R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(14915
+ ,3440
+ ,813
+ ,5126
+ ,2563
+ ,11773
+ ,3054
+ ,647
+ ,4127
+ ,1505
+ ,11608
+ ,3203
+ ,630
+ ,4232
+ ,1145
+ ,11468
+ ,3148
+ ,662
+ ,4167
+ ,1082
+ ,11511
+ ,3181
+ ,653
+ ,4058
+ ,1135
+ ,11200
+ ,3211
+ ,660
+ ,3802
+ ,1109
+ ,11164
+ ,3306
+ ,632
+ ,3907
+ ,932
+ ,10960
+ ,3252
+ ,673
+ ,3708
+ ,957
+ ,10667
+ ,3218
+ ,627
+ ,3724
+ ,806
+ ,11556
+ ,3418
+ ,641
+ ,4025
+ ,1107
+ ,11372
+ ,3188
+ ,660
+ ,4051
+ ,1081
+ ,12333
+ ,3186
+ ,723
+ ,4264
+ ,1255
+ ,13102
+ ,3360
+ ,797
+ ,4533
+ ,1507
+ ,11115
+ ,2944
+ ,680
+ ,3827
+ ,1205
+ ,12572
+ ,3522
+ ,752
+ ,4316
+ ,1305
+ ,11557
+ ,3121
+ ,724
+ ,4091
+ ,1089
+ ,12059
+ ,3305
+ ,799
+ ,4175
+ ,1164
+ ,11420
+ ,3283
+ ,778
+ ,3822
+ ,988
+ ,11185
+ ,3139
+ ,789
+ ,3610
+ ,1000
+ ,11113
+ ,3315
+ ,688
+ ,3478
+ ,1023
+ ,10706
+ ,3163
+ ,623
+ ,3526
+ ,878
+ ,11523
+ ,3318
+ ,683
+ ,3887
+ ,1032
+ ,11391
+ ,3208
+ ,694
+ ,3912
+ ,994
+ ,12634
+ ,3335
+ ,742
+ ,4466
+ ,1193
+ ,13469
+ ,3393
+ ,966
+ ,4553
+ ,1503
+ ,11735
+ ,3118
+ ,779
+ ,3992
+ ,1251
+ ,13281
+ ,3379
+ ,854
+ ,4535
+ ,1694
+ ,11968
+ ,3245
+ ,808
+ ,4113
+ ,1273
+ ,11623
+ ,3326
+ ,783
+ ,3982
+ ,984
+ ,11084
+ ,3318
+ ,815
+ ,3587
+ ,943
+ ,11509
+ ,3380
+ ,811
+ ,3792
+ ,936
+ ,11134
+ ,3283
+ ,912
+ ,3546
+ ,962
+ ,10438
+ ,3174
+ ,717
+ ,3444
+ ,717
+ ,11530
+ ,3348
+ ,787
+ ,4001
+ ,898
+ ,11491
+ ,3306
+ ,775
+ ,3928
+ ,963
+ ,13093
+ ,3407
+ ,961
+ ,4519
+ ,1387
+ ,13106
+ ,3373
+ ,952
+ ,4502
+ ,1442
+ ,11305
+ ,3055
+ ,778
+ ,3891
+ ,1197
+ ,13113
+ ,3382
+ ,928
+ ,4522
+ ,1536
+ ,12203
+ ,3344
+ ,811
+ ,4113
+ ,1308
+ ,11309
+ ,3315
+ ,811
+ ,3769
+ ,1047
+ ,11088
+ ,3276
+ ,844
+ ,3538
+ ,975
+ ,11234
+ ,3386
+ ,829
+ ,3504
+ ,975
+ ,11619
+ ,3304
+ ,972
+ ,3599
+ ,1092
+ ,10942
+ ,3301
+ ,791
+ ,3572
+ ,887
+ ,11445
+ ,3357
+ ,782
+ ,3816
+ ,972
+ ,11291
+ ,3289
+ ,828
+ ,3716
+ ,1066
+ ,13281
+ ,3485
+ ,912
+ ,4400
+ ,1745
+ ,13726
+ ,3489
+ ,990
+ ,4498
+ ,1930
+ ,11300
+ ,3189
+ ,755
+ ,3859
+ ,1108
+ ,11983
+ ,3455
+ ,840
+ ,4006
+ ,1167
+ ,11092
+ ,3295
+ ,781
+ ,3648
+ ,1024
+ ,11093
+ ,3335
+ ,828
+ ,3691
+ ,918
+ ,10692
+ ,3329
+ ,795
+ ,3481
+ ,894
+ ,10786
+ ,3382
+ ,838
+ ,3326
+ ,899
+ ,11166
+ ,3395
+ ,944
+ ,3376
+ ,1013
+ ,10553
+ ,3345
+ ,739
+ ,3436
+ ,770
+ ,11103
+ ,3374
+ ,789
+ ,3651
+ ,902
+ ,10969
+ ,3270
+ ,803
+ ,3629
+ ,937
+ ,12090
+ ,3442
+ ,859
+ ,4037
+ ,1193
+ ,12544
+ ,3448
+ ,927
+ ,4095
+ ,1493
+ ,12264
+ ,3216
+ ,860
+ ,3891
+ ,1827
+ ,13783
+ ,3542
+ ,1052
+ ,4476
+ ,2034
+ ,11214
+ ,3361
+ ,744
+ ,3568
+ ,1273
+ ,11453
+ ,3425
+ ,778
+ ,3681
+ ,1153
+ ,10883
+ ,3383
+ ,843
+ ,3299
+ ,1083
+ ,10381
+ ,3285
+ ,779
+ ,3156
+ ,907
+ ,10348
+ ,3435
+ ,760
+ ,3186
+ ,694
+ ,10024
+ ,3254
+ ,743
+ ,3012
+ ,803
+ ,10805
+ ,3337
+ ,838
+ ,3436
+ ,876
+ ,10796
+ ,3296
+ ,749
+ ,3587
+ ,975
+ ,11907
+ ,3391
+ ,918
+ ,3963
+ ,1197
+ ,12261
+ ,3508
+ ,907
+ ,3906
+ ,1356
+ ,11377
+ ,3091
+ ,873
+ ,3700
+ ,1366
+ ,12689
+ ,3451
+ ,968
+ ,4115
+ ,1532
+ ,11474
+ ,3315
+ ,957
+ ,3590
+ ,1262
+ ,10992
+ ,3368
+ ,866
+ ,3341
+ ,1073
+ ,10764
+ ,3412
+ ,887
+ ,3199
+ ,1029
+ ,12164
+ ,3521
+ ,1255
+ ,3407
+ ,1294
+ ,10409
+ ,3302
+ ,832
+ ,3081
+ ,824
+ ,10398
+ ,3278
+ ,887
+ ,3050
+ ,919
+ ,10349
+ ,3425
+ ,776
+ ,3155
+ ,899
+ ,10865
+ ,3384
+ ,784
+ ,3445
+ ,987
+ ,11630
+ ,3508
+ ,834
+ ,3731
+ ,1190
+ ,12221
+ ,3609
+ ,902
+ ,3803
+ ,1445
+ ,10884
+ ,3211
+ ,759
+ ,3471
+ ,1277
+ ,12019
+ ,3418
+ ,877
+ ,3840
+ ,1393
+ ,11021
+ ,3306
+ ,901
+ ,3396
+ ,1179
+ ,10799
+ ,3313
+ ,851
+ ,3270
+ ,1117
+ ,10423
+ ,3362
+ ,829
+ ,3106
+ ,997
+ ,10484
+ ,3413
+ ,825
+ ,3050
+ ,950
+ ,10450
+ ,3479
+ ,887
+ ,3035
+ ,817
+ ,9906
+ ,3213
+ ,787
+ ,2992
+ ,811
+ ,11049
+ ,3465
+ ,832
+ ,3430
+ ,1003
+ ,11281
+ ,3476
+ ,838
+ ,3541
+ ,1124
+ ,12485
+ ,3629
+ ,996
+ ,3915
+ ,1423
+ ,12849
+ ,3665
+ ,1080
+ ,3873
+ ,1562
+ ,11380
+ ,3420
+ ,931
+ ,3490
+ ,1246
+ ,12079
+ ,3611
+ ,987
+ ,3677
+ ,1317
+ ,11366
+ ,3341
+ ,953
+ ,3491
+ ,1257
+ ,11328
+ ,3511
+ ,989
+ ,3308
+ ,1139
+ ,10444
+ ,3407
+ ,907
+ ,3031
+ ,922
+ ,10854
+ ,3523
+ ,898
+ ,3044
+ ,1044
+ ,10434
+ ,3472
+ ,877
+ ,2933
+ ,903
+ ,10137
+ ,3385
+ ,893
+ ,2941
+ ,820
+ ,10992
+ ,3546
+ ,851
+ ,3355
+ ,1010
+ ,10906
+ ,3443
+ ,912
+ ,3259
+ ,1069
+ ,12367
+ ,3550
+ ,1062
+ ,3727
+ ,1500
+ ,14371
+ ,3795
+ ,1252
+ ,4201
+ ,2293
+ ,11695
+ ,3268
+ ,1013
+ ,3406
+ ,1616
+ ,11546
+ ,3560
+ ,912
+ ,3519
+ ,1229
+ ,10922
+ ,3488
+ ,877
+ ,3243
+ ,1127
+ ,10670
+ ,3436
+ ,926
+ ,3095
+ ,1031
+ ,10254
+ ,3440
+ ,925
+ ,2822
+ ,916
+ ,10573
+ ,3502
+ ,950
+ ,2997
+ ,900
+ ,10239
+ ,3509
+ ,990
+ ,2758
+ ,826
+ ,10253
+ ,3494
+ ,861
+ ,2932
+ ,797
+ ,11176
+ ,3782
+ ,937
+ ,3181
+ ,1054
+ ,10719
+ ,3430
+ ,906
+ ,3128
+ ,1050
+ ,11817
+ ,3692
+ ,1017
+ ,3615
+ ,1123
+ ,12487
+ ,3760
+ ,1107
+ ,3700
+ ,1398
+ ,11519
+ ,3370
+ ,1000
+ ,3477
+ ,1356
+ ,12025
+ ,3755
+ ,1068
+ ,3512
+ ,1208
+ ,10976
+ ,3515
+ ,885
+ ,3231
+ ,983
+ ,11276
+ ,3560
+ ,1042
+ ,3143
+ ,1062
+ ,10657
+ ,3607
+ ,974
+ ,2954
+ ,925
+ ,11141
+ ,3635
+ ,1136
+ ,2954
+ ,1029
+ ,10423
+ ,3628
+ ,968
+ ,2834
+ ,808
+ ,10640
+ ,3552
+ ,957
+ ,2941
+ ,936
+ ,11426
+ ,3742
+ ,1019
+ ,3281
+ ,1097
+ ,10948
+ ,3551
+ ,954
+ ,3196
+ ,1007
+ ,12540
+ ,3841
+ ,1211
+ ,3786
+ ,1207
+ ,12200
+ ,3675
+ ,1133
+ ,3602
+ ,1339
+ ,10644
+ ,3367
+ ,954
+ ,3066
+ ,1101
+ ,12044
+ ,3736
+ ,1050
+ ,3484
+ ,1275
+ ,11338
+ ,3632
+ ,1024
+ ,3194
+ ,1243
+ ,11292
+ ,3668
+ ,1025
+ ,3162
+ ,1147
+ ,10612
+ ,3543
+ ,985
+ ,2865
+ ,1032
+ ,10995
+ ,3773
+ ,1076
+ ,2960
+ ,936
+ ,10686
+ ,3653
+ ,1051
+ ,2909
+ ,915
+ ,10635
+ ,3662
+ ,1041
+ ,2864
+ ,864
+ ,11285
+ ,3745
+ ,1041
+ ,3204
+ ,995
+ ,11475
+ ,3761
+ ,1084
+ ,3188
+ ,1109
+ ,12535
+ ,3823
+ ,1204
+ ,3634
+ ,1361)
+ ,dim=c(5
+ ,144)
+ ,dimnames=list(c('Y_t'
+ ,'X_1t'
+ ,'X_2t'
+ ,'X_3t'
+ ,'X_4t')
+ ,1:144))
> y <- array(NA,dim=c(5,144),dimnames=list(c('Y_t','X_1t','X_2t','X_3t','X_4t'),1:144))
> 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'
> 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, 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
Y_t X_1t X_2t X_3t X_4t
1 14915 3440 813 5126 2563
2 11773 3054 647 4127 1505
3 11608 3203 630 4232 1145
4 11468 3148 662 4167 1082
5 11511 3181 653 4058 1135
6 11200 3211 660 3802 1109
7 11164 3306 632 3907 932
8 10960 3252 673 3708 957
9 10667 3218 627 3724 806
10 11556 3418 641 4025 1107
11 11372 3188 660 4051 1081
12 12333 3186 723 4264 1255
13 13102 3360 797 4533 1507
14 11115 2944 680 3827 1205
15 12572 3522 752 4316 1305
16 11557 3121 724 4091 1089
17 12059 3305 799 4175 1164
18 11420 3283 778 3822 988
19 11185 3139 789 3610 1000
20 11113 3315 688 3478 1023
21 10706 3163 623 3526 878
22 11523 3318 683 3887 1032
23 11391 3208 694 3912 994
24 12634 3335 742 4466 1193
25 13469 3393 966 4553 1503
26 11735 3118 779 3992 1251
27 13281 3379 854 4535 1694
28 11968 3245 808 4113 1273
29 11623 3326 783 3982 984
30 11084 3318 815 3587 943
31 11509 3380 811 3792 936
32 11134 3283 912 3546 962
33 10438 3174 717 3444 717
34 11530 3348 787 4001 898
35 11491 3306 775 3928 963
36 13093 3407 961 4519 1387
37 13106 3373 952 4502 1442
38 11305 3055 778 3891 1197
39 13113 3382 928 4522 1536
40 12203 3344 811 4113 1308
41 11309 3315 811 3769 1047
42 11088 3276 844 3538 975
43 11234 3386 829 3504 975
44 11619 3304 972 3599 1092
45 10942 3301 791 3572 887
46 11445 3357 782 3816 972
47 11291 3289 828 3716 1066
48 13281 3485 912 4400 1745
49 13726 3489 990 4498 1930
50 11300 3189 755 3859 1108
51 11983 3455 840 4006 1167
52 11092 3295 781 3648 1024
53 11093 3335 828 3691 918
54 10692 3329 795 3481 894
55 10786 3382 838 3326 899
56 11166 3395 944 3376 1013
57 10553 3345 739 3436 770
58 11103 3374 789 3651 902
59 10969 3270 803 3629 937
60 12090 3442 859 4037 1193
61 12544 3448 927 4095 1493
62 12264 3216 860 3891 1827
63 13783 3542 1052 4476 2034
64 11214 3361 744 3568 1273
65 11453 3425 778 3681 1153
66 10883 3383 843 3299 1083
67 10381 3285 779 3156 907
68 10348 3435 760 3186 694
69 10024 3254 743 3012 803
70 10805 3337 838 3436 876
71 10796 3296 749 3587 975
72 11907 3391 918 3963 1197
73 12261 3508 907 3906 1356
74 11377 3091 873 3700 1366
75 12689 3451 968 4115 1532
76 11474 3315 957 3590 1262
77 10992 3368 866 3341 1073
78 10764 3412 887 3199 1029
79 12164 3521 1255 3407 1294
80 10409 3302 832 3081 824
81 10398 3278 887 3050 919
82 10349 3425 776 3155 899
83 10865 3384 784 3445 987
84 11630 3508 834 3731 1190
85 12221 3609 902 3803 1445
86 10884 3211 759 3471 1277
87 12019 3418 877 3840 1393
88 11021 3306 901 3396 1179
89 10799 3313 851 3270 1117
90 10423 3362 829 3106 997
91 10484 3413 825 3050 950
92 10450 3479 887 3035 817
93 9906 3213 787 2992 811
94 11049 3465 832 3430 1003
95 11281 3476 838 3541 1124
96 12485 3629 996 3915 1423
97 12849 3665 1080 3873 1562
98 11380 3420 931 3490 1246
99 12079 3611 987 3677 1317
100 11366 3341 953 3491 1257
101 11328 3511 989 3308 1139
102 10444 3407 907 3031 922
103 10854 3523 898 3044 1044
104 10434 3472 877 2933 903
105 10137 3385 893 2941 820
106 10992 3546 851 3355 1010
107 10906 3443 912 3259 1069
108 12367 3550 1062 3727 1500
109 14371 3795 1252 4201 2293
110 11695 3268 1013 3406 1616
111 11546 3560 912 3519 1229
112 10922 3488 877 3243 1127
113 10670 3436 926 3095 1031
114 10254 3440 925 2822 916
115 10573 3502 950 2997 900
116 10239 3509 990 2758 826
117 10253 3494 861 2932 797
118 11176 3782 937 3181 1054
119 10719 3430 906 3128 1050
120 11817 3692 1017 3615 1123
121 12487 3760 1107 3700 1398
122 11519 3370 1000 3477 1356
123 12025 3755 1068 3512 1208
124 10976 3515 885 3231 983
125 11276 3560 1042 3143 1062
126 10657 3607 974 2954 925
127 11141 3635 1136 2954 1029
128 10423 3628 968 2834 808
129 10640 3552 957 2941 936
130 11426 3742 1019 3281 1097
131 10948 3551 954 3196 1007
132 12540 3841 1211 3786 1207
133 12200 3675 1133 3602 1339
134 10644 3367 954 3066 1101
135 12044 3736 1050 3484 1275
136 11338 3632 1024 3194 1243
137 11292 3668 1025 3162 1147
138 10612 3543 985 2865 1032
139 10995 3773 1076 2960 936
140 10686 3653 1051 2909 915
141 10635 3662 1041 2864 864
142 11285 3745 1041 3204 995
143 11475 3761 1084 3188 1109
144 12535 3823 1204 3634 1361
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X_1t X_2t X_3t X_4t
775.6939 0.9163 1.5623 1.4271 0.9080
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-174.40 -63.05 -8.10 46.35 332.46
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 775.69389 220.74837 3.514 0.000596 ***
X_1t 0.91632 0.07337 12.488 < 2e-16 ***
X_2t 1.56229 0.11365 13.747 < 2e-16 ***
X_3t 1.42712 0.02948 48.412 < 2e-16 ***
X_4t 0.90800 0.04934 18.403 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 93.68 on 139 degrees of freedom
Multiple R-squared: 0.9892, Adjusted R-squared: 0.9889
F-statistic: 3189 on 4 and 139 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,] 0.11457449 2.291490e-01 8.854255e-01
[2,] 0.05151190 1.030238e-01 9.484881e-01
[3,] 0.04175199 8.350398e-02 9.582480e-01
[4,] 0.02179023 4.358046e-02 9.782098e-01
[5,] 0.61745971 7.650806e-01 3.825403e-01
[6,] 0.59601295 8.079741e-01 4.039870e-01
[7,] 0.52580177 9.483965e-01 4.741982e-01
[8,] 0.46073132 9.214626e-01 5.392687e-01
[9,] 0.56171227 8.765755e-01 4.382877e-01
[10,] 0.71912728 5.617454e-01 2.808727e-01
[11,] 0.66271146 6.745771e-01 3.372885e-01
[12,] 0.67992721 6.401456e-01 3.200728e-01
[13,] 0.91934033 1.613193e-01 8.065967e-02
[14,] 0.97700072 4.599856e-02 2.299928e-02
[15,] 0.98299134 3.401732e-02 1.700866e-02
[16,] 0.98260284 3.479431e-02 1.739716e-02
[17,] 0.99799508 4.009845e-03 2.004923e-03
[18,] 0.99895933 2.081337e-03 1.040669e-03
[19,] 0.99886236 2.275282e-03 1.137641e-03
[20,] 0.99898618 2.027648e-03 1.013824e-03
[21,] 0.99966945 6.610911e-04 3.305456e-04
[22,] 0.99964704 7.059176e-04 3.529588e-04
[23,] 0.99985004 2.999213e-04 1.499606e-04
[24,] 0.99984702 3.059629e-04 1.529814e-04
[25,] 0.99995110 9.780904e-05 4.890452e-05
[26,] 0.99993576 1.284785e-04 6.423924e-05
[27,] 0.99992679 1.464158e-04 7.320791e-05
[28,] 0.99989107 2.178559e-04 1.089280e-04
[29,] 0.99986229 2.754151e-04 1.377075e-04
[30,] 0.99981832 3.633699e-04 1.816850e-04
[31,] 0.99989170 2.165987e-04 1.082993e-04
[32,] 0.99988094 2.381299e-04 1.190650e-04
[33,] 0.99985225 2.954984e-04 1.477492e-04
[34,] 0.99991667 1.666640e-04 8.333199e-05
[35,] 0.99989379 2.124247e-04 1.062123e-04
[36,] 0.99995831 8.337232e-05 4.168616e-05
[37,] 0.99998569 2.862751e-05 1.431376e-05
[38,] 0.99998226 3.547269e-05 1.773635e-05
[39,] 0.99998270 3.460305e-05 1.730153e-05
[40,] 0.99998428 3.143914e-05 1.571957e-05
[41,] 0.99998445 3.109883e-05 1.554942e-05
[42,] 0.99998584 2.831233e-05 1.415617e-05
[43,] 0.99998413 3.174629e-05 1.587315e-05
[44,] 0.99998203 3.593816e-05 1.796908e-05
[45,] 0.99997978 4.044114e-05 2.022057e-05
[46,] 0.99998743 2.513456e-05 1.256728e-05
[47,] 0.99999595 8.103767e-06 4.051884e-06
[48,] 0.99999439 1.121732e-05 5.608662e-06
[49,] 0.99999360 1.280354e-05 6.401769e-06
[50,] 0.99999037 1.926136e-05 9.630682e-06
[51,] 0.99998592 2.815074e-05 1.407537e-05
[52,] 0.99998218 3.564305e-05 1.782152e-05
[53,] 0.99997706 4.588951e-05 2.294475e-05
[54,] 0.99997063 5.873560e-05 2.936780e-05
[55,] 0.99995982 8.035708e-05 4.017854e-05
[56,] 0.99996905 6.190280e-05 3.095140e-05
[57,] 0.99995584 8.831271e-05 4.415636e-05
[58,] 0.99994553 1.089431e-04 5.447154e-05
[59,] 0.99991303 1.739314e-04 8.696570e-05
[60,] 0.99989426 2.114895e-04 1.057447e-04
[61,] 0.99990667 1.866554e-04 9.332769e-05
[62,] 0.99992013 1.597343e-04 7.986714e-05
[63,] 0.99988944 2.211280e-04 1.105640e-04
[64,] 0.99993455 1.309077e-04 6.545386e-05
[65,] 0.99994486 1.102769e-04 5.513845e-05
[66,] 0.99995317 9.365382e-05 4.682691e-05
[67,] 0.99994947 1.010560e-04 5.052800e-05
[68,] 0.99992778 1.444340e-04 7.221700e-05
[69,] 0.99992069 1.586207e-04 7.931034e-05
[70,] 0.99989764 2.047105e-04 1.023552e-04
[71,] 0.99983645 3.271056e-04 1.635528e-04
[72,] 0.99995932 8.136872e-05 4.068436e-05
[73,] 0.99999771 4.582506e-06 2.291253e-06
[74,] 0.99999797 4.064618e-06 2.032309e-06
[75,] 0.99999815 3.705089e-06 1.852545e-06
[76,] 0.99999691 6.182610e-06 3.091305e-06
[77,] 0.99999494 1.011925e-05 5.059626e-06
[78,] 0.99999085 1.829249e-05 9.146247e-06
[79,] 0.99999432 1.135551e-05 5.677754e-06
[80,] 0.99999218 1.563820e-05 7.819100e-06
[81,] 0.99999087 1.826896e-05 9.134481e-06
[82,] 0.99998353 3.294010e-05 1.647005e-05
[83,] 0.99997896 4.208456e-05 2.104228e-05
[84,] 0.99997721 4.557156e-05 2.278578e-05
[85,] 0.99996904 6.192632e-05 3.096316e-05
[86,] 0.99994672 1.065549e-04 5.327744e-05
[87,] 0.99992651 1.469768e-04 7.348840e-05
[88,] 0.99987968 2.406337e-04 1.203169e-04
[89,] 0.99980596 3.880787e-04 1.940393e-04
[90,] 0.99988757 2.248637e-04 1.124318e-04
[91,] 0.99985229 2.954291e-04 1.477146e-04
[92,] 0.99980693 3.861357e-04 1.930678e-04
[93,] 0.99969846 6.030810e-04 3.015405e-04
[94,] 0.99963111 7.377897e-04 3.688948e-04
[95,] 0.99938216 1.235685e-03 6.178427e-04
[96,] 0.99980197 3.960570e-04 1.980285e-04
[97,] 0.99987758 2.448378e-04 1.224189e-04
[98,] 0.99982055 3.588924e-04 1.794462e-04
[99,] 0.99969805 6.038948e-04 3.019474e-04
[100,] 0.99953053 9.389378e-04 4.694689e-04
[101,] 0.99928430 1.431402e-03 7.157011e-04
[102,] 0.99918196 1.636085e-03 8.180424e-04
[103,] 0.99876292 2.474152e-03 1.237076e-03
[104,] 0.99794942 4.101154e-03 2.050577e-03
[105,] 0.99727744 5.445127e-03 2.722564e-03
[106,] 0.99617410 7.651804e-03 3.825902e-03
[107,] 0.99370412 1.259177e-02 6.295883e-03
[108,] 0.98986573 2.026854e-02 1.013427e-02
[109,] 0.98415391 3.169218e-02 1.584609e-02
[110,] 0.97580922 4.838155e-02 2.419078e-02
[111,] 0.96831927 6.336146e-02 3.168073e-02
[112,] 0.95441993 9.116015e-02 4.558007e-02
[113,] 0.94803726 1.039255e-01 5.196274e-02
[114,] 0.92739460 1.452108e-01 7.260540e-02
[115,] 0.91702797 1.659441e-01 8.297203e-02
[116,] 0.90025046 1.994991e-01 9.974954e-02
[117,] 0.92818070 1.436386e-01 7.181930e-02
[118,] 0.99285309 1.429383e-02 7.146913e-03
[119,] 0.98642726 2.714548e-02 1.357274e-02
[120,] 0.99751856 4.962876e-03 2.481438e-03
[121,] 0.99504653 9.906942e-03 4.953471e-03
[122,] 0.99745863 5.082731e-03 2.541366e-03
[123,] 0.99763675 4.726505e-03 2.363252e-03
[124,] 0.99405036 1.189928e-02 5.949640e-03
[125,] 0.99099952 1.800096e-02 9.000479e-03
[126,] 0.97712153 4.575694e-02 2.287847e-02
[127,] 0.94753475 1.049305e-01 5.246525e-02
[128,] 0.96610200 6.779600e-02 3.389800e-02
[129,] 0.96595130 6.809739e-02 3.404870e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1i2tx1353865580.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/24mhz1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3831e1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/49q8h1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5vrde1353865580.ps",horizontal=F,onefile=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 = 144
Frequency = 1
1 2 3 4 5 6
74.4286601 -68.1809308 -166.1217475 -155.7509980 -21.4969605 18.0274807
7 8 9 10 11 12
-50.4104886 -7.6866780 -83.3928552 -102.3981511 -118.8255284 283.6153569
13 14 15 16 17 18
164.8566564 23.5930328 49.8160317 -36.7673441 -8.5192432 69.0278383
19 20 21 22 23 24
240.4454540 332.4601343 229.4472651 155.6595864 106.0953973 186.4185360
25 26 27 28 29 30
212.6810212 52.2447980 64.7464146 -69.0911658 0.1078936 19.3845131
31 32 33 34 35 36
107.6188207 -8.8264669 67.7238503 -68.3277234 -4.9351400 -14.4863027
37 38 39 40 41 42
18.0502615 -125.2941289 -59.5957818 38.7265401 -100.7844903 57.4363586
43 44 45 46 47 48
174.5976597 169.5166464 2.7114669 43.0617864 -63.1338403 23.3569256
49 50 51 52 53 54
34.9961139 -90.6686291 -47.5619663 -59.0243079 -133.2229369 -155.6828910
55 56 57 58 59 60
39.2370524 66.8547492 -45.0438631 -26.4174416 -87.3756925 -26.1818845
61 62 63 64 65 66
-39.0874453 -13.9673981 -116.4657937 -51.6185905 23.3146286 -1.0300532
67 68 69 70 71 72
50.6409581 60.4665988 78.2258642 -36.6276060 -174.4013529 -152.6499665
73 74 75 76 77 78
48.3000716 -115.5711179 -24.8444794 -103.6440236 34.9231241 -23.6003747
79 80 81 82 83 84
164.1389829 162.6598464 45.7065084 -96.2656537 -48.9627537 -68.1797354
85 86 87 88 89 90
-10.2553060 -132.8067527 -3.7687642 -108.6844204 -22.8715779 -66.3938746
91 92 93 94 95 96
76.7174989 27.5490077 -49.6674079 -7.2955897 -63.0265487 -51.2980173
97 98 99 100 101 102
82.2095811 -95.9982430 9.1579985 -83.3945276 34.8951519 -33.3530943
103 104 105 106 107 108
155.0863627 101.0643332 -77.2657422 -67.5230306 -71.0104042 -1.6376174
109 110 111 112 113 114
84.5339345 14.0933307 -54.5497865 -71.3945994 -53.9170445 22.0027474
115 116 117 118 119 120
9.9161880 15.2833059 22.5767851 -25.7644253 -32.5201906 -109.2996717
121 122 123 124 125 126
-13.2195591 -100.3074186 31.1088790 93.2435278 160.5844430 -1.1260499
127 128 129 130 131 132
109.6945603 32.4947888 67.3949234 -48.9749900 -47.3846697 -146.2239661
133 134 135 136 137 138
-69.5226385 -82.6085644 74.7635886 -52.3998043 -0.1140466 25.1908913
139 140 141 142 143 144
6.8609880 -61.2726539 5.6315201 -24.5905135 2.8921632 -46.7039504
> postscript(file="/var/wessaorg/rcomp/tmp/62ivm1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 144
Frequency = 1
lag(myerror, k = 1) myerror
0 74.4286601 NA
1 -68.1809308 74.4286601
2 -166.1217475 -68.1809308
3 -155.7509980 -166.1217475
4 -21.4969605 -155.7509980
5 18.0274807 -21.4969605
6 -50.4104886 18.0274807
7 -7.6866780 -50.4104886
8 -83.3928552 -7.6866780
9 -102.3981511 -83.3928552
10 -118.8255284 -102.3981511
11 283.6153569 -118.8255284
12 164.8566564 283.6153569
13 23.5930328 164.8566564
14 49.8160317 23.5930328
15 -36.7673441 49.8160317
16 -8.5192432 -36.7673441
17 69.0278383 -8.5192432
18 240.4454540 69.0278383
19 332.4601343 240.4454540
20 229.4472651 332.4601343
21 155.6595864 229.4472651
22 106.0953973 155.6595864
23 186.4185360 106.0953973
24 212.6810212 186.4185360
25 52.2447980 212.6810212
26 64.7464146 52.2447980
27 -69.0911658 64.7464146
28 0.1078936 -69.0911658
29 19.3845131 0.1078936
30 107.6188207 19.3845131
31 -8.8264669 107.6188207
32 67.7238503 -8.8264669
33 -68.3277234 67.7238503
34 -4.9351400 -68.3277234
35 -14.4863027 -4.9351400
36 18.0502615 -14.4863027
37 -125.2941289 18.0502615
38 -59.5957818 -125.2941289
39 38.7265401 -59.5957818
40 -100.7844903 38.7265401
41 57.4363586 -100.7844903
42 174.5976597 57.4363586
43 169.5166464 174.5976597
44 2.7114669 169.5166464
45 43.0617864 2.7114669
46 -63.1338403 43.0617864
47 23.3569256 -63.1338403
48 34.9961139 23.3569256
49 -90.6686291 34.9961139
50 -47.5619663 -90.6686291
51 -59.0243079 -47.5619663
52 -133.2229369 -59.0243079
53 -155.6828910 -133.2229369
54 39.2370524 -155.6828910
55 66.8547492 39.2370524
56 -45.0438631 66.8547492
57 -26.4174416 -45.0438631
58 -87.3756925 -26.4174416
59 -26.1818845 -87.3756925
60 -39.0874453 -26.1818845
61 -13.9673981 -39.0874453
62 -116.4657937 -13.9673981
63 -51.6185905 -116.4657937
64 23.3146286 -51.6185905
65 -1.0300532 23.3146286
66 50.6409581 -1.0300532
67 60.4665988 50.6409581
68 78.2258642 60.4665988
69 -36.6276060 78.2258642
70 -174.4013529 -36.6276060
71 -152.6499665 -174.4013529
72 48.3000716 -152.6499665
73 -115.5711179 48.3000716
74 -24.8444794 -115.5711179
75 -103.6440236 -24.8444794
76 34.9231241 -103.6440236
77 -23.6003747 34.9231241
78 164.1389829 -23.6003747
79 162.6598464 164.1389829
80 45.7065084 162.6598464
81 -96.2656537 45.7065084
82 -48.9627537 -96.2656537
83 -68.1797354 -48.9627537
84 -10.2553060 -68.1797354
85 -132.8067527 -10.2553060
86 -3.7687642 -132.8067527
87 -108.6844204 -3.7687642
88 -22.8715779 -108.6844204
89 -66.3938746 -22.8715779
90 76.7174989 -66.3938746
91 27.5490077 76.7174989
92 -49.6674079 27.5490077
93 -7.2955897 -49.6674079
94 -63.0265487 -7.2955897
95 -51.2980173 -63.0265487
96 82.2095811 -51.2980173
97 -95.9982430 82.2095811
98 9.1579985 -95.9982430
99 -83.3945276 9.1579985
100 34.8951519 -83.3945276
101 -33.3530943 34.8951519
102 155.0863627 -33.3530943
103 101.0643332 155.0863627
104 -77.2657422 101.0643332
105 -67.5230306 -77.2657422
106 -71.0104042 -67.5230306
107 -1.6376174 -71.0104042
108 84.5339345 -1.6376174
109 14.0933307 84.5339345
110 -54.5497865 14.0933307
111 -71.3945994 -54.5497865
112 -53.9170445 -71.3945994
113 22.0027474 -53.9170445
114 9.9161880 22.0027474
115 15.2833059 9.9161880
116 22.5767851 15.2833059
117 -25.7644253 22.5767851
118 -32.5201906 -25.7644253
119 -109.2996717 -32.5201906
120 -13.2195591 -109.2996717
121 -100.3074186 -13.2195591
122 31.1088790 -100.3074186
123 93.2435278 31.1088790
124 160.5844430 93.2435278
125 -1.1260499 160.5844430
126 109.6945603 -1.1260499
127 32.4947888 109.6945603
128 67.3949234 32.4947888
129 -48.9749900 67.3949234
130 -47.3846697 -48.9749900
131 -146.2239661 -47.3846697
132 -69.5226385 -146.2239661
133 -82.6085644 -69.5226385
134 74.7635886 -82.6085644
135 -52.3998043 74.7635886
136 -0.1140466 -52.3998043
137 25.1908913 -0.1140466
138 6.8609880 25.1908913
139 -61.2726539 6.8609880
140 5.6315201 -61.2726539
141 -24.5905135 5.6315201
142 2.8921632 -24.5905135
143 -46.7039504 2.8921632
144 NA -46.7039504
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -68.1809308 74.4286601
[2,] -166.1217475 -68.1809308
[3,] -155.7509980 -166.1217475
[4,] -21.4969605 -155.7509980
[5,] 18.0274807 -21.4969605
[6,] -50.4104886 18.0274807
[7,] -7.6866780 -50.4104886
[8,] -83.3928552 -7.6866780
[9,] -102.3981511 -83.3928552
[10,] -118.8255284 -102.3981511
[11,] 283.6153569 -118.8255284
[12,] 164.8566564 283.6153569
[13,] 23.5930328 164.8566564
[14,] 49.8160317 23.5930328
[15,] -36.7673441 49.8160317
[16,] -8.5192432 -36.7673441
[17,] 69.0278383 -8.5192432
[18,] 240.4454540 69.0278383
[19,] 332.4601343 240.4454540
[20,] 229.4472651 332.4601343
[21,] 155.6595864 229.4472651
[22,] 106.0953973 155.6595864
[23,] 186.4185360 106.0953973
[24,] 212.6810212 186.4185360
[25,] 52.2447980 212.6810212
[26,] 64.7464146 52.2447980
[27,] -69.0911658 64.7464146
[28,] 0.1078936 -69.0911658
[29,] 19.3845131 0.1078936
[30,] 107.6188207 19.3845131
[31,] -8.8264669 107.6188207
[32,] 67.7238503 -8.8264669
[33,] -68.3277234 67.7238503
[34,] -4.9351400 -68.3277234
[35,] -14.4863027 -4.9351400
[36,] 18.0502615 -14.4863027
[37,] -125.2941289 18.0502615
[38,] -59.5957818 -125.2941289
[39,] 38.7265401 -59.5957818
[40,] -100.7844903 38.7265401
[41,] 57.4363586 -100.7844903
[42,] 174.5976597 57.4363586
[43,] 169.5166464 174.5976597
[44,] 2.7114669 169.5166464
[45,] 43.0617864 2.7114669
[46,] -63.1338403 43.0617864
[47,] 23.3569256 -63.1338403
[48,] 34.9961139 23.3569256
[49,] -90.6686291 34.9961139
[50,] -47.5619663 -90.6686291
[51,] -59.0243079 -47.5619663
[52,] -133.2229369 -59.0243079
[53,] -155.6828910 -133.2229369
[54,] 39.2370524 -155.6828910
[55,] 66.8547492 39.2370524
[56,] -45.0438631 66.8547492
[57,] -26.4174416 -45.0438631
[58,] -87.3756925 -26.4174416
[59,] -26.1818845 -87.3756925
[60,] -39.0874453 -26.1818845
[61,] -13.9673981 -39.0874453
[62,] -116.4657937 -13.9673981
[63,] -51.6185905 -116.4657937
[64,] 23.3146286 -51.6185905
[65,] -1.0300532 23.3146286
[66,] 50.6409581 -1.0300532
[67,] 60.4665988 50.6409581
[68,] 78.2258642 60.4665988
[69,] -36.6276060 78.2258642
[70,] -174.4013529 -36.6276060
[71,] -152.6499665 -174.4013529
[72,] 48.3000716 -152.6499665
[73,] -115.5711179 48.3000716
[74,] -24.8444794 -115.5711179
[75,] -103.6440236 -24.8444794
[76,] 34.9231241 -103.6440236
[77,] -23.6003747 34.9231241
[78,] 164.1389829 -23.6003747
[79,] 162.6598464 164.1389829
[80,] 45.7065084 162.6598464
[81,] -96.2656537 45.7065084
[82,] -48.9627537 -96.2656537
[83,] -68.1797354 -48.9627537
[84,] -10.2553060 -68.1797354
[85,] -132.8067527 -10.2553060
[86,] -3.7687642 -132.8067527
[87,] -108.6844204 -3.7687642
[88,] -22.8715779 -108.6844204
[89,] -66.3938746 -22.8715779
[90,] 76.7174989 -66.3938746
[91,] 27.5490077 76.7174989
[92,] -49.6674079 27.5490077
[93,] -7.2955897 -49.6674079
[94,] -63.0265487 -7.2955897
[95,] -51.2980173 -63.0265487
[96,] 82.2095811 -51.2980173
[97,] -95.9982430 82.2095811
[98,] 9.1579985 -95.9982430
[99,] -83.3945276 9.1579985
[100,] 34.8951519 -83.3945276
[101,] -33.3530943 34.8951519
[102,] 155.0863627 -33.3530943
[103,] 101.0643332 155.0863627
[104,] -77.2657422 101.0643332
[105,] -67.5230306 -77.2657422
[106,] -71.0104042 -67.5230306
[107,] -1.6376174 -71.0104042
[108,] 84.5339345 -1.6376174
[109,] 14.0933307 84.5339345
[110,] -54.5497865 14.0933307
[111,] -71.3945994 -54.5497865
[112,] -53.9170445 -71.3945994
[113,] 22.0027474 -53.9170445
[114,] 9.9161880 22.0027474
[115,] 15.2833059 9.9161880
[116,] 22.5767851 15.2833059
[117,] -25.7644253 22.5767851
[118,] -32.5201906 -25.7644253
[119,] -109.2996717 -32.5201906
[120,] -13.2195591 -109.2996717
[121,] -100.3074186 -13.2195591
[122,] 31.1088790 -100.3074186
[123,] 93.2435278 31.1088790
[124,] 160.5844430 93.2435278
[125,] -1.1260499 160.5844430
[126,] 109.6945603 -1.1260499
[127,] 32.4947888 109.6945603
[128,] 67.3949234 32.4947888
[129,] -48.9749900 67.3949234
[130,] -47.3846697 -48.9749900
[131,] -146.2239661 -47.3846697
[132,] -69.5226385 -146.2239661
[133,] -82.6085644 -69.5226385
[134,] 74.7635886 -82.6085644
[135,] -52.3998043 74.7635886
[136,] -0.1140466 -52.3998043
[137,] 25.1908913 -0.1140466
[138,] 6.8609880 25.1908913
[139,] -61.2726539 6.8609880
[140,] 5.6315201 -61.2726539
[141,] -24.5905135 5.6315201
[142,] 2.8921632 -24.5905135
[143,] -46.7039504 2.8921632
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -68.1809308 74.4286601
2 -166.1217475 -68.1809308
3 -155.7509980 -166.1217475
4 -21.4969605 -155.7509980
5 18.0274807 -21.4969605
6 -50.4104886 18.0274807
7 -7.6866780 -50.4104886
8 -83.3928552 -7.6866780
9 -102.3981511 -83.3928552
10 -118.8255284 -102.3981511
11 283.6153569 -118.8255284
12 164.8566564 283.6153569
13 23.5930328 164.8566564
14 49.8160317 23.5930328
15 -36.7673441 49.8160317
16 -8.5192432 -36.7673441
17 69.0278383 -8.5192432
18 240.4454540 69.0278383
19 332.4601343 240.4454540
20 229.4472651 332.4601343
21 155.6595864 229.4472651
22 106.0953973 155.6595864
23 186.4185360 106.0953973
24 212.6810212 186.4185360
25 52.2447980 212.6810212
26 64.7464146 52.2447980
27 -69.0911658 64.7464146
28 0.1078936 -69.0911658
29 19.3845131 0.1078936
30 107.6188207 19.3845131
31 -8.8264669 107.6188207
32 67.7238503 -8.8264669
33 -68.3277234 67.7238503
34 -4.9351400 -68.3277234
35 -14.4863027 -4.9351400
36 18.0502615 -14.4863027
37 -125.2941289 18.0502615
38 -59.5957818 -125.2941289
39 38.7265401 -59.5957818
40 -100.7844903 38.7265401
41 57.4363586 -100.7844903
42 174.5976597 57.4363586
43 169.5166464 174.5976597
44 2.7114669 169.5166464
45 43.0617864 2.7114669
46 -63.1338403 43.0617864
47 23.3569256 -63.1338403
48 34.9961139 23.3569256
49 -90.6686291 34.9961139
50 -47.5619663 -90.6686291
51 -59.0243079 -47.5619663
52 -133.2229369 -59.0243079
53 -155.6828910 -133.2229369
54 39.2370524 -155.6828910
55 66.8547492 39.2370524
56 -45.0438631 66.8547492
57 -26.4174416 -45.0438631
58 -87.3756925 -26.4174416
59 -26.1818845 -87.3756925
60 -39.0874453 -26.1818845
61 -13.9673981 -39.0874453
62 -116.4657937 -13.9673981
63 -51.6185905 -116.4657937
64 23.3146286 -51.6185905
65 -1.0300532 23.3146286
66 50.6409581 -1.0300532
67 60.4665988 50.6409581
68 78.2258642 60.4665988
69 -36.6276060 78.2258642
70 -174.4013529 -36.6276060
71 -152.6499665 -174.4013529
72 48.3000716 -152.6499665
73 -115.5711179 48.3000716
74 -24.8444794 -115.5711179
75 -103.6440236 -24.8444794
76 34.9231241 -103.6440236
77 -23.6003747 34.9231241
78 164.1389829 -23.6003747
79 162.6598464 164.1389829
80 45.7065084 162.6598464
81 -96.2656537 45.7065084
82 -48.9627537 -96.2656537
83 -68.1797354 -48.9627537
84 -10.2553060 -68.1797354
85 -132.8067527 -10.2553060
86 -3.7687642 -132.8067527
87 -108.6844204 -3.7687642
88 -22.8715779 -108.6844204
89 -66.3938746 -22.8715779
90 76.7174989 -66.3938746
91 27.5490077 76.7174989
92 -49.6674079 27.5490077
93 -7.2955897 -49.6674079
94 -63.0265487 -7.2955897
95 -51.2980173 -63.0265487
96 82.2095811 -51.2980173
97 -95.9982430 82.2095811
98 9.1579985 -95.9982430
99 -83.3945276 9.1579985
100 34.8951519 -83.3945276
101 -33.3530943 34.8951519
102 155.0863627 -33.3530943
103 101.0643332 155.0863627
104 -77.2657422 101.0643332
105 -67.5230306 -77.2657422
106 -71.0104042 -67.5230306
107 -1.6376174 -71.0104042
108 84.5339345 -1.6376174
109 14.0933307 84.5339345
110 -54.5497865 14.0933307
111 -71.3945994 -54.5497865
112 -53.9170445 -71.3945994
113 22.0027474 -53.9170445
114 9.9161880 22.0027474
115 15.2833059 9.9161880
116 22.5767851 15.2833059
117 -25.7644253 22.5767851
118 -32.5201906 -25.7644253
119 -109.2996717 -32.5201906
120 -13.2195591 -109.2996717
121 -100.3074186 -13.2195591
122 31.1088790 -100.3074186
123 93.2435278 31.1088790
124 160.5844430 93.2435278
125 -1.1260499 160.5844430
126 109.6945603 -1.1260499
127 32.4947888 109.6945603
128 67.3949234 32.4947888
129 -48.9749900 67.3949234
130 -47.3846697 -48.9749900
131 -146.2239661 -47.3846697
132 -69.5226385 -146.2239661
133 -82.6085644 -69.5226385
134 74.7635886 -82.6085644
135 -52.3998043 74.7635886
136 -0.1140466 -52.3998043
137 25.1908913 -0.1140466
138 6.8609880 25.1908913
139 -61.2726539 6.8609880
140 5.6315201 -61.2726539
141 -24.5905135 5.6315201
142 2.8921632 -24.5905135
143 -46.7039504 2.8921632
> 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/wessaorg/rcomp/tmp/7fp491353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8qgyc1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/98ypj1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/108gkz1353865580.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11p6lf1353865580.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/wessaorg/rcomp/tmp/12day71353865580.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/wessaorg/rcomp/tmp/13kkhb1353865580.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/wessaorg/rcomp/tmp/14pbok1353865580.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/wessaorg/rcomp/tmp/154gt01353865580.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/wessaorg/rcomp/tmp/16pfp51353865580.tab")
+ }
>
> try(system("convert tmp/1i2tx1353865580.ps tmp/1i2tx1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/24mhz1353865580.ps tmp/24mhz1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/3831e1353865580.ps tmp/3831e1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/49q8h1353865580.ps tmp/49q8h1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vrde1353865580.ps tmp/5vrde1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/62ivm1353865580.ps tmp/62ivm1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fp491353865580.ps tmp/7fp491353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/8qgyc1353865580.ps tmp/8qgyc1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/98ypj1353865580.ps tmp/98ypj1353865580.png",intern=TRUE))
character(0)
> try(system("convert tmp/108gkz1353865580.ps tmp/108gkz1353865580.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.019 1.112 8.204