 0 1 0 0 0 0 0 0 0 0
64 34556 18282 0 0 0 1 0 0 0 0 0 0 0
65 31348 14936 0 0 0 0 1 0 0 0 0 0 0
66 30805 15701 0 0 0 0 0 1 0 0 0 0 0
67 28353 16394 0 0 0 0 0 0 1 0 0 0 0
68 24514 13085 0 0 0 0 0 0 0 1 0 0 0
69 21106 11431 0 0 0 0 0 0 0 0 1 0 0
70 21346 9334 0 0 0 0 0 0 0 0 0 1 0
71 23335 10921 0 0 0 0 0 0 0 0 0 0 1
72 24379 11725 0 0 0 0 0 0 0 0 0 0 0
73 26290 13077 1 0 0 0 0 0 0 0 0 0 0
74 30084 11794 0 1 0 0 0 0 0 0 0 0 0
75 29429 11047 0 0 1 0 0 0 0 0 0 0 0
76 30632 16797 0 0 0 1 0 0 0 0 0 0 0
77 27349 11482 0 0 0 0 1 0 0 0 0 0 0
78 27264 12657 0 0 0 0 0 1 0 0 0 0 0
79 27474 15277 0 0 0 0 0 0 1 0 0 0 0
80 24482 12385 0 0 0 0 0 0 0 1 0 0 0
81 21453 11996 0 0 0 0 0 0 0 0 1 0 0
82 18788 8395 0 0 0 0 0 0 0 0 0 1 0
83 19282 8928 0 0 0 0 0 0 0 0 0 0 1
84 19713 9937 0 0 0 0 0 0 0 0 0 0 0
85 21917 11468 1 0 0 0 0 0 0 0 0 0 0
86 23812 9554 0 1 0 0 0 0 0 0 0 0 0
87 23785 9226 0 0 1 0 0 0 0 0 0 0 0
88 24696 11021 0 0 0 1 0 0 0 0 0 0 0
89 24562 10065 0 0 0 0 1 0 0 0 0 0 0
90 23580 9939 0 0 0 0 0 1 0 0 0 0 0
91 24939 11179 0 0 0 0 0 0 1 0 0 0 0
92 23899 11943 0 0 0 0 0 0 0 1 0 0 0
93 21454 10792 0 0 0 0 0 0 0 0 1 0 0
94 19761 8080 0 0 0 0 0 0 0 0 0 1 0
95 19815 8603 0 0 0 0 0 0 0 0 0 0 1
96 20780 11561 0 0 0 0 0 0 0 0 0 0 0
97 23462 10449 1 0 0 0 0 0 0 0 0 0 0
98 25005 8197 0 1 0 0 0 0 0 0 0 0 0
99 24725 7602 0 0 1 0 0 0 0 0 0 0 0
100 26198 9521 0 0 0 1 0 0 0 0 0 0 0
101 27543 10412 0 0 0 0 1 0 0 0 0 0 0
102 26471 10860 0 0 0 0 0 1 0 0 0 0 0
103 26558 11538 0 0 0 0 0 0 1 0 0 0 0
104 25317 11420 0 0 0 0 0 0 0 1 0 0 0
105 22896 10408 0 0 0 0 0 0 0 0 1 0 0
106 22248 5998 0 0 0 0 0 0 0 0 0 1 0
107 23406 8356 0 0 0 0 0 0 0 0 0 0 1
108 25073 10569 0 0 0 0 0 0 0 0 0 0 0
109 27691 9660 1 0 0 0 0 0 0 0 0 0 0
110 30599 9304 0 1 0 0 0 0 0 0 0 0 0
111 31948 9114 0 0 1 0 0 0 0 0 0 0 0
112 32946 10492 0 0 0 1 0 0 0 0 0 0 0
113 34012 12388 0 0 0 0 1 0 0 0 0 0 0
114 32936 10003 0 0 0 0 0 1 0 0 0 0 0
115 32974 14029 0 0 0 0 0 0 1 0 0 0 0
116 30951 12452 0 0 0 0 0 0 0 1 0 0 0
117 29812 12332 0 0 0 0 0 0 0 0 1 0 0
118 29010 8064 0 0 0 0 0 0 0 0 0 1 0
119 31068 10931 0 0 0 0 0 0 0 0 0 0 1
120 32447 12631 0 0 0 0 0 0 0 0 0 0 0
121 34844 13656 1 0 0 0 0 0 0 0 0 0 0
122 35676 11005 0 1 0 0 0 0 0 0 0 0 0
123 35387 8879 0 0 1 0 0 0 0 0 0 0 0
124 36488 11536 0 0 0 1 0 0 0 0 0 0 0
125 35652 13698 0 0 0 0 1 0 0 0 0 0 0
126 33488 10853 0 0 0 0 0 1 0 0 0 0 0
127 32914 15107 0 0 0 0 0 0 1 0 0 0 0
128 29781 13604 0 0 0 0 0 0 0 1 0 0 0
129 27951 12231 0 0 0 0 0 0 0 0 1 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) OntvangenJobs M1 M2 M3
10623.194 1.296 1477.022 5607.428 6426.256
M4 M5 M6 M7 M8
3206.563 3787.280 3228.360 -280.372 75.602
M9 M10 M11
-1565.325 1889.992 1852.994
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5704.8 -2663.5 -511.6 2293.2 7710.8
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.062e+04 1.392e+03 7.631 7.14e-12 ***
OntvangenJobs 1.296e+00 5.698e-02 22.741 < 2e-16 ***
M1 1.477e+03 1.463e+03 1.010 0.314757
M2 5.607e+03 1.462e+03 3.835 0.000205 ***
M3 6.426e+03 1.464e+03 4.389 2.53e-05 ***
M4 3.207e+03 1.465e+03 2.189 0.030625 *
M5 3.787e+03 1.462e+03 2.590 0.010813 *
M6 3.228e+03 1.462e+03 2.209 0.029153 *
M7 -2.804e+02 1.468e+03 -0.191 0.848841
M8 7.560e+01 1.462e+03 0.052 0.958844
M9 -1.565e+03 1.462e+03 -1.071 0.286402
M10 1.890e+03 1.513e+03 1.249 0.214014
M11 1.853e+03 1.503e+03 1.233 0.220054
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3345 on 116 degrees of freedom
Multiple R-squared: 0.8389, Adjusted R-squared: 0.8222
F-statistic: 50.33 on 12 and 116 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,] 0.251929868 0.503859737 0.74807013
[2,] 0.145453410 0.290906820 0.85454659
[3,] 0.080880693 0.161761386 0.91911931
[4,] 0.104998781 0.209997563 0.89500122
[5,] 0.057899682 0.115799364 0.94210032
[6,] 0.030385750 0.060771501 0.96961425
[7,] 0.044714996 0.089429992 0.95528500
[8,] 0.064783989 0.129567978 0.93521601
[9,] 0.053033641 0.106067282 0.94696636
[10,] 0.092045008 0.184090016 0.90795499
[11,] 0.139181499 0.278362998 0.86081850
[12,] 0.102347492 0.204694984 0.89765251
[13,] 0.110292838 0.220585676 0.88970716
[14,] 0.206662987 0.413325974 0.79333701
[15,] 0.154682752 0.309365503 0.84531725
[16,] 0.484656986 0.969313973 0.51534301
[17,] 0.423139183 0.846278366 0.57686082
[18,] 0.420508875 0.841017749 0.57949113
[19,] 0.362265029 0.724530058 0.63773497
[20,] 0.337205714 0.674411427 0.66279429
[21,] 0.362516076 0.725032152 0.63748392
[22,] 0.318612000 0.637224001 0.68138800
[23,] 0.339663154 0.679326308 0.66033685
[24,] 0.383307227 0.766614455 0.61669277
[25,] 0.356740538 0.713481077 0.64325946
[26,] 0.320813389 0.641626778 0.67918661
[27,] 0.268071854 0.536143709 0.73192815
[28,] 0.236508910 0.473017821 0.76349109
[29,] 0.199366050 0.398732100 0.80063395
[30,] 0.224056344 0.448112688 0.77594366
[31,] 0.192087560 0.384175119 0.80791244
[32,] 0.202025939 0.404051877 0.79797406
[33,] 0.166663427 0.333326854 0.83333657
[34,] 0.135187889 0.270375778 0.86481211
[35,] 0.117489572 0.234979144 0.88251043
[36,] 0.116670131 0.233340262 0.88332987
[37,] 0.111106900 0.222213800 0.88889310
[38,] 0.087016933 0.174033865 0.91298307
[39,] 0.093211082 0.186422163 0.90678892
[40,] 0.073292925 0.146585849 0.92670708
[41,] 0.057148947 0.114297893 0.94285105
[42,] 0.043129546 0.086259092 0.95687045
[43,] 0.039532248 0.079064497 0.96046775
[44,] 0.040190453 0.080380905 0.95980955
[45,] 0.031202060 0.062404121 0.96879794
[46,] 0.023492184 0.046984367 0.97650782
[47,] 0.017248886 0.034497772 0.98275111
[48,] 0.012192389 0.024384777 0.98780761
[49,] 0.010170389 0.020340779 0.98982961
[50,] 0.008315989 0.016631978 0.99168401
[51,] 0.007739621 0.015479242 0.99226038
[52,] 0.007093021 0.014186042 0.99290698
[53,] 0.006514288 0.013028576 0.99348571
[54,] 0.005326949 0.010653898 0.99467305
[55,] 0.004873825 0.009747651 0.99512617
[56,] 0.004636259 0.009272519 0.99536374
[57,] 0.003137093 0.006274187 0.99686291
[58,] 0.002441043 0.004882086 0.99755896
[59,] 0.001636768 0.003273536 0.99836323
[60,] 0.001161241 0.002322483 0.99883876
[61,] 0.003852112 0.007704224 0.99614789
[62,] 0.002771715 0.005543430 0.99722829
[63,] 0.003571435 0.007142870 0.99642856
[64,] 0.005440248 0.010880496 0.99455975
[65,] 0.004177646 0.008355292 0.99582235
[66,] 0.004515489 0.009030977 0.99548451
[67,] 0.008621709 0.017243418 0.99137829
[68,] 0.010030730 0.020061460 0.98996927
[69,] 0.007658654 0.015317308 0.99234135
[70,] 0.013580367 0.027160733 0.98641963
[71,] 0.021064374 0.042128748 0.97893563
[72,] 0.055984896 0.111969791 0.94401510
[73,] 0.130231462 0.260462924 0.86976854
[74,] 0.105521054 0.211042109 0.89447895
[75,] 0.132642755 0.265285509 0.86735725
[76,] 0.117685320 0.235370640 0.88231468
[77,] 0.106708946 0.213417892 0.89329105
[78,] 0.095602718 0.191205436 0.90439728
[79,] 0.241628881 0.483257762 0.75837112
[80,] 0.265452349 0.530904698 0.73454765
[81,] 0.513246118 0.973507763 0.48675388
[82,] 0.560068133 0.879863734 0.43993187
[83,] 0.541577791 0.916844418 0.45842221
[84,] 0.660061822 0.679876356 0.33993818
[85,] 0.774887635 0.450224731 0.22511237
[86,] 0.724987126 0.550025748 0.27501287
[87,] 0.976959084 0.046081833 0.02304092
[88,] 0.966483141 0.067033719 0.03351686
[89,] 0.950533113 0.098933773 0.04946689
[90,] 0.935626432 0.128747136 0.06437357
[91,] 0.925285680 0.149428640 0.07471432
[92,] 0.910097166 0.179805668 0.08990283
[93,] 0.933077085 0.133845830 0.06692291
[94,] 0.897164878 0.205670244 0.10283512
[95,] 0.911085552 0.177828896 0.08891445
[96,] 0.951951046 0.096097909 0.04804895
[97,] 0.975112417 0.049775167 0.02488758
[98,] 0.957107077 0.085785847 0.04289292
> postscript(file="/var/www/html/rcomp/tmp/1sh481290756779.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2sh481290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3sh481290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4k7la1290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5k7la1290756779.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 = 129
Frequency = 1
1 2 3 4 5 6
-900.85538 -762.20856 1819.80716 -3280.61059 -2125.99799 -3102.71633
7 8 9 10 11 12
-5704.83153 92.73432 1459.96797 -412.98395 1230.08372 1142.68582
13 14 15 16 17 18
-2257.23844 -1408.19812 -2803.74250 -562.71722 -653.21272 -1515.01609
19 20 21 22 23 24
-1230.00000 1141.99896 2293.17437 4156.86079 6014.06860 4339.99442
25 26 27 28 29 30
4090.32353 4644.84584 1943.16151 2566.36166 5888.76877 679.79085
31 32 33 34 35 36
6117.63835 1958.08605 -605.68010 1806.64690 3431.40431 -1700.85320
37 38 39 40 41 42
1811.64225 -3550.65928 -4779.17995 -3320.92181 -1783.27384 -600.27964
43 44 45 46 47 48
-2666.39163 -966.31931 -3983.62250 -438.97210 -1499.09839 -129.48482
49 50 51 52 53 54
-511.61535 2249.67802 3036.03246 2671.76170 -766.52708 3820.76143
55 56 57 58 59 60
552.20255 57.41918 162.21627 -2036.98440 -1845.15773 180.01568
61 62 63 64 65 66
-381.76818 -599.54094 189.24122 -2962.10278 -2415.34210 -3390.64739
67 68 69 70 71 72
-3231.84942 -3139.28664 -2763.24023 -3261.43295 -3291.74225 -1436.50649
73 74 75 76 77 78
-2754.34091 -1428.33935 -1934.26507 -4961.95918 -1938.92662 -2987.47695
79 80 81 82 83 84
-2663.53063 -2264.28293 -3148.32180 -4602.75225 -4762.37310 -3785.75986
85 86 87 88 89 90
-5042.52808 -4797.92746 -5218.75968 -3413.88281 -2889.89195 -3149.71109
91 92 93 94 95 96
111.32826 -2274.57487 -1587.27541 -3221.60058 -3808.26423 -4823.00848
97 98 99 100 101 102
-2177.18982 -1846.63598 -2174.51106 31.69658 -358.50665 -1452.06884
103 104 105 106 107 108
1265.16493 -178.91352 352.28092 1963.08761 102.77851 755.34536
109 110 111 112 113 114
3074.13294 2313.00243 3089.36091 5521.55286 3550.15143 6123.36285
115 116 117 118 119 120
4453.52742 4117.90386 4775.31642 6048.13093 4428.30055 5457.57156
121 122 123 124 125 126
5049.43744 5185.98340 6832.85501 7710.82160 3492.75876 5574.00120
127 128 129
2996.74170 1455.23489 3045.18410
> postscript(file="/var/www/html/rcomp/tmp/6k7la1290756779.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 = 129
Frequency = 1
lag(myerror, k = 1) myerror
0 -900.85538 NA
1 -762.20856 -900.85538
2 1819.80716 -762.20856
3 -3280.61059 1819.80716
4 -2125.99799 -3280.61059
5 -3102.71633 -2125.99799
6 -5704.83153 -3102.71633
7 92.73432 -5704.83153
8 1459.96797 92.73432
9 -412.98395 1459.96797
10 1230.08372 -412.98395
11 1142.68582 1230.08372
12 -2257.23844 1142.68582
13 -1408.19812 -2257.23844
14 -2803.74250 -1408.19812
15 -562.71722 -2803.74250
16 -653.21272 -562.71722
17 -1515.01609 -653.21272
18 -1230.00000 -1515.01609
19 1141.99896 -1230.00000
20 2293.17437 1141.99896
21 4156.86079 2293.17437
22 6014.06860 4156.86079
23 4339.99442 6014.06860
24 4090.32353 4339.99442
25 4644.84584 4090.32353
26 1943.16151 4644.84584
27 2566.36166 1943.16151
28 5888.76877 2566.36166
29 679.79085 5888.76877
30 6117.63835 679.79085
31 1958.08605 6117.63835
32 -605.68010 1958.08605
33 1806.64690 -605.68010
34 3431.40431 1806.64690
35 -1700.85320 3431.40431
36 1811.64225 -1700.85320
37 -3550.65928 1811.64225
38 -4779.17995 -3550.65928
39 -3320.92181 -4779.17995
40 -1783.27384 -3320.92181
41 -600.27964 -1783.27384
42 -2666.39163 -600.27964
43 -966.31931 -2666.39163
44 -3983.62250 -966.31931
45 -438.97210 -3983.62250
46 -1499.09839 -438.97210
47 -129.48482 -1499.09839
48 -511.61535 -129.48482
49 2249.67802 -511.61535
50 3036.03246 2249.67802
51 2671.76170 3036.03246
52 -766.52708 2671.76170
53 3820.76143 -766.52708
54 552.20255 3820.76143
55 57.41918 552.20255
56 162.21627 57.41918
57 -2036.98440 162.21627
58 -1845.15773 -2036.98440
59 180.01568 -1845.15773
60 -381.76818 180.01568
61 -599.54094 -381.76818
62 189.24122 -599.54094
63 -2962.10278 189.24122
64 -2415.34210 -2962.10278
65 -3390.64739 -2415.34210
66 -3231.84942 -3390.64739
67 -3139.28664 -3231.84942
68 -2763.24023 -3139.28664
69 -3261.43295 -2763.24023
70 -3291.74225 -3261.43295
71 -1436.50649 -3291.74225
72 -2754.34091 -1436.50649
73 -1428.33935 -2754.34091
74 -1934.26507 -1428.33935
75 -4961.95918 -1934.26507
76 -1938.92662 -4961.95918
77 -2987.47695 -1938.92662
78 -2663.53063 -2987.47695
79 -2264.28293 -2663.53063
80 -3148.32180 -2264.28293
81 -4602.75225 -3148.32180
82 -4762.37310 -4602.75225
83 -3785.75986 -4762.37310
84 -5042.52808 -3785.75986
85 -4797.92746 -5042.52808
86 -5218.75968 -4797.92746
87 -3413.88281 -5218.75968
88 -2889.89195 -3413.88281
89 -3149.71109 -2889.89195
90 111.32826 -3149.71109
91 -2274.57487 111.32826
92 -1587.27541 -2274.57487
93 -3221.60058 -1587.27541
94 -3808.26423 -3221.60058
95 -4823.00848 -3808.26423
96 -2177.18982 -4823.00848
97 -1846.63598 -2177.18982
98 -2174.51106 -1846.63598
99 31.69658 -2174.51106
100 -358.50665 31.69658
101 -1452.06884 -358.50665
102 1265.16493 -1452.06884
103 -178.91352 1265.16493
104 352.28092 -178.91352
105 1963.08761 352.28092
106 102.77851 1963.08761
107 755.34536 102.77851
108 3074.13294 755.34536
109 2313.00243 3074.13294
110 3089.36091 2313.00243
111 5521.55286 3089.36091
112 3550.15143 5521.55286
113 6123.36285 3550.15143
114 4453.52742 6123.36285
115 4117.90386 4453.52742
116 4775.31642 4117.90386
117 6048.13093 4775.31642
118 4428.30055 6048.13093
119 5457.57156 4428.30055
120 5049.43744 5457.57156
121 5185.98340 5049.43744
122 6832.85501 5185.98340
123 7710.82160 6832.85501
124 3492.75876 7710.82160
125 5574.00120 3492.75876
126 2996.74170 5574.00120
127 1455.23489 2996.74170
128 3045.18410 1455.23489
129 NA 3045.18410
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -762.20856 -900.85538
[2,] 1819.80716 -762.20856
[3,] -3280.61059 1819.80716
[4,] -2125.99799 -3280.61059
[5,] -3102.71633 -2125.99799
[6,] -5704.83153 -3102.71633
[7,] 92.73432 -5704.83153
[8,] 1459.96797 92.73432
[9,] -412.98395 1459.96797
[10,] 1230.08372 -412.98395
[11,] 1142.68582 1230.08372
[12,] -2257.23844 1142.68582
[13,] -1408.19812 -2257.23844
[14,] -2803.74250 -1408.19812
[15,] -562.71722 -2803.74250
[16,] -653.21272 -562.71722
[17,] -1515.01609 -653.21272
[18,] -1230.00000 -1515.01609
[19,] 1141.99896 -1230.00000
[20,] 2293.17437 1141.99896
[21,] 4156.86079 2293.17437
[22,] 6014.06860 4156.86079
[23,] 4339.99442 6014.06860
[24,] 4090.32353 4339.99442
[25,] 4644.84584 4090.32353
[26,] 1943.16151 4644.84584
[27,] 2566.36166 1943.16151
[28,] 5888.76877 2566.36166
[29,] 679.79085 5888.76877
[30,] 6117.63835 679.79085
[31,] 1958.08605 6117.63835
[32,] -605.68010 1958.08605
[33,] 1806.64690 -605.68010
[34,] 3431.40431 1806.64690
[35,] -1700.85320 3431.40431
[36,] 1811.64225 -1700.85320
[37,] -3550.65928 1811.64225
[38,] -4779.17995 -3550.65928
[39,] -3320.92181 -4779.17995
[40,] -1783.27384 -3320.92181
[41,] -600.27964 -1783.27384
[42,] -2666.39163 -600.27964
[43,] -966.31931 -2666.39163
[44,] -3983.62250 -966.31931
[45,] -438.97210 -3983.62250
[46,] -1499.09839 -438.97210
[47,] -129.48482 -1499.09839
[48,] -511.61535 -129.48482
[49,] 2249.67802 -511.61535
[50,] 3036.03246 2249.67802
[51,] 2671.76170 3036.03246
[52,] -766.52708 2671.76170
[53,] 3820.76143 -766.52708
[54,] 552.20255 3820.76143
[55,] 57.41918 552.20255
[56,] 162.21627 57.41918
[57,] -2036.98440 162.21627
[58,] -1845.15773 -2036.98440
[59,] 180.01568 -1845.15773
[60,] -381.76818 180.01568
[61,] -599.54094 -381.76818
[62,] 189.24122 -599.54094
[63,] -2962.10278 189.24122
[64,] -2415.34210 -2962.10278
[65,] -3390.64739 -2415.34210
[66,] -3231.84942 -3390.64739
[67,] -3139.28664 -3231.84942
[68,] -2763.24023 -3139.28664
[69,] -3261.43295 -2763.24023
[70,] -3291.74225 -3261.43295
[71,] -1436.50649 -3291.74225
[72,] -2754.34091 -1436.50649
[73,] -1428.33935 -2754.34091
[74,] -1934.26507 -1428.33935
[75,] -4961.95918 -1934.26507
[76,] -1938.92662 -4961.95918
[77,] -2987.47695 -1938.92662
[78,] -2663.53063 -2987.47695
[79,] -2264.28293 -2663.53063
[80,] -3148.32180 -2264.28293
[81,] -4602.75225 -3148.32180
[82,] -4762.37310 -4602.75225
[83,] -3785.75986 -4762.37310
[84,] -5042.52808 -3785.75986
[85,] -4797.92746 -5042.52808
[86,] -5218.75968 -4797.92746
[87,] -3413.88281 -5218.75968
[88,] -2889.89195 -3413.88281
[89,] -3149.71109 -2889.89195
[90,] 111.32826 -3149.71109
[91,] -2274.57487 111.32826
[92,] -1587.27541 -2274.57487
[93,] -3221.60058 -1587.27541
[94,] -3808.26423 -3221.60058
[95,] -4823.00848 -3808.26423
[96,] -2177.18982 -4823.00848
[97,] -1846.63598 -2177.18982
[98,] -2174.51106 -1846.63598
[99,] 31.69658 -2174.51106
[100,] -358.50665 31.69658
[101,] -1452.06884 -358.50665
[102,] 1265.16493 -1452.06884
[103,] -178.91352 1265.16493
[104,] 352.28092 -178.91352
[105,] 1963.08761 352.28092
[106,] 102.77851 1963.08761
[107,] 755.34536 102.77851
[108,] 3074.13294 755.34536
[109,] 2313.00243 3074.13294
[110,] 3089.36091 2313.00243
[111,] 5521.55286 3089.36091
[112,] 3550.15143 5521.55286
[113,] 6123.36285 3550.15143
[114,] 4453.52742 6123.36285
[115,] 4117.90386 4453.52742
[116,] 4775.31642 4117.90386
[117,] 6048.13093 4775.31642
[118,] 4428.30055 6048.13093
[119,] 5457.57156 4428.30055
[120,] 5049.43744 5457.57156
[121,] 5185.98340 5049.43744
[122,] 6832.85501 5185.98340
[123,] 7710.82160 6832.85501
[124,] 3492.75876 7710.82160
[125,] 5574.00120 3492.75876
[126,] 2996.74170 5574.00120
[127,] 1455.23489 2996.74170
[128,] 3045.18410 1455.23489
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -762.20856 -900.85538
2 1819.80716 -762.20856
3 -3280.61059 1819.80716
4 -2125.99799 -3280.61059
5 -3102.71633 -2125.99799
6 -5704.83153 -3102.71633
7 92.73432 -5704.83153
8 1459.96797 92.73432
9 -412.98395 1459.96797
10 1230.08372 -412.98395
11 1142.68582 1230.08372
12 -2257.23844 1142.68582
13 -1408.19812 -2257.23844
14 -2803.74250 -1408.19812
15 -562.71722 -2803.74250
16 -653.21272 -562.71722
17 -1515.01609 -653.21272
18 -1230.00000 -1515.01609
19 1141.99896 -1230.00000
20 2293.17437 1141.99896
21 4156.86079 2293.17437
22 6014.06860 4156.86079
23 4339.99442 6014.06860
24 4090.32353 4339.99442
25 4644.84584 4090.32353
26 1943.16151 4644.84584
27 2566.36166 1943.16151
28 5888.76877 2566.36166
29 679.79085 5888.76877
30 6117.63835 679.79085
31 1958.08605 6117.63835
32 -605.68010 1958.08605
33 1806.64690 -605.68010
34 3431.40431 1806.64690
35 -1700.85320 3431.40431
36 1811.64225 -1700.85320
37 -3550.65928 1811.64225
38 -4779.17995 -3550.65928
39 -3320.92181 -4779.17995
40 -1783.27384 -3320.92181
41 -600.27964 -1783.27384
42 -2666.39163 -600.27964
43 -966.31931 -2666.39163
44 -3983.62250 -966.31931
45 -438.97210 -3983.62250
46 -1499.09839 -438.97210
47 -129.48482 -1499.09839
48 -511.61535 -129.48482
49 2249.67802 -511.61535
50 3036.03246 2249.67802
51 2671.76170 3036.03246
52 -766.52708 2671.76170
53 3820.76143 -766.52708
54 552.20255 3820.76143
55 57.41918 552.20255
56 162.21627 57.41918
57 -2036.98440 162.21627
58 -1845.15773 -2036.98440
59 180.01568 -1845.15773
60 -381.76818 180.01568
61 -599.54094 -381.76818
62 189.24122 -599.54094
63 -2962.10278 189.24122
64 -2415.34210 -2962.10278
65 -3390.64739 -2415.34210
66 -3231.84942 -3390.64739
67 -3139.28664 -3231.84942
68 -2763.24023 -3139.28664
69 -3261.43295 -2763.24023
70 -3291.74225 -3261.43295
71 -1436.50649 -3291.74225
72 -2754.34091 -1436.50649
73 -1428.33935 -2754.34091
74 -1934.26507 -1428.33935
75 -4961.95918 -1934.26507
76 -1938.92662 -4961.95918
77 -2987.47695 -1938.92662
78 -2663.53063 -2987.47695
79 -2264.28293 -2663.53063
80 -3148.32180 -2264.28293
81 -4602.75225 -3148.32180
82 -4762.37310 -4602.75225
83 -3785.75986 -4762.37310
84 -5042.52808 -3785.75986
85 -4797.92746 -5042.52808
86 -5218.75968 -4797.92746
87 -3413.88281 -5218.75968
88 -2889.89195 -3413.88281
89 -3149.71109 -2889.89195
90 111.32826 -3149.71109
91 -2274.57487 111.32826
92 -1587.27541 -2274.57487
93 -3221.60058 -1587.27541
94 -3808.26423 -3221.60058
95 -4823.00848 -3808.26423
96 -2177.18982 -4823.00848
97 -1846.63598 -2177.18982
98 -2174.51106 -1846.63598
99 31.69658 -2174.51106
100 -358.50665 31.69658
101 -1452.06884 -358.50665
102 1265.16493 -1452.06884
103 -178.91352 1265.16493
104 352.28092 -178.91352
105 1963.08761 352.28092
106 102.77851 1963.08761
107 755.34536 102.77851
108 3074.13294 755.34536
109 2313.00243 3074.13294
110 3089.36091 2313.00243
111 5521.55286 3089.36091
112 3550.15143 5521.55286
113 6123.36285 3550.15143
114 4453.52742 6123.36285
115 4117.90386 4453.52742
116 4775.31642 4117.90386
117 6048.13093 4775.31642
118 4428.30055 6048.13093
119 5457.57156 4428.30055
120 5049.43744 5457.57156
121 5185.98340 5049.43744
122 6832.85501 5185.98340
123 7710.82160 6832.85501
124 3492.75876 7710.82160
125 5574.00120 3492.75876
126 2996.74170 5574.00120
127 1455.23489 2996.74170
128 3045.18410 1455.23489
> 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/7vzke1290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8681g1290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9681g1290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10681g1290756779.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1199i41290756779.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/12c9ga1290756779.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/131sdm1290756779.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/14c1d71290756779.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/15xktv1290756779.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/16tcrl1290756779.tab")
+ }
>
> try(system("convert tmp/1sh481290756779.ps tmp/1sh481290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sh481290756779.ps tmp/2sh481290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sh481290756779.ps tmp/3sh481290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/4k7la1290756779.ps tmp/4k7la1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/5k7la1290756779.ps tmp/5k7la1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/6k7la1290756779.ps tmp/6k7la1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vzke1290756779.ps tmp/7vzke1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/8681g1290756779.ps tmp/8681g1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/9681g1290756779.ps tmp/9681g1290756779.png",intern=TRUE))
character(0)
> try(system("convert tmp/10681g1290756779.ps tmp/10681g1290756779.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.439 1.710 8.583