R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(119.992
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+ ,0.00003
+ ,0.00412
+ ,0.00396
+ ,0.01235
+ ,0.02574
+ ,0.255
+ ,0.01454
+ ,0.01582
+ ,0.01758
+ ,0.04363
+ ,0.04441
+ ,19.368
+ ,0
+ ,0.508479
+ ,0.683761
+ ,-6.934474
+ ,0.15989
+ ,2.316346
+ ,174.188
+ ,230.978
+ ,94.261
+ ,0.00459
+ ,0.00003
+ ,0.00263
+ ,0.00259
+ ,0.0079
+ ,0.04087
+ ,0.405
+ ,0.02336
+ ,0.02498
+ ,0.02745
+ ,0.07008
+ ,0.02764
+ ,19.517
+ ,0
+ ,0.448439
+ ,0.657899
+ ,-6.538586
+ ,0.121952
+ ,2.657476
+ ,209.516
+ ,253.017
+ ,89.488
+ ,0.00564
+ ,0.00003
+ ,0.00331
+ ,0.00292
+ ,0.00994
+ ,0.02751
+ ,0.263
+ ,0.01604
+ ,0.01657
+ ,0.01879
+ ,0.04812
+ ,0.0181
+ ,19.147
+ ,0
+ ,0.431674
+ ,0.683244
+ ,-6.195325
+ ,0.129303
+ ,2.784312
+ ,174.688
+ ,240.005
+ ,74.287
+ ,0.0136
+ ,0.00008
+ ,0.00624
+ ,0.00564
+ ,0.01873
+ ,0.02308
+ ,0.256
+ ,0.01268
+ ,0.01365
+ ,0.01667
+ ,0.03804
+ ,0.10715
+ ,17.883
+ ,0
+ ,0.407567
+ ,0.655683
+ ,-6.787197
+ ,0.158453
+ ,2.679772
+ ,198.764
+ ,396.961
+ ,74.904
+ ,0.0074
+ ,0.00004
+ ,0.0037
+ ,0.0039
+ ,0.01109
+ ,0.02296
+ ,0.241
+ ,0.01265
+ ,0.01321
+ ,0.01588
+ ,0.03794
+ ,0.07223
+ ,19.02
+ ,0
+ ,0.451221
+ ,0.643956
+ ,-6.744577
+ ,0.207454
+ ,2.138608
+ ,214.289
+ ,260.277
+ ,77.973
+ ,0.00567
+ ,0.00003
+ ,0.00295
+ ,0.00317
+ ,0.00885
+ ,0.01884
+ ,0.19
+ ,0.01026
+ ,0.01161
+ ,0.01373
+ ,0.03078
+ ,0.04398
+ ,21.209
+ ,0
+ ,0.462803
+ ,0.664357
+ ,-5.724056
+ ,0.190667
+ ,2.555477)
+ ,dim=c(22
+ ,195)
+ ,dimnames=list(c('MDVP:Fo(Hz)'
+ ,'MDVP:Fhi(Hz)'
+ ,'MDVP:Flo(Hz)'
+ ,'MDVP:Jitter(%)'
+ ,'MDVP:Jitter(Abs)'
+ ,'MDVP:RAP'
+ ,'MDVP:PPQ'
+ ,'Jitter:DDP'
+ ,'MDVP:Shimmer'
+ ,'MDVP:Shimmer(dB)'
+ ,'Shimmer:APQ3'
+ ,'Shimmer:APQ5'
+ ,'MDVP:APQ'
+ ,'Shimmer:DDA'
+ ,'NHR'
+ ,'HNR'
+ ,'status'
+ ,'RPDE'
+ ,'DFA'
+ ,'spread1'
+ ,'spread2'
+ ,'D2')
+ ,1:195))
> y <- array(NA,dim=c(22,195),dimnames=list(c('MDVP:Fo(Hz)','MDVP:Fhi(Hz)','MDVP:Flo(Hz)','MDVP:Jitter(%)','MDVP:Jitter(Abs)','MDVP:RAP','MDVP:PPQ','Jitter:DDP','MDVP:Shimmer','MDVP:Shimmer(dB)','Shimmer:APQ3','Shimmer:APQ5','MDVP:APQ','Shimmer:DDA','NHR','HNR','status','RPDE','DFA','spread1','spread2','D2'),1:195))
> 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. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Multiple Regression (v1.0.29) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following objects 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
MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%) MDVP:Jitter(Abs)
1 119.992 157.302 74.997 0.00784 7.0e-05
2 122.400 148.650 113.819 0.00968 8.0e-05
3 116.682 131.111 111.555 0.01050 9.0e-05
4 116.676 137.871 111.366 0.00997 9.0e-05
5 116.014 141.781 110.655 0.01284 1.1e-04
6 120.552 131.162 113.787 0.00968 8.0e-05
7 120.267 137.244 114.820 0.00333 3.0e-05
8 107.332 113.840 104.315 0.00290 3.0e-05
9 95.730 132.068 91.754 0.00551 6.0e-05
10 95.056 120.103 91.226 0.00532 6.0e-05
11 88.333 112.240 84.072 0.00505 6.0e-05
12 91.904 115.871 86.292 0.00540 6.0e-05
13 136.926 159.866 131.276 0.00293 2.0e-05
14 139.173 179.139 76.556 0.00390 3.0e-05
15 152.845 163.305 75.836 0.00294 2.0e-05
16 142.167 217.455 83.159 0.00369 3.0e-05
17 144.188 349.259 82.764 0.00544 4.0e-05
18 168.778 232.181 75.603 0.00718 4.0e-05
19 153.046 175.829 68.623 0.00742 5.0e-05
20 156.405 189.398 142.822 0.00768 5.0e-05
21 153.848 165.738 65.782 0.00840 5.0e-05
22 153.880 172.860 78.128 0.00480 3.0e-05
23 167.930 193.221 79.068 0.00442 3.0e-05
24 173.917 192.735 86.180 0.00476 3.0e-05
25 163.656 200.841 76.779 0.00742 5.0e-05
26 104.400 206.002 77.968 0.00633 6.0e-05
27 171.041 208.313 75.501 0.00455 3.0e-05
28 146.845 208.701 81.737 0.00496 3.0e-05
29 155.358 227.383 80.055 0.00310 2.0e-05
30 162.568 198.346 77.630 0.00502 3.0e-05
31 197.076 206.896 192.055 0.00289 1.0e-05
32 199.228 209.512 192.091 0.00241 1.0e-05
33 198.383 215.203 193.104 0.00212 1.0e-05
34 202.266 211.604 197.079 0.00180 9.0e-06
35 203.184 211.526 196.160 0.00178 9.0e-06
36 201.464 210.565 195.708 0.00198 1.0e-05
37 177.876 192.921 168.013 0.00411 2.0e-05
38 176.170 185.604 163.564 0.00369 2.0e-05
39 180.198 201.249 175.456 0.00284 2.0e-05
40 187.733 202.324 173.015 0.00316 2.0e-05
41 186.163 197.724 177.584 0.00298 2.0e-05
42 184.055 196.537 166.977 0.00258 1.0e-05
43 237.226 247.326 225.227 0.00298 1.0e-05
44 241.404 248.834 232.483 0.00281 1.0e-05
45 243.439 250.912 232.435 0.00210 9.0e-06
46 242.852 255.034 227.911 0.00225 9.0e-06
47 245.510 262.090 231.848 0.00235 1.0e-05
48 252.455 261.487 182.786 0.00185 7.0e-06
49 122.188 128.611 115.765 0.00524 4.0e-05
50 122.964 130.049 114.676 0.00428 3.0e-05
51 124.445 135.069 117.495 0.00431 3.0e-05
52 126.344 134.231 112.773 0.00448 4.0e-05
53 128.001 138.052 122.080 0.00436 3.0e-05
54 129.336 139.867 118.604 0.00490 4.0e-05
55 108.807 134.656 102.874 0.00761 7.0e-05
56 109.860 126.358 104.437 0.00874 8.0e-05
57 110.417 131.067 103.370 0.00784 7.0e-05
58 117.274 129.916 110.402 0.00752 6.0e-05
59 116.879 131.897 108.153 0.00788 7.0e-05
60 114.847 271.314 104.680 0.00867 8.0e-05
61 209.144 237.494 109.379 0.00282 1.0e-05
62 223.365 238.987 98.664 0.00264 1.0e-05
63 222.236 231.345 205.495 0.00266 1.0e-05
64 228.832 234.619 223.634 0.00296 1.0e-05
65 229.401 252.221 221.156 0.00205 9.0e-06
66 228.969 239.541 113.201 0.00238 1.0e-05
67 140.341 159.774 67.021 0.00817 6.0e-05
68 136.969 166.607 66.004 0.00923 7.0e-05
69 143.533 162.215 65.809 0.01101 8.0e-05
70 148.090 162.824 67.343 0.00762 5.0e-05
71 142.729 162.408 65.476 0.00831 6.0e-05
72 136.358 176.595 65.750 0.00971 7.0e-05
73 120.080 139.710 111.208 0.00405 3.0e-05
74 112.014 588.518 107.024 0.00533 5.0e-05
75 110.793 128.101 107.316 0.00494 4.0e-05
76 110.707 122.611 105.007 0.00516 5.0e-05
77 112.876 148.826 106.981 0.00500 4.0e-05
78 110.568 125.394 106.821 0.00462 4.0e-05
79 95.385 102.145 90.264 0.00608 6.0e-05
80 100.770 115.697 85.545 0.01038 1.0e-04
81 96.106 108.664 84.510 0.00694 7.0e-05
82 95.605 107.715 87.549 0.00702 7.0e-05
83 100.960 110.019 95.628 0.00606 6.0e-05
84 98.804 102.305 87.804 0.00432 4.0e-05
85 176.858 205.560 75.344 0.00747 4.0e-05
86 180.978 200.125 155.495 0.00406 2.0e-05
87 178.222 202.450 141.047 0.00321 2.0e-05
88 176.281 227.381 125.610 0.00520 3.0e-05
89 173.898 211.350 74.677 0.00448 3.0e-05
90 179.711 225.930 144.878 0.00709 4.0e-05
91 166.605 206.008 78.032 0.00742 4.0e-05
92 151.955 163.335 147.226 0.00419 3.0e-05
93 148.272 164.989 142.299 0.00459 3.0e-05
94 152.125 161.469 76.596 0.00382 3.0e-05
95 157.821 172.975 68.401 0.00358 2.0e-05
96 157.447 163.267 149.605 0.00369 2.0e-05
97 159.116 168.913 144.811 0.00342 2.0e-05
98 125.036 143.946 116.187 0.01280 1.0e-04
99 125.791 140.557 96.206 0.01378 1.1e-04
100 126.512 141.756 99.770 0.01936 1.5e-04
101 125.641 141.068 116.346 0.03316 2.6e-04
102 128.451 150.449 75.632 0.01551 1.2e-04
103 139.224 586.567 66.157 0.03011 2.2e-04
104 150.258 154.609 75.349 0.00248 2.0e-05
105 154.003 160.267 128.621 0.00183 1.0e-05
106 149.689 160.368 133.608 0.00257 2.0e-05
107 155.078 163.736 144.148 0.00168 1.0e-05
108 151.884 157.765 133.751 0.00258 2.0e-05
109 151.989 157.339 132.857 0.00174 1.0e-05
110 193.030 208.900 80.297 0.00766 4.0e-05
111 200.714 223.982 89.686 0.00621 3.0e-05
112 208.519 220.315 199.020 0.00609 3.0e-05
113 204.664 221.300 189.621 0.00841 4.0e-05
114 210.141 232.706 185.258 0.00534 3.0e-05
115 206.327 226.355 92.020 0.00495 2.0e-05
116 151.872 492.892 69.085 0.00856 6.0e-05
117 158.219 442.557 71.948 0.00476 3.0e-05
118 170.756 450.247 79.032 0.00555 3.0e-05
119 178.285 442.824 82.063 0.00462 3.0e-05
120 217.116 233.481 93.978 0.00404 2.0e-05
121 128.940 479.697 88.251 0.00581 5.0e-05
122 176.824 215.293 83.961 0.00460 3.0e-05
123 138.190 203.522 83.340 0.00704 5.0e-05
124 182.018 197.173 79.187 0.00842 5.0e-05
125 156.239 195.107 79.820 0.00694 4.0e-05
126 145.174 198.109 80.637 0.00733 5.0e-05
127 138.145 197.238 81.114 0.00544 4.0e-05
128 166.888 198.966 79.512 0.00638 4.0e-05
129 119.031 127.533 109.216 0.00440 4.0e-05
130 120.078 126.632 105.667 0.00270 2.0e-05
131 120.289 128.143 100.209 0.00492 4.0e-05
132 120.256 125.306 104.773 0.00407 3.0e-05
133 119.056 125.213 86.795 0.00346 3.0e-05
134 118.747 123.723 109.836 0.00331 3.0e-05
135 106.516 112.777 93.105 0.00589 6.0e-05
136 110.453 127.611 105.554 0.00494 4.0e-05
137 113.400 133.344 107.816 0.00451 4.0e-05
138 113.166 130.270 100.673 0.00502 4.0e-05
139 112.239 126.609 104.095 0.00472 4.0e-05
140 116.150 131.731 109.815 0.00381 3.0e-05
141 170.368 268.796 79.543 0.00571 3.0e-05
142 208.083 253.792 91.802 0.00757 4.0e-05
143 198.458 219.290 148.691 0.00376 2.0e-05
144 202.805 231.508 86.232 0.00370 2.0e-05
145 202.544 241.350 164.168 0.00254 1.0e-05
146 223.361 263.872 87.638 0.00352 2.0e-05
147 169.774 191.759 151.451 0.01568 9.0e-05
148 183.520 216.814 161.340 0.01466 8.0e-05
149 188.620 216.302 165.982 0.01719 9.0e-05
150 202.632 565.740 177.258 0.01627 8.0e-05
151 186.695 211.961 149.442 0.01872 1.0e-04
152 192.818 224.429 168.793 0.03107 1.6e-04
153 198.116 233.099 174.478 0.02714 1.4e-04
154 121.345 139.644 98.250 0.00684 6.0e-05
155 119.100 128.442 88.833 0.00692 6.0e-05
156 117.870 127.349 95.654 0.00647 5.0e-05
157 122.336 142.369 94.794 0.00727 6.0e-05
158 117.963 134.209 100.757 0.01813 1.5e-04
159 126.144 154.284 97.543 0.00975 8.0e-05
160 127.930 138.752 112.173 0.00605 5.0e-05
161 114.238 124.393 77.022 0.00581 5.0e-05
162 115.322 135.738 107.802 0.00619 5.0e-05
163 114.554 126.778 91.121 0.00651 6.0e-05
164 112.150 131.669 97.527 0.00519 5.0e-05
165 102.273 142.830 85.902 0.00907 9.0e-05
166 236.200 244.663 102.137 0.00277 1.0e-05
167 237.323 243.709 229.256 0.00303 1.0e-05
168 260.105 264.919 237.303 0.00339 1.0e-05
169 197.569 217.627 90.794 0.00803 4.0e-05
170 240.301 245.135 219.783 0.00517 2.0e-05
171 244.990 272.210 239.170 0.00451 2.0e-05
172 112.547 133.374 105.715 0.00355 3.0e-05
173 110.739 113.597 100.139 0.00356 3.0e-05
174 113.715 116.443 96.913 0.00349 3.0e-05
175 117.004 144.466 99.923 0.00353 3.0e-05
176 115.380 123.109 108.634 0.00332 3.0e-05
177 116.388 129.038 108.970 0.00346 3.0e-05
178 151.737 190.204 129.859 0.00314 2.0e-05
179 148.790 158.359 138.990 0.00309 2.0e-05
180 148.143 155.982 135.041 0.00392 3.0e-05
181 150.440 163.441 144.736 0.00396 3.0e-05
182 148.462 161.078 141.998 0.00397 3.0e-05
183 149.818 163.417 144.786 0.00336 2.0e-05
184 117.226 123.925 106.656 0.00417 4.0e-05
185 116.848 217.552 99.503 0.00531 5.0e-05
186 116.286 177.291 96.983 0.00314 3.0e-05
187 116.556 592.030 86.228 0.00496 4.0e-05
188 116.342 581.289 94.246 0.00267 2.0e-05
189 114.563 119.167 86.647 0.00327 3.0e-05
190 201.774 262.707 78.228 0.00694 3.0e-05
191 174.188 230.978 94.261 0.00459 3.0e-05
192 209.516 253.017 89.488 0.00564 3.0e-05
193 174.688 240.005 74.287 0.01360 8.0e-05
194 198.764 396.961 74.904 0.00740 4.0e-05
195 214.289 260.277 77.973 0.00567 3.0e-05
MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer MDVP:Shimmer(dB) Shimmer:APQ3
1 0.00370 0.00554 0.01109 0.04374 0.426 0.02182
2 0.00465 0.00696 0.01394 0.06134 0.626 0.03134
3 0.00544 0.00781 0.01633 0.05233 0.482 0.02757
4 0.00502 0.00698 0.01505 0.05492 0.517 0.02924
5 0.00655 0.00908 0.01966 0.06425 0.584 0.03490
6 0.00463 0.00750 0.01388 0.04701 0.456 0.02328
7 0.00155 0.00202 0.00466 0.01608 0.140 0.00779
8 0.00144 0.00182 0.00431 0.01567 0.134 0.00829
9 0.00293 0.00332 0.00880 0.02093 0.191 0.01073
10 0.00268 0.00332 0.00803 0.02838 0.255 0.01441
11 0.00254 0.00330 0.00763 0.02143 0.197 0.01079
12 0.00281 0.00336 0.00844 0.02752 0.249 0.01424
13 0.00118 0.00153 0.00355 0.01259 0.112 0.00656
14 0.00165 0.00208 0.00496 0.01642 0.154 0.00728
15 0.00121 0.00149 0.00364 0.01828 0.158 0.01064
16 0.00157 0.00203 0.00471 0.01503 0.126 0.00772
17 0.00211 0.00292 0.00632 0.02047 0.192 0.00969
18 0.00284 0.00387 0.00853 0.03327 0.348 0.01441
19 0.00364 0.00432 0.01092 0.05517 0.542 0.02471
20 0.00372 0.00399 0.01116 0.03995 0.348 0.01721
21 0.00428 0.00450 0.01285 0.03810 0.328 0.01667
22 0.00232 0.00267 0.00696 0.04137 0.370 0.02021
23 0.00220 0.00247 0.00661 0.04351 0.377 0.02228
24 0.00221 0.00258 0.00663 0.04192 0.364 0.02187
25 0.00380 0.00390 0.01140 0.01659 0.164 0.00738
26 0.00316 0.00375 0.00948 0.03767 0.381 0.01732
27 0.00250 0.00234 0.00750 0.01966 0.186 0.00889
28 0.00250 0.00275 0.00749 0.01919 0.198 0.00883
29 0.00159 0.00176 0.00476 0.01718 0.161 0.00769
30 0.00280 0.00253 0.00841 0.01791 0.168 0.00793
31 0.00166 0.00168 0.00498 0.01098 0.097 0.00563
32 0.00134 0.00138 0.00402 0.01015 0.089 0.00504
33 0.00113 0.00135 0.00339 0.01263 0.111 0.00640
34 0.00093 0.00107 0.00278 0.00954 0.085 0.00469
35 0.00094 0.00106 0.00283 0.00958 0.085 0.00468
36 0.00105 0.00115 0.00314 0.01194 0.107 0.00586
37 0.00233 0.00241 0.00700 0.02126 0.189 0.01154
38 0.00205 0.00218 0.00616 0.01851 0.168 0.00938
39 0.00153 0.00166 0.00459 0.01444 0.131 0.00726
40 0.00168 0.00182 0.00504 0.01663 0.151 0.00829
41 0.00165 0.00175 0.00496 0.01495 0.135 0.00774
42 0.00134 0.00147 0.00403 0.01463 0.132 0.00742
43 0.00169 0.00182 0.00507 0.01752 0.164 0.01035
44 0.00157 0.00173 0.00470 0.01760 0.154 0.01006
45 0.00109 0.00137 0.00327 0.01419 0.126 0.00777
46 0.00117 0.00139 0.00350 0.01494 0.134 0.00847
47 0.00127 0.00148 0.00380 0.01608 0.141 0.00906
48 0.00092 0.00113 0.00276 0.01152 0.103 0.00614
49 0.00169 0.00203 0.00507 0.01613 0.143 0.00855
50 0.00124 0.00155 0.00373 0.01681 0.154 0.00930
51 0.00141 0.00167 0.00422 0.02184 0.197 0.01241
52 0.00131 0.00169 0.00393 0.02033 0.185 0.01143
53 0.00137 0.00166 0.00411 0.02297 0.210 0.01323
54 0.00165 0.00183 0.00495 0.02498 0.228 0.01396
55 0.00349 0.00486 0.01046 0.02719 0.255 0.01483
56 0.00398 0.00539 0.01193 0.03209 0.307 0.01789
57 0.00352 0.00514 0.01056 0.03715 0.334 0.02032
58 0.00299 0.00469 0.00898 0.02293 0.221 0.01189
59 0.00334 0.00493 0.01003 0.02645 0.265 0.01394
60 0.00373 0.00520 0.01120 0.03225 0.350 0.01805
61 0.00147 0.00152 0.00442 0.01861 0.170 0.00975
62 0.00154 0.00151 0.00461 0.01906 0.165 0.01013
63 0.00152 0.00144 0.00457 0.01643 0.145 0.00867
64 0.00175 0.00155 0.00526 0.01644 0.145 0.00882
65 0.00114 0.00113 0.00342 0.01457 0.129 0.00769
66 0.00136 0.00140 0.00408 0.01745 0.154 0.00942
67 0.00430 0.00440 0.01289 0.03198 0.313 0.01830
68 0.00507 0.00463 0.01520 0.03111 0.308 0.01638
69 0.00647 0.00467 0.01941 0.05384 0.478 0.03152
70 0.00467 0.00354 0.01400 0.05428 0.497 0.03357
71 0.00469 0.00419 0.01407 0.03485 0.365 0.01868
72 0.00534 0.00478 0.01601 0.04978 0.483 0.02749
73 0.00180 0.00220 0.00540 0.01706 0.152 0.00974
74 0.00268 0.00329 0.00805 0.02448 0.226 0.01373
75 0.00260 0.00283 0.00780 0.02442 0.216 0.01432
76 0.00277 0.00289 0.00831 0.02215 0.206 0.01284
77 0.00270 0.00289 0.00810 0.03999 0.350 0.02413
78 0.00226 0.00280 0.00677 0.02199 0.197 0.01284
79 0.00331 0.00332 0.00994 0.03202 0.263 0.01803
80 0.00622 0.00576 0.01865 0.03121 0.361 0.01773
81 0.00389 0.00415 0.01168 0.04024 0.364 0.02266
82 0.00428 0.00371 0.01283 0.03156 0.296 0.01792
83 0.00351 0.00348 0.01053 0.02427 0.216 0.01371
84 0.00247 0.00258 0.00742 0.02223 0.202 0.01277
85 0.00418 0.00420 0.01254 0.04795 0.435 0.02679
86 0.00220 0.00244 0.00659 0.03852 0.331 0.02107
87 0.00163 0.00194 0.00488 0.03759 0.327 0.02073
88 0.00287 0.00312 0.00862 0.06511 0.580 0.03671
89 0.00237 0.00254 0.00710 0.06727 0.650 0.03788
90 0.00391 0.00419 0.01172 0.04313 0.442 0.02297
91 0.00387 0.00453 0.01161 0.06640 0.634 0.03650
92 0.00224 0.00227 0.00672 0.07959 0.772 0.04421
93 0.00250 0.00256 0.00750 0.04190 0.383 0.02383
94 0.00191 0.00226 0.00574 0.05925 0.637 0.03341
95 0.00196 0.00196 0.00587 0.03716 0.307 0.02062
96 0.00201 0.00197 0.00602 0.03272 0.283 0.01813
97 0.00178 0.00184 0.00535 0.03381 0.307 0.01806
98 0.00743 0.00623 0.02228 0.03886 0.342 0.02135
99 0.00826 0.00655 0.02478 0.04689 0.422 0.02542
100 0.01159 0.00990 0.03476 0.06734 0.659 0.03611
101 0.02144 0.01522 0.06433 0.09178 0.891 0.05358
102 0.00905 0.00909 0.02716 0.06170 0.584 0.03223
103 0.01854 0.01628 0.05563 0.09419 0.930 0.05551
104 0.00105 0.00136 0.00315 0.01131 0.107 0.00522
105 0.00076 0.00100 0.00229 0.01030 0.094 0.00469
106 0.00116 0.00134 0.00349 0.01346 0.126 0.00660
107 0.00068 0.00092 0.00204 0.01064 0.097 0.00522
108 0.00115 0.00122 0.00346 0.01450 0.137 0.00633
109 0.00075 0.00096 0.00225 0.01024 0.093 0.00455
110 0.00450 0.00389 0.01351 0.03044 0.275 0.01771
111 0.00371 0.00337 0.01112 0.02286 0.207 0.01192
112 0.00368 0.00339 0.01105 0.01761 0.155 0.00952
113 0.00502 0.00485 0.01506 0.02378 0.210 0.01277
114 0.00321 0.00280 0.00964 0.01680 0.149 0.00861
115 0.00302 0.00246 0.00905 0.02105 0.209 0.01107
116 0.00404 0.00385 0.01211 0.01843 0.235 0.00796
117 0.00214 0.00207 0.00642 0.01458 0.148 0.00606
118 0.00244 0.00261 0.00731 0.01725 0.175 0.00757
119 0.00157 0.00194 0.00472 0.01279 0.129 0.00617
120 0.00127 0.00128 0.00381 0.01299 0.124 0.00679
121 0.00241 0.00314 0.00723 0.02008 0.221 0.00849
122 0.00209 0.00221 0.00628 0.01169 0.117 0.00534
123 0.00406 0.00398 0.01218 0.04479 0.441 0.02587
124 0.00506 0.00449 0.01517 0.02503 0.231 0.01372
125 0.00403 0.00395 0.01209 0.02343 0.224 0.01289
126 0.00414 0.00422 0.01242 0.02362 0.233 0.01235
127 0.00294 0.00327 0.00883 0.02791 0.246 0.01484
128 0.00368 0.00351 0.01104 0.02857 0.257 0.01547
129 0.00214 0.00192 0.00641 0.01033 0.098 0.00538
130 0.00116 0.00135 0.00349 0.01022 0.090 0.00476
131 0.00269 0.00238 0.00808 0.01412 0.125 0.00703
132 0.00224 0.00205 0.00671 0.01516 0.138 0.00721
133 0.00169 0.00170 0.00508 0.01201 0.106 0.00633
134 0.00168 0.00171 0.00504 0.01043 0.099 0.00490
135 0.00291 0.00319 0.00873 0.04932 0.441 0.02683
136 0.00244 0.00315 0.00731 0.04128 0.379 0.02229
137 0.00219 0.00283 0.00658 0.04879 0.431 0.02385
138 0.00257 0.00312 0.00772 0.05279 0.476 0.02896
139 0.00238 0.00290 0.00715 0.05643 0.517 0.03070
140 0.00181 0.00232 0.00542 0.03026 0.267 0.01514
141 0.00232 0.00269 0.00696 0.03273 0.281 0.01713
142 0.00428 0.00428 0.01285 0.06725 0.571 0.04016
143 0.00182 0.00215 0.00546 0.03527 0.297 0.02055
144 0.00189 0.00211 0.00568 0.01997 0.180 0.01117
145 0.00100 0.00133 0.00301 0.02662 0.228 0.01475
146 0.00169 0.00188 0.00506 0.02536 0.225 0.01379
147 0.00863 0.00946 0.02589 0.08143 0.821 0.03804
148 0.00849 0.00819 0.02546 0.06050 0.618 0.02865
149 0.00996 0.01027 0.02987 0.07118 0.722 0.03474
150 0.00919 0.00963 0.02756 0.07170 0.833 0.03515
151 0.01075 0.01154 0.03225 0.05830 0.784 0.02699
152 0.01800 0.01958 0.05401 0.11908 1.302 0.05647
153 0.01568 0.01699 0.04705 0.08684 1.018 0.04284
154 0.00388 0.00332 0.01164 0.02534 0.241 0.01340
155 0.00393 0.00300 0.01179 0.02682 0.236 0.01484
156 0.00356 0.00300 0.01067 0.03087 0.276 0.01659
157 0.00415 0.00339 0.01246 0.02293 0.223 0.01205
158 0.01117 0.00718 0.03351 0.04912 0.438 0.02610
159 0.00593 0.00454 0.01778 0.02852 0.266 0.01500
160 0.00321 0.00318 0.00962 0.03235 0.339 0.01360
161 0.00299 0.00316 0.00896 0.04009 0.406 0.01579
162 0.00352 0.00329 0.01057 0.03273 0.325 0.01644
163 0.00366 0.00340 0.01097 0.03658 0.369 0.01864
164 0.00291 0.00284 0.00873 0.01756 0.155 0.00967
165 0.00493 0.00461 0.01480 0.02814 0.272 0.01579
166 0.00154 0.00153 0.00462 0.02448 0.217 0.01410
167 0.00173 0.00159 0.00519 0.01242 0.116 0.00696
168 0.00205 0.00186 0.00616 0.02030 0.197 0.01186
169 0.00490 0.00448 0.01470 0.02177 0.189 0.01279
170 0.00316 0.00283 0.00949 0.02018 0.212 0.01176
171 0.00279 0.00237 0.00837 0.01897 0.181 0.01084
172 0.00166 0.00190 0.00499 0.01358 0.129 0.00664
173 0.00170 0.00200 0.00510 0.01484 0.133 0.00754
174 0.00171 0.00203 0.00514 0.01472 0.133 0.00748
175 0.00176 0.00218 0.00528 0.01657 0.145 0.00881
176 0.00160 0.00199 0.00480 0.01503 0.137 0.00812
177 0.00169 0.00213 0.00507 0.01725 0.155 0.00874
178 0.00135 0.00162 0.00406 0.01469 0.132 0.00728
179 0.00152 0.00186 0.00456 0.01574 0.142 0.00839
180 0.00204 0.00231 0.00612 0.01450 0.131 0.00725
181 0.00206 0.00233 0.00619 0.02551 0.237 0.01321
182 0.00202 0.00235 0.00605 0.01831 0.163 0.00950
183 0.00174 0.00198 0.00521 0.02145 0.198 0.01155
184 0.00186 0.00270 0.00558 0.01909 0.171 0.00864
185 0.00260 0.00346 0.00780 0.01795 0.163 0.00810
186 0.00134 0.00192 0.00403 0.01564 0.136 0.00667
187 0.00254 0.00263 0.00762 0.01660 0.154 0.00820
188 0.00115 0.00148 0.00345 0.01300 0.117 0.00631
189 0.00146 0.00184 0.00439 0.01185 0.106 0.00557
190 0.00412 0.00396 0.01235 0.02574 0.255 0.01454
191 0.00263 0.00259 0.00790 0.04087 0.405 0.02336
192 0.00331 0.00292 0.00994 0.02751 0.263 0.01604
193 0.00624 0.00564 0.01873 0.02308 0.256 0.01268
194 0.00370 0.00390 0.01109 0.02296 0.241 0.01265
195 0.00295 0.00317 0.00885 0.01884 0.190 0.01026
Shimmer:APQ5 MDVP:APQ Shimmer:DDA NHR HNR status RPDE DFA
1 0.03130 0.02971 0.06545 0.02211 21.033 1 0.414783 0.815285
2 0.04518 0.04368 0.09403 0.01929 19.085 1 0.458359 0.819521
3 0.03858 0.03590 0.08270 0.01309 20.651 1 0.429895 0.825288
4 0.04005 0.03772 0.08771 0.01353 20.644 1 0.434969 0.819235
5 0.04825 0.04465 0.10470 0.01767 19.649 1 0.417356 0.823484
6 0.03526 0.03243 0.06985 0.01222 21.378 1 0.415564 0.825069
7 0.00937 0.01351 0.02337 0.00607 24.886 1 0.596040 0.764112
8 0.00946 0.01256 0.02487 0.00344 26.892 1 0.637420 0.763262
9 0.01277 0.01717 0.03218 0.01070 21.812 1 0.615551 0.773587
10 0.01725 0.02444 0.04324 0.01022 21.862 1 0.547037 0.798463
11 0.01342 0.01892 0.03237 0.01166 21.118 1 0.611137 0.776156
12 0.01641 0.02214 0.04272 0.01141 21.414 1 0.583390 0.792520
13 0.00717 0.01140 0.01968 0.00581 25.703 1 0.460600 0.646846
14 0.00932 0.01797 0.02184 0.01041 24.889 1 0.430166 0.665833
15 0.00972 0.01246 0.03191 0.00609 24.922 1 0.474791 0.654027
16 0.00888 0.01359 0.02316 0.00839 25.175 1 0.565924 0.658245
17 0.01200 0.02074 0.02908 0.01859 22.333 1 0.567380 0.644692
18 0.01893 0.03430 0.04322 0.02919 20.376 1 0.631099 0.605417
19 0.03572 0.05767 0.07413 0.03160 17.280 1 0.665318 0.719467
20 0.02374 0.04310 0.05164 0.03365 17.153 1 0.649554 0.686080
21 0.02383 0.04055 0.05000 0.03871 17.536 1 0.660125 0.704087
22 0.02591 0.04525 0.06062 0.01849 19.493 1 0.629017 0.698951
23 0.02540 0.04246 0.06685 0.01280 22.468 1 0.619060 0.679834
24 0.02470 0.03772 0.06562 0.01840 20.422 1 0.537264 0.686894
25 0.00948 0.01497 0.02214 0.01778 23.831 1 0.397937 0.732479
26 0.02245 0.03780 0.05197 0.02887 22.066 1 0.522746 0.737948
27 0.01169 0.01872 0.02666 0.01095 25.908 1 0.418622 0.720916
28 0.01144 0.01826 0.02650 0.01328 25.119 1 0.358773 0.726652
29 0.01012 0.01661 0.02307 0.00677 25.970 1 0.470478 0.676258
30 0.01057 0.01799 0.02380 0.01170 25.678 1 0.427785 0.723797
31 0.00680 0.00802 0.01689 0.00339 26.775 0 0.422229 0.741367
32 0.00641 0.00762 0.01513 0.00167 30.940 0 0.432439 0.742055
33 0.00825 0.00951 0.01919 0.00119 30.775 0 0.465946 0.738703
34 0.00606 0.00719 0.01407 0.00072 32.684 0 0.368535 0.742133
35 0.00610 0.00726 0.01403 0.00065 33.047 0 0.340068 0.741899
36 0.00760 0.00957 0.01758 0.00135 31.732 0 0.344252 0.742737
37 0.01347 0.01612 0.03463 0.00586 23.216 1 0.360148 0.778834
38 0.01160 0.01491 0.02814 0.00340 24.951 1 0.341435 0.783626
39 0.00885 0.01190 0.02177 0.00231 26.738 1 0.403884 0.766209
40 0.01003 0.01366 0.02488 0.00265 26.310 1 0.396793 0.758324
41 0.00941 0.01233 0.02321 0.00231 26.822 1 0.326480 0.765623
42 0.00901 0.01234 0.02226 0.00257 26.453 1 0.306443 0.759203
43 0.01024 0.01133 0.03104 0.00740 22.736 0 0.305062 0.654172
44 0.01038 0.01251 0.03017 0.00675 23.145 0 0.457702 0.634267
45 0.00898 0.01033 0.02330 0.00454 25.368 0 0.438296 0.635285
46 0.00879 0.01014 0.02542 0.00476 25.032 0 0.431285 0.638928
47 0.00977 0.01149 0.02719 0.00476 24.602 0 0.467489 0.631653
48 0.00730 0.00860 0.01841 0.00432 26.805 0 0.610367 0.635204
49 0.00776 0.01433 0.02566 0.00839 23.162 0 0.579597 0.733659
50 0.00802 0.01400 0.02789 0.00462 24.971 0 0.538688 0.754073
51 0.01024 0.01685 0.03724 0.00479 25.135 0 0.553134 0.775933
52 0.00959 0.01614 0.03429 0.00474 25.030 0 0.507504 0.760361
53 0.01072 0.01677 0.03969 0.00481 24.692 0 0.459766 0.766204
54 0.01219 0.01947 0.04188 0.00484 25.429 0 0.420383 0.785714
55 0.01609 0.02067 0.04450 0.01036 21.028 1 0.536009 0.819032
56 0.01992 0.02454 0.05368 0.01180 20.767 1 0.558586 0.811843
57 0.02302 0.02802 0.06097 0.00969 21.422 1 0.541781 0.821364
58 0.01459 0.01948 0.03568 0.00681 22.817 1 0.530529 0.817756
59 0.01625 0.02137 0.04183 0.00786 22.603 1 0.540049 0.813432
60 0.01974 0.02519 0.05414 0.01143 21.660 1 0.547975 0.817396
61 0.01258 0.01382 0.02925 0.00871 25.554 0 0.341788 0.678874
62 0.01296 0.01340 0.03039 0.00301 26.138 0 0.447979 0.686264
63 0.01108 0.01200 0.02602 0.00340 25.856 0 0.364867 0.694399
64 0.01075 0.01179 0.02647 0.00351 25.964 0 0.256570 0.683296
65 0.00957 0.01016 0.02308 0.00300 26.415 0 0.276850 0.673636
66 0.01160 0.01234 0.02827 0.00420 24.547 0 0.305429 0.681811
67 0.01810 0.02428 0.05490 0.02183 19.560 1 0.460139 0.720908
68 0.01759 0.02603 0.04914 0.02659 19.979 1 0.498133 0.729067
69 0.02422 0.03392 0.09455 0.04882 20.338 1 0.513237 0.731444
70 0.02494 0.03635 0.10070 0.02431 21.718 1 0.487407 0.727313
71 0.01906 0.02949 0.05605 0.02599 20.264 1 0.489345 0.730387
72 0.02466 0.03736 0.08247 0.03361 18.570 1 0.543299 0.733232
73 0.00925 0.01345 0.02921 0.00442 25.742 1 0.495954 0.762959
74 0.01375 0.01956 0.04120 0.00623 24.178 1 0.509127 0.789532
75 0.01325 0.01831 0.04295 0.00479 25.438 1 0.437031 0.815908
76 0.01219 0.01715 0.03851 0.00472 25.197 1 0.463514 0.807217
77 0.02231 0.02704 0.07238 0.00905 23.370 1 0.489538 0.789977
78 0.01199 0.01636 0.03852 0.00420 25.820 1 0.429484 0.816340
79 0.01886 0.02455 0.05408 0.01062 21.875 1 0.644954 0.779612
80 0.01783 0.02139 0.05320 0.02220 19.200 1 0.594387 0.790117
81 0.02451 0.02876 0.06799 0.01823 19.055 1 0.544805 0.770466
82 0.01841 0.02190 0.05377 0.01825 19.659 1 0.576084 0.778747
83 0.01421 0.01751 0.04114 0.01237 20.536 1 0.554610 0.787896
84 0.01343 0.01552 0.03831 0.00882 22.244 1 0.576644 0.772416
85 0.03022 0.03510 0.08037 0.05470 13.893 1 0.556494 0.729586
86 0.02493 0.02877 0.06321 0.02782 16.176 1 0.583574 0.727747
87 0.02415 0.02784 0.06219 0.03151 15.924 1 0.598714 0.712199
88 0.04159 0.04683 0.11012 0.04824 13.922 1 0.602874 0.740837
89 0.04254 0.04802 0.11363 0.04214 14.739 1 0.599371 0.743937
90 0.02768 0.03455 0.06892 0.07223 11.866 1 0.590951 0.745526
91 0.04282 0.05114 0.10949 0.08725 11.744 1 0.653410 0.733165
92 0.04962 0.05690 0.13262 0.01658 19.664 1 0.501037 0.714360
93 0.02521 0.03051 0.07150 0.01914 18.780 1 0.454444 0.734504
94 0.03794 0.04398 0.10024 0.01211 20.969 1 0.447456 0.697790
95 0.02321 0.02764 0.06185 0.00850 22.219 1 0.502380 0.712170
96 0.01909 0.02571 0.05439 0.01018 21.693 1 0.447285 0.705658
97 0.02024 0.02809 0.05417 0.00852 22.663 1 0.366329 0.693429
98 0.02174 0.03088 0.06406 0.08151 15.338 1 0.629574 0.714485
99 0.02630 0.03908 0.07625 0.10323 15.433 1 0.571010 0.690892
100 0.03963 0.05783 0.10833 0.16744 12.435 1 0.638545 0.674953
101 0.04791 0.06196 0.16074 0.31482 8.867 1 0.671299 0.656846
102 0.03672 0.05174 0.09669 0.11843 15.060 1 0.639808 0.643327
103 0.05005 0.06023 0.16654 0.25930 10.489 1 0.596362 0.641418
104 0.00659 0.01009 0.01567 0.00495 26.759 1 0.296888 0.722356
105 0.00582 0.00871 0.01406 0.00243 28.409 1 0.263654 0.691483
106 0.00818 0.01059 0.01979 0.00578 27.421 1 0.365488 0.719974
107 0.00632 0.00928 0.01567 0.00233 29.746 1 0.334171 0.677930
108 0.00788 0.01267 0.01898 0.00659 26.833 1 0.393563 0.700246
109 0.00576 0.00993 0.01364 0.00238 29.928 1 0.311369 0.676066
110 0.01815 0.02084 0.05312 0.00947 21.934 1 0.497554 0.740539
111 0.01439 0.01852 0.03576 0.00704 23.239 1 0.436084 0.727863
112 0.01058 0.01307 0.02855 0.00830 22.407 1 0.338097 0.712466
113 0.01483 0.01767 0.03831 0.01316 21.305 1 0.498877 0.722085
114 0.01017 0.01301 0.02583 0.00620 23.671 1 0.441097 0.722254
115 0.01284 0.01604 0.03320 0.01048 21.864 1 0.331508 0.715121
116 0.00832 0.01271 0.02389 0.06051 23.693 1 0.407701 0.662668
117 0.00747 0.01312 0.01818 0.01554 26.356 1 0.450798 0.653823
118 0.00971 0.01652 0.02270 0.01802 25.690 1 0.486738 0.676023
119 0.00744 0.01151 0.01851 0.00856 25.020 1 0.470422 0.655239
120 0.00631 0.01075 0.02038 0.00681 24.581 1 0.462516 0.582710
121 0.01117 0.01734 0.02548 0.02350 24.743 1 0.487756 0.684130
122 0.00630 0.01104 0.01603 0.01161 27.166 1 0.400088 0.656182
123 0.02567 0.03220 0.07761 0.01968 18.305 1 0.538016 0.741480
124 0.01580 0.01931 0.04115 0.01813 18.784 1 0.589956 0.732903
125 0.01420 0.01720 0.03867 0.02020 19.196 1 0.618663 0.728421
126 0.01495 0.01944 0.03706 0.01874 18.857 1 0.637518 0.735546
127 0.01805 0.02259 0.04451 0.01794 18.178 1 0.623209 0.738245
128 0.01859 0.02301 0.04641 0.01796 18.330 1 0.585169 0.736964
129 0.00570 0.00811 0.01614 0.01724 26.842 1 0.457541 0.699787
130 0.00588 0.00903 0.01428 0.00487 26.369 1 0.491345 0.718839
131 0.00820 0.01194 0.02110 0.01610 23.949 1 0.467160 0.724045
132 0.00815 0.01310 0.02164 0.01015 26.017 1 0.468621 0.735136
133 0.00701 0.00915 0.01898 0.00903 23.389 1 0.470972 0.721308
134 0.00621 0.00903 0.01471 0.00504 25.619 1 0.482296 0.723096
135 0.03112 0.03651 0.08050 0.03031 17.060 1 0.637814 0.744064
136 0.02592 0.03316 0.06688 0.02529 17.707 1 0.653427 0.706687
137 0.02973 0.04370 0.07154 0.02278 19.013 1 0.647900 0.708144
138 0.03347 0.04134 0.08689 0.03690 16.747 1 0.625362 0.708617
139 0.03530 0.04451 0.09211 0.02629 17.366 1 0.640945 0.701404
140 0.01812 0.02770 0.04543 0.01827 18.801 1 0.624811 0.696049
141 0.01964 0.02824 0.05139 0.02485 18.540 1 0.677131 0.685057
142 0.04003 0.04464 0.12047 0.04238 15.648 1 0.606344 0.665945
143 0.02076 0.02530 0.06165 0.01728 18.702 1 0.606273 0.661735
144 0.01177 0.01506 0.03350 0.02010 18.687 1 0.536102 0.632631
145 0.01558 0.02006 0.04426 0.01049 20.680 1 0.497480 0.630409
146 0.01478 0.01909 0.04137 0.01493 20.366 1 0.566849 0.574282
147 0.05426 0.08808 0.11411 0.07530 12.359 1 0.561610 0.793509
148 0.04101 0.06359 0.08595 0.06057 14.367 1 0.478024 0.768974
149 0.04580 0.06824 0.10422 0.08069 12.298 1 0.552870 0.764036
150 0.04265 0.06460 0.10546 0.07889 14.989 1 0.427627 0.775708
151 0.03714 0.06259 0.08096 0.10952 12.529 1 0.507826 0.762726
152 0.07940 0.13778 0.16942 0.21713 8.441 1 0.625866 0.768320
153 0.05556 0.08318 0.12851 0.16265 9.449 1 0.584164 0.754449
154 0.01399 0.02056 0.04019 0.04179 21.520 1 0.566867 0.670475
155 0.01405 0.02018 0.04451 0.04611 21.824 1 0.651680 0.659333
156 0.01804 0.02402 0.04977 0.02631 22.431 1 0.628300 0.652025
157 0.01289 0.01771 0.03615 0.03191 22.953 1 0.611679 0.623731
158 0.02161 0.02916 0.07830 0.10748 19.075 1 0.630547 0.646786
159 0.01581 0.02157 0.04499 0.03828 21.534 1 0.635015 0.627337
160 0.01650 0.03105 0.04079 0.02663 19.651 1 0.654945 0.675865
161 0.01994 0.04114 0.04736 0.02073 20.437 1 0.653139 0.694571
162 0.01722 0.02931 0.04933 0.02810 19.388 1 0.577802 0.684373
163 0.01940 0.03091 0.05592 0.02707 18.954 1 0.685151 0.719576
164 0.01033 0.01363 0.02902 0.01435 21.219 1 0.557045 0.673086
165 0.01553 0.02073 0.04736 0.03882 18.447 1 0.671378 0.674562
166 0.01426 0.01621 0.04231 0.00620 24.078 0 0.469928 0.628232
167 0.00747 0.00882 0.02089 0.00533 24.679 0 0.384868 0.626710
168 0.01230 0.01367 0.03557 0.00910 21.083 0 0.440988 0.628058
169 0.01272 0.01439 0.03836 0.01337 19.269 0 0.372222 0.725216
170 0.01191 0.01344 0.03529 0.00965 21.020 0 0.371837 0.646167
171 0.01121 0.01255 0.03253 0.01049 21.528 0 0.522812 0.646818
172 0.00786 0.01140 0.01992 0.00435 26.436 0 0.413295 0.756700
173 0.00950 0.01285 0.02261 0.00430 26.550 0 0.369090 0.776158
174 0.00905 0.01148 0.02245 0.00478 26.547 0 0.380253 0.766700
175 0.01062 0.01318 0.02643 0.00590 25.445 0 0.387482 0.756482
176 0.00933 0.01133 0.02436 0.00401 26.005 0 0.405991 0.761255
177 0.01021 0.01331 0.02623 0.00415 26.143 0 0.361232 0.763242
178 0.00886 0.01230 0.02184 0.00570 24.151 1 0.396610 0.745957
179 0.00956 0.01309 0.02518 0.00488 24.412 1 0.402591 0.762508
180 0.00876 0.01263 0.02175 0.00540 23.683 1 0.398499 0.778349
181 0.01574 0.02148 0.03964 0.00611 23.133 1 0.352396 0.759320
182 0.01103 0.01559 0.02849 0.00639 22.866 1 0.408598 0.768845
183 0.01341 0.01666 0.03464 0.00595 23.008 1 0.329577 0.757180
184 0.01223 0.01949 0.02592 0.00955 23.079 0 0.603515 0.669565
185 0.01144 0.01756 0.02429 0.01179 22.085 0 0.663842 0.656516
186 0.00990 0.01691 0.02001 0.00737 24.199 0 0.598515 0.654331
187 0.00972 0.01491 0.02460 0.01397 23.958 0 0.566424 0.667654
188 0.00789 0.01144 0.01892 0.00680 25.023 0 0.528485 0.663884
189 0.00721 0.01095 0.01672 0.00703 24.775 0 0.555303 0.659132
190 0.01582 0.01758 0.04363 0.04441 19.368 0 0.508479 0.683761
191 0.02498 0.02745 0.07008 0.02764 19.517 0 0.448439 0.657899
192 0.01657 0.01879 0.04812 0.01810 19.147 0 0.431674 0.683244
193 0.01365 0.01667 0.03804 0.10715 17.883 0 0.407567 0.655683
194 0.01321 0.01588 0.03794 0.07223 19.020 0 0.451221 0.643956
195 0.01161 0.01373 0.03078 0.04398 21.209 0 0.462803 0.664357
spread1 spread2 D2
1 -4.813031 0.266482 2.301442
2 -4.075192 0.335590 2.486855
3 -4.443179 0.311173 2.342259
4 -4.117501 0.334147 2.405554
5 -3.747787 0.234513 2.332180
6 -4.242867 0.299111 2.187560
7 -5.634322 0.257682 1.854785
8 -6.167603 0.183721 2.064693
9 -5.498678 0.327769 2.322511
10 -5.011879 0.325996 2.432792
11 -5.249770 0.391002 2.407313
12 -4.960234 0.363566 2.642476
13 -6.547148 0.152813 2.041277
14 -5.660217 0.254989 2.519422
15 -6.105098 0.203653 2.125618
16 -5.340115 0.210185 2.205546
17 -5.440040 0.239764 2.264501
18 -2.931070 0.434326 3.007463
19 -3.949079 0.357870 3.109010
20 -4.554466 0.340176 2.856676
21 -4.095442 0.262564 2.739710
22 -5.186960 0.237622 2.557536
23 -4.330956 0.262384 2.916777
24 -5.248776 0.210279 2.547508
25 -5.557447 0.220890 2.692176
26 -5.571843 0.236853 2.846369
27 -6.183590 0.226278 2.589702
28 -6.271690 0.196102 2.314209
29 -7.120925 0.279789 2.241742
30 -6.635729 0.209866 1.957961
31 -7.348300 0.177551 1.743867
32 -7.682587 0.173319 2.103106
33 -7.067931 0.175181 1.512275
34 -7.695734 0.178540 1.544609
35 -7.964984 0.163519 1.423287
36 -7.777685 0.170183 2.447064
37 -6.149653 0.218037 2.477082
38 -6.006414 0.196371 2.536527
39 -6.452058 0.212294 2.269398
40 -6.006647 0.266892 2.382544
41 -6.647379 0.201095 2.374073
42 -7.044105 0.063412 2.361532
43 -7.310550 0.098648 2.416838
44 -6.793547 0.158266 2.256699
45 -7.057869 0.091608 2.330716
46 -6.995820 0.102083 2.365800
47 -7.156076 0.127642 2.392122
48 -7.319510 0.200873 2.028612
49 -6.439398 0.266392 2.079922
50 -6.482096 0.264967 2.054419
51 -6.650471 0.254498 1.840198
52 -6.689151 0.291954 2.431854
53 -7.072419 0.220434 1.972297
54 -6.836811 0.269866 2.223719
55 -4.649573 0.205558 1.986899
56 -4.333543 0.221727 2.014606
57 -4.438453 0.238298 1.922940
58 -4.608260 0.290024 2.021591
59 -4.476755 0.262633 1.827012
60 -4.609161 0.221711 1.831691
61 -7.040508 0.066994 2.460791
62 -7.293801 0.086372 2.321560
63 -6.966321 0.095882 2.278687
64 -7.245620 0.018689 2.498224
65 -7.496264 0.056844 2.003032
66 -7.314237 0.006274 2.118596
67 -5.409423 0.226850 2.359973
68 -5.324574 0.205660 2.291558
69 -5.869750 0.151814 2.118496
70 -6.261141 0.120956 2.137075
71 -5.720868 0.158830 2.277927
72 -5.207985 0.224852 2.642276
73 -5.791820 0.329066 2.205024
74 -5.389129 0.306636 1.928708
75 -5.313360 0.201861 2.225815
76 -5.477592 0.315074 1.862092
77 -5.775966 0.341169 2.007923
78 -5.391029 0.250572 1.777901
79 -5.115212 0.249494 2.017753
80 -4.913885 0.265699 2.398422
81 -4.441519 0.155097 2.645959
82 -5.132032 0.210458 2.232576
83 -5.022288 0.146948 2.428306
84 -6.025367 0.078202 2.053601
85 -5.288912 0.343073 3.099301
86 -5.657899 0.315903 3.098256
87 -6.366916 0.335753 2.654271
88 -5.515071 0.299549 3.136550
89 -5.783272 0.299793 3.007096
90 -4.379411 0.375531 3.671155
91 -4.508984 0.389232 3.317586
92 -6.411497 0.207156 2.344876
93 -5.952058 0.087840 2.344336
94 -6.152551 0.173520 2.080121
95 -6.251425 0.188056 2.143851
96 -6.247076 0.180528 2.344348
97 -6.417440 0.194627 2.473239
98 -4.020042 0.265315 2.671825
99 -5.159169 0.202146 2.441612
100 -3.760348 0.242861 2.634633
101 -3.700544 0.260481 2.991063
102 -4.202730 0.310163 2.638279
103 -3.269487 0.270641 2.690917
104 -6.878393 0.089267 2.004055
105 -7.111576 0.144780 2.065477
106 -6.997403 0.210279 1.994387
107 -6.981201 0.184550 2.129924
108 -6.600023 0.249172 2.499148
109 -6.739151 0.160686 2.296873
110 -5.845099 0.278679 2.608749
111 -5.258320 0.256454 2.550961
112 -6.471427 0.184378 2.502336
113 -4.876336 0.212054 2.376749
114 -5.963040 0.250283 2.489191
115 -6.729713 0.181701 2.938114
116 -4.673241 0.261549 2.702355
117 -6.051233 0.273280 2.640798
118 -4.597834 0.372114 2.975889
119 -4.913137 0.393056 2.816781
120 -5.517173 0.389295 2.925862
121 -6.186128 0.279933 2.686240
122 -4.711007 0.281618 2.655744
123 -5.418787 0.160267 2.090438
124 -5.445140 0.142466 2.174306
125 -5.944191 0.143359 1.929715
126 -5.594275 0.127950 1.765957
127 -5.540351 0.087165 1.821297
128 -5.825257 0.115697 1.996146
129 -6.890021 0.152941 2.328513
130 -5.892061 0.195976 2.108873
131 -6.135296 0.203630 2.539724
132 -6.112667 0.217013 2.527742
133 -5.436135 0.254909 2.516320
134 -6.448134 0.178713 2.034827
135 -5.301321 0.320385 2.375138
136 -5.333619 0.322044 2.631793
137 -4.378916 0.300067 2.445502
138 -4.654894 0.304107 2.672362
139 -5.634576 0.306014 2.419253
140 -5.866357 0.233070 2.445646
141 -4.796845 0.397749 2.963799
142 -5.410336 0.288917 2.665133
143 -5.585259 0.310746 2.465528
144 -5.898673 0.213353 2.470746
145 -6.132663 0.220617 2.576563
146 -5.456811 0.345238 2.840556
147 -3.297668 0.414758 3.413649
148 -4.276605 0.355736 3.142364
149 -3.377325 0.335357 3.274865
150 -4.892495 0.262281 2.910213
151 -4.484303 0.340256 2.958815
152 -2.434031 0.450493 3.079221
153 -2.839756 0.356224 3.184027
154 -4.865194 0.246404 2.013530
155 -4.239028 0.175691 2.451130
156 -3.583722 0.207914 2.439597
157 -5.435100 0.230532 2.699645
158 -3.444478 0.303214 2.964568
159 -5.070096 0.280091 2.892300
160 -5.498456 0.234196 2.103014
161 -5.185987 0.259229 2.151121
162 -5.283009 0.226528 2.442906
163 -5.529833 0.242750 2.408689
164 -5.617124 0.184896 1.871871
165 -2.929379 0.396746 2.560422
166 -6.816086 0.172270 2.235197
167 -7.018057 0.176316 1.852402
168 -7.517934 0.160414 1.881767
169 -5.736781 0.164529 2.882450
170 -7.169701 0.073298 2.266432
171 -7.304500 0.171088 2.095237
172 -6.323531 0.218885 2.193412
173 -6.085567 0.192375 1.889002
174 -5.943501 0.192150 1.852542
175 -6.012559 0.229298 1.872946
176 -5.966779 0.197938 1.974857
177 -6.016891 0.109256 2.004719
178 -6.486822 0.197919 2.449763
179 -6.311987 0.182459 2.251553
180 -5.711205 0.240875 2.845109
181 -6.261446 0.183218 2.264226
182 -5.704053 0.216204 2.679185
183 -6.277170 0.109397 2.209021
184 -5.619070 0.191576 2.027228
185 -5.198864 0.206768 2.120412
186 -5.592584 0.133917 2.058658
187 -6.431119 0.153310 2.161936
188 -6.359018 0.116636 2.152083
189 -6.710219 0.149694 1.913990
190 -6.934474 0.159890 2.316346
191 -6.538586 0.121952 2.657476
192 -6.195325 0.129303 2.784312
193 -6.787197 0.158453 2.679772
194 -6.744577 0.207454 2.138608
195 -5.724056 0.190667 2.555477
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `MDVP:Fhi(Hz)` `MDVP:Flo(Hz)` `MDVP:Jitter(%)`
2.731e+02 3.208e-02 2.536e-01 1.079e+04
`MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ` `Jitter:DDP`
-1.909e+06 6.347e+05 -1.415e+03 -2.087e+05
`MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3` `Shimmer:APQ5`
2.969e+01 -7.588e+01 8.307e+04 2.153e+03
`MDVP:APQ` `Shimmer:DDA` NHR HNR
-1.354e+03 -2.743e+04 -2.433e+02 -4.896e-01
status RPDE DFA spread1
-5.457e+00 -3.635e+01 -2.260e+02 -3.095e+00
spread2 D2
2.469e+01 8.161e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-52.862 -11.013 -0.665 10.531 45.809
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.731e+02 4.887e+01 5.590 8.72e-08 ***
`MDVP:Fhi(Hz)` 3.208e-02 1.644e-02 1.952 0.05257 .
`MDVP:Flo(Hz)` 2.536e-01 3.695e-02 6.863 1.15e-10 ***
`MDVP:Jitter(%)` 1.079e+04 3.410e+03 3.164 0.00184 **
`MDVP:Jitter(Abs)` -1.909e+06 1.761e+05 -10.839 < 2e-16 ***
`MDVP:RAP` 6.347e+05 4.796e+05 1.323 0.18745
`MDVP:PPQ` -1.415e+03 4.215e+03 -0.336 0.73750
`Jitter:DDP` -2.087e+05 1.600e+05 -1.305 0.19364
`MDVP:Shimmer` 2.969e+01 1.775e+03 0.017 0.98668
`MDVP:Shimmer(dB)` -7.588e+01 5.939e+01 -1.278 0.20309
`Shimmer:APQ3` 8.307e+04 4.628e+05 0.180 0.85775
`Shimmer:APQ5` 2.153e+03 1.030e+03 2.090 0.03810 *
`MDVP:APQ` -1.354e+03 5.406e+02 -2.505 0.01319 *
`Shimmer:DDA` -2.743e+04 1.542e+05 -0.178 0.85904
NHR -2.433e+02 1.012e+02 -2.403 0.01733 *
HNR -4.896e-01 7.383e-01 -0.663 0.50812
status -5.457e+00 3.913e+00 -1.395 0.16492
RPDE -3.635e+01 2.292e+01 -1.586 0.11459
DFA -2.260e+02 3.347e+01 -6.751 2.13e-10 ***
spread1 -3.095e+00 2.890e+00 -1.071 0.28572
spread2 2.469e+01 2.515e+01 0.982 0.32766
D2 8.161e+00 5.859e+00 1.393 0.16547
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 16.9 on 173 degrees of freedom
Multiple R-squared: 0.8513, Adjusted R-squared: 0.8333
F-statistic: 47.17 on 21 and 173 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,] 1.826280e-01 3.652560e-01 0.8173720
[2,] 8.711639e-02 1.742328e-01 0.9128836
[3,] 3.895557e-02 7.791114e-02 0.9610444
[4,] 4.024470e-02 8.048939e-02 0.9597553
[5,] 1.751879e-02 3.503758e-02 0.9824812
[6,] 8.486019e-03 1.697204e-02 0.9915140
[7,] 3.351956e-03 6.703912e-03 0.9966480
[8,] 1.501731e-03 3.003463e-03 0.9984983
[9,] 1.019137e-03 2.038274e-03 0.9989809
[10,] 6.937780e-04 1.387556e-03 0.9993062
[11,] 2.932588e-04 5.865175e-04 0.9997067
[12,] 1.173654e-04 2.347308e-04 0.9998826
[13,] 6.549233e-05 1.309847e-04 0.9999345
[14,] 2.438001e-05 4.876002e-05 0.9999756
[15,] 1.035496e-04 2.070993e-04 0.9998965
[16,] 1.491025e-04 2.982050e-04 0.9998509
[17,] 1.053419e-04 2.106838e-04 0.9998947
[18,] 4.924561e-05 9.849123e-05 0.9999508
[19,] 6.092988e-05 1.218598e-04 0.9999391
[20,] 4.777886e-05 9.555773e-05 0.9999522
[21,] 8.520432e-05 1.704086e-04 0.9999148
[22,] 9.500188e-05 1.900038e-04 0.9999050
[23,] 9.864357e-05 1.972871e-04 0.9999014
[24,] 6.653523e-03 1.330705e-02 0.9933465
[25,] 4.549915e-03 9.099830e-03 0.9954501
[26,] 3.462511e-03 6.925021e-03 0.9965375
[27,] 2.108898e-03 4.217797e-03 0.9978911
[28,] 1.567931e-03 3.135862e-03 0.9984321
[29,] 1.016291e-03 2.032582e-03 0.9989837
[30,] 6.002934e-04 1.200587e-03 0.9993997
[31,] 3.459197e-03 6.918394e-03 0.9965408
[32,] 6.799305e-03 1.359861e-02 0.9932007
[33,] 5.940496e-03 1.188099e-02 0.9940595
[34,] 8.331230e-03 1.666246e-02 0.9916688
[35,] 1.418706e-02 2.837413e-02 0.9858129
[36,] 2.996023e-02 5.992047e-02 0.9700398
[37,] 2.429034e-02 4.858069e-02 0.9757097
[38,] 4.012102e-02 8.024203e-02 0.9598790
[39,] 4.088711e-02 8.177421e-02 0.9591129
[40,] 4.296187e-02 8.592375e-02 0.9570381
[41,] 4.506423e-02 9.012847e-02 0.9549358
[42,] 1.022712e-01 2.045424e-01 0.8977288
[43,] 8.595385e-02 1.719077e-01 0.9140461
[44,] 6.759592e-02 1.351918e-01 0.9324041
[45,] 5.410067e-02 1.082013e-01 0.9458993
[46,] 6.809114e-02 1.361823e-01 0.9319089
[47,] 5.411564e-02 1.082313e-01 0.9458844
[48,] 4.455113e-02 8.910225e-02 0.9554489
[49,] 4.042443e-02 8.084886e-02 0.9595756
[50,] 1.852665e-01 3.705329e-01 0.8147335
[51,] 2.427338e-01 4.854676e-01 0.7572662
[52,] 2.123280e-01 4.246559e-01 0.7876720
[53,] 2.002643e-01 4.005285e-01 0.7997357
[54,] 1.749019e-01 3.498039e-01 0.8250981
[55,] 1.749328e-01 3.498656e-01 0.8250672
[56,] 1.828381e-01 3.656763e-01 0.8171619
[57,] 2.121796e-01 4.243591e-01 0.7878204
[58,] 1.955382e-01 3.910765e-01 0.8044618
[59,] 2.231487e-01 4.462973e-01 0.7768513
[60,] 2.720714e-01 5.441429e-01 0.7279286
[61,] 3.345620e-01 6.691240e-01 0.6654380
[62,] 2.969961e-01 5.939923e-01 0.7030039
[63,] 3.021263e-01 6.042526e-01 0.6978737
[64,] 2.654732e-01 5.309463e-01 0.7345268
[65,] 3.111544e-01 6.223087e-01 0.6888456
[66,] 2.896077e-01 5.792154e-01 0.7103923
[67,] 2.545371e-01 5.090742e-01 0.7454629
[68,] 2.647196e-01 5.294391e-01 0.7352804
[69,] 2.617193e-01 5.234386e-01 0.7382807
[70,] 2.608931e-01 5.217863e-01 0.7391069
[71,] 2.247193e-01 4.494387e-01 0.7752807
[72,] 2.606996e-01 5.213992e-01 0.7393004
[73,] 2.801946e-01 5.603893e-01 0.7198054
[74,] 2.492188e-01 4.984377e-01 0.7507812
[75,] 2.174467e-01 4.348934e-01 0.7825533
[76,] 2.113721e-01 4.227442e-01 0.7886279
[77,] 2.059593e-01 4.119186e-01 0.7940407
[78,] 2.012019e-01 4.024037e-01 0.7987981
[79,] 2.576274e-01 5.152547e-01 0.7423726
[80,] 2.744493e-01 5.488986e-01 0.7255507
[81,] 2.715722e-01 5.431444e-01 0.7284278
[82,] 2.355411e-01 4.710822e-01 0.7644589
[83,] 2.119744e-01 4.239488e-01 0.7880256
[84,] 1.803484e-01 3.606968e-01 0.8196516
[85,] 1.796686e-01 3.593372e-01 0.8203314
[86,] 1.586556e-01 3.173111e-01 0.8413444
[87,] 1.410488e-01 2.820975e-01 0.8589512
[88,] 1.266473e-01 2.532946e-01 0.8733527
[89,] 1.325182e-01 2.650363e-01 0.8674818
[90,] 1.542600e-01 3.085201e-01 0.8457400
[91,] 1.287901e-01 2.575802e-01 0.8712099
[92,] 1.116882e-01 2.233764e-01 0.8883118
[93,] 9.961448e-02 1.992290e-01 0.9003855
[94,] 8.482241e-02 1.696448e-01 0.9151776
[95,] 8.373236e-02 1.674647e-01 0.9162676
[96,] 1.293958e-01 2.587915e-01 0.8706042
[97,] 1.617486e-01 3.234972e-01 0.8382514
[98,] 2.004746e-01 4.009492e-01 0.7995254
[99,] 1.769885e-01 3.539769e-01 0.8230115
[100,] 1.630743e-01 3.261486e-01 0.8369257
[101,] 1.403375e-01 2.806750e-01 0.8596625
[102,] 1.399798e-01 2.799596e-01 0.8600202
[103,] 1.522004e-01 3.044008e-01 0.8477996
[104,] 3.152494e-01 6.304987e-01 0.6847506
[105,] 3.015847e-01 6.031693e-01 0.6984153
[106,] 2.931178e-01 5.862356e-01 0.7068822
[107,] 2.744944e-01 5.489887e-01 0.7255056
[108,] 2.841665e-01 5.683329e-01 0.7158335
[109,] 2.914839e-01 5.829678e-01 0.7085161
[110,] 2.752826e-01 5.505652e-01 0.7247174
[111,] 4.337877e-01 8.675755e-01 0.5662123
[112,] 5.048569e-01 9.902862e-01 0.4951431
[113,] 4.633630e-01 9.267260e-01 0.5366370
[114,] 5.161522e-01 9.676957e-01 0.4838478
[115,] 5.521470e-01 8.957060e-01 0.4478530
[116,] 7.510591e-01 4.978817e-01 0.2489409
[117,] 7.151158e-01 5.697683e-01 0.2848842
[118,] 6.914704e-01 6.170592e-01 0.3085296
[119,] 6.973522e-01 6.052957e-01 0.3026478
[120,] 7.145913e-01 5.708173e-01 0.2854087
[121,] 7.612198e-01 4.775603e-01 0.2387802
[122,] 7.645170e-01 4.709660e-01 0.2354830
[123,] 7.519138e-01 4.961725e-01 0.2480862
[124,] 7.368290e-01 5.263421e-01 0.2631710
[125,] 7.691266e-01 4.617468e-01 0.2308734
[126,] 7.225045e-01 5.549910e-01 0.2774955
[127,] 7.540178e-01 4.919643e-01 0.2459822
[128,] 7.244500e-01 5.511000e-01 0.2755500
[129,] 7.180076e-01 5.639847e-01 0.2819924
[130,] 7.056179e-01 5.887643e-01 0.2943821
[131,] 7.299402e-01 5.401196e-01 0.2700598
[132,] 8.402021e-01 3.195959e-01 0.1597979
[133,] 8.049079e-01 3.901843e-01 0.1950921
[134,] 7.577030e-01 4.845940e-01 0.2422970
[135,] 7.302020e-01 5.395960e-01 0.2697980
[136,] 6.658555e-01 6.682890e-01 0.3341445
[137,] 5.876684e-01 8.246632e-01 0.4123316
[138,] 7.809775e-01 4.380450e-01 0.2190225
[139,] 7.100172e-01 5.799655e-01 0.2899828
[140,] 6.545472e-01 6.909056e-01 0.3454528
[141,] 6.535730e-01 6.928539e-01 0.3464270
[142,] 8.498228e-01 3.003544e-01 0.1501772
[143,] 7.624901e-01 4.750198e-01 0.2375099
[144,] 7.228798e-01 5.542405e-01 0.2771202
[145,] 7.104527e-01 5.790945e-01 0.2895473
[146,] 7.594741e-01 4.810518e-01 0.2405259
> postscript(file="/var/wessaorg/rcomp/tmp/1x5cm1386521634.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2zrh51386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3x9m71386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4na2v1386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5d8a21386521634.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 = 195
Frequency = 1
1 2 3 4 5 6
12.7687615 -4.5114159 -4.5707673 -1.4044689 -3.2491734 -2.9294619
7 8 9 10 11 12
3.3986656 -7.2058960 4.8599607 10.8726355 8.7604526 7.0660784
13 14 15 16 17 18
-29.1836515 -1.2708514 -2.7084181 -0.2794616 -4.5004017 8.7972063
19 20 21 22 23 24
30.6199516 1.6985483 14.6550240 18.6127687 29.8962235 23.3266525
25 26 27 28 29 30
16.0789304 9.6026967 21.8580665 -6.4045001 -4.8751505 14.5331422
31 32 33 34 35 36
-0.9158338 7.3541339 16.4525285 17.2801993 22.0669047 8.0324724
37 38 39 40 41 42
-4.0598163 5.6301031 16.8083339 18.4008060 17.2319201 6.4753258
43 44 45 46 47 48
-1.9235606 4.2945049 17.8214016 14.7312680 14.1427584 45.8086554
49 50 51 52 53 54
-12.7060630 -13.3276264 -11.1302293 1.1670536 -15.4158281 -0.1079679
55 56 57 58 59 60
19.5923006 22.1562503 18.4773238 15.1286808 30.6076954 34.9223023
61 62 63 64 65 66
14.3205441 30.5943145 8.6895046 -1.2611558 10.8169025 37.1920657
67 68 69 70 71 72
-0.2170814 8.4485464 9.5028594 -1.6505872 14.2154370 5.0398267
73 74 75 76 77 78
-17.4152922 -6.6954738 -8.5416369 7.2044127 -21.1797186 -2.1230075
79 80 81 82 83 84
0.7890234 16.8144353 0.7287899 -3.6269212 0.3312369 -11.9780972
85 86 87 88 89 90
-2.2751505 -13.0619793 0.2350693 -2.6681951 18.9974270 0.7373603
91 92 93 94 95 96
2.3216851 -21.4984173 -17.6458362 10.2310665 -5.3574489 -25.5649742
97 98 99 100 101 102
-19.2520917 -6.1339783 4.9498384 15.9313262 18.9723554 7.3298523
103 104 105 106 107 108
-7.0357777 14.8629761 -14.9997758 -4.3100704 -18.8065006 -5.1607171
109 110 111 112 113 114
-19.4117723 8.4926805 14.3034267 -9.8159066 -15.9376725 13.6238043
115 116 117 118 119 120
6.5203638 0.6124355 -9.7196546 -5.4092093 10.2445042 20.2838774
121 122 123 124 125 126
-8.3848291 17.7938374 -3.3248231 14.2443004 -2.4842041 7.8447609
127 128 129 130 131 132
9.1802576 15.4959726 -19.4752720 -18.7922931 -17.1944221 -24.5785537
133 134 135 136 137 138
-14.7181582 -14.8255021 -0.6649599 -31.6898310 -5.8302941 -25.0924831
139 140 141 142 143 144
-24.6022805 -25.6150686 2.1758853 4.0333080 5.9693771 24.9722282
145 146 147 148 149 150
-0.7843086 26.3019874 8.1618809 -14.4643459 -21.8179543 -16.1378030
151 152 153 154 155 156
6.4886904 -1.4821137 -27.8413139 -3.5549840 -5.1170363 -28.4965954
157 158 159 160 161 162
-25.5748679 -7.1099855 -28.7949980 5.6626398 18.2245278 -14.7904266
163 164 165 166 167 168
8.5865902 -16.5939691 6.2175268 32.5295276 -0.9069044 12.8013955
169 170 171 172 173 174
-10.8965828 -6.0231023 3.7686143 -22.1989935 -19.9273667 -14.5847619
175 176 177 178 179 180
-20.8450755 -18.7326375 -17.4900030 -5.0745130 -5.8502082 0.6352480
181 182 183 184 185 186
0.3867237 -3.9398184 -17.5925710 -13.6636600 -15.5166903 -18.2756277
187 188 189 190 191 192
-43.1735949 -52.8618501 -24.3019666 -2.5643379 -8.2634604 15.1663115
193 194 195
-8.9493191 8.2292599 32.7038786
> postscript(file="/var/wessaorg/rcomp/tmp/6ohhv1386521634.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 = 195
Frequency = 1
lag(myerror, k = 1) myerror
0 12.7687615 NA
1 -4.5114159 12.7687615
2 -4.5707673 -4.5114159
3 -1.4044689 -4.5707673
4 -3.2491734 -1.4044689
5 -2.9294619 -3.2491734
6 3.3986656 -2.9294619
7 -7.2058960 3.3986656
8 4.8599607 -7.2058960
9 10.8726355 4.8599607
10 8.7604526 10.8726355
11 7.0660784 8.7604526
12 -29.1836515 7.0660784
13 -1.2708514 -29.1836515
14 -2.7084181 -1.2708514
15 -0.2794616 -2.7084181
16 -4.5004017 -0.2794616
17 8.7972063 -4.5004017
18 30.6199516 8.7972063
19 1.6985483 30.6199516
20 14.6550240 1.6985483
21 18.6127687 14.6550240
22 29.8962235 18.6127687
23 23.3266525 29.8962235
24 16.0789304 23.3266525
25 9.6026967 16.0789304
26 21.8580665 9.6026967
27 -6.4045001 21.8580665
28 -4.8751505 -6.4045001
29 14.5331422 -4.8751505
30 -0.9158338 14.5331422
31 7.3541339 -0.9158338
32 16.4525285 7.3541339
33 17.2801993 16.4525285
34 22.0669047 17.2801993
35 8.0324724 22.0669047
36 -4.0598163 8.0324724
37 5.6301031 -4.0598163
38 16.8083339 5.6301031
39 18.4008060 16.8083339
40 17.2319201 18.4008060
41 6.4753258 17.2319201
42 -1.9235606 6.4753258
43 4.2945049 -1.9235606
44 17.8214016 4.2945049
45 14.7312680 17.8214016
46 14.1427584 14.7312680
47 45.8086554 14.1427584
48 -12.7060630 45.8086554
49 -13.3276264 -12.7060630
50 -11.1302293 -13.3276264
51 1.1670536 -11.1302293
52 -15.4158281 1.1670536
53 -0.1079679 -15.4158281
54 19.5923006 -0.1079679
55 22.1562503 19.5923006
56 18.4773238 22.1562503
57 15.1286808 18.4773238
58 30.6076954 15.1286808
59 34.9223023 30.6076954
60 14.3205441 34.9223023
61 30.5943145 14.3205441
62 8.6895046 30.5943145
63 -1.2611558 8.6895046
64 10.8169025 -1.2611558
65 37.1920657 10.8169025
66 -0.2170814 37.1920657
67 8.4485464 -0.2170814
68 9.5028594 8.4485464
69 -1.6505872 9.5028594
70 14.2154370 -1.6505872
71 5.0398267 14.2154370
72 -17.4152922 5.0398267
73 -6.6954738 -17.4152922
74 -8.5416369 -6.6954738
75 7.2044127 -8.5416369
76 -21.1797186 7.2044127
77 -2.1230075 -21.1797186
78 0.7890234 -2.1230075
79 16.8144353 0.7890234
80 0.7287899 16.8144353
81 -3.6269212 0.7287899
82 0.3312369 -3.6269212
83 -11.9780972 0.3312369
84 -2.2751505 -11.9780972
85 -13.0619793 -2.2751505
86 0.2350693 -13.0619793
87 -2.6681951 0.2350693
88 18.9974270 -2.6681951
89 0.7373603 18.9974270
90 2.3216851 0.7373603
91 -21.4984173 2.3216851
92 -17.6458362 -21.4984173
93 10.2310665 -17.6458362
94 -5.3574489 10.2310665
95 -25.5649742 -5.3574489
96 -19.2520917 -25.5649742
97 -6.1339783 -19.2520917
98 4.9498384 -6.1339783
99 15.9313262 4.9498384
100 18.9723554 15.9313262
101 7.3298523 18.9723554
102 -7.0357777 7.3298523
103 14.8629761 -7.0357777
104 -14.9997758 14.8629761
105 -4.3100704 -14.9997758
106 -18.8065006 -4.3100704
107 -5.1607171 -18.8065006
108 -19.4117723 -5.1607171
109 8.4926805 -19.4117723
110 14.3034267 8.4926805
111 -9.8159066 14.3034267
112 -15.9376725 -9.8159066
113 13.6238043 -15.9376725
114 6.5203638 13.6238043
115 0.6124355 6.5203638
116 -9.7196546 0.6124355
117 -5.4092093 -9.7196546
118 10.2445042 -5.4092093
119 20.2838774 10.2445042
120 -8.3848291 20.2838774
121 17.7938374 -8.3848291
122 -3.3248231 17.7938374
123 14.2443004 -3.3248231
124 -2.4842041 14.2443004
125 7.8447609 -2.4842041
126 9.1802576 7.8447609
127 15.4959726 9.1802576
128 -19.4752720 15.4959726
129 -18.7922931 -19.4752720
130 -17.1944221 -18.7922931
131 -24.5785537 -17.1944221
132 -14.7181582 -24.5785537
133 -14.8255021 -14.7181582
134 -0.6649599 -14.8255021
135 -31.6898310 -0.6649599
136 -5.8302941 -31.6898310
137 -25.0924831 -5.8302941
138 -24.6022805 -25.0924831
139 -25.6150686 -24.6022805
140 2.1758853 -25.6150686
141 4.0333080 2.1758853
142 5.9693771 4.0333080
143 24.9722282 5.9693771
144 -0.7843086 24.9722282
145 26.3019874 -0.7843086
146 8.1618809 26.3019874
147 -14.4643459 8.1618809
148 -21.8179543 -14.4643459
149 -16.1378030 -21.8179543
150 6.4886904 -16.1378030
151 -1.4821137 6.4886904
152 -27.8413139 -1.4821137
153 -3.5549840 -27.8413139
154 -5.1170363 -3.5549840
155 -28.4965954 -5.1170363
156 -25.5748679 -28.4965954
157 -7.1099855 -25.5748679
158 -28.7949980 -7.1099855
159 5.6626398 -28.7949980
160 18.2245278 5.6626398
161 -14.7904266 18.2245278
162 8.5865902 -14.7904266
163 -16.5939691 8.5865902
164 6.2175268 -16.5939691
165 32.5295276 6.2175268
166 -0.9069044 32.5295276
167 12.8013955 -0.9069044
168 -10.8965828 12.8013955
169 -6.0231023 -10.8965828
170 3.7686143 -6.0231023
171 -22.1989935 3.7686143
172 -19.9273667 -22.1989935
173 -14.5847619 -19.9273667
174 -20.8450755 -14.5847619
175 -18.7326375 -20.8450755
176 -17.4900030 -18.7326375
177 -5.0745130 -17.4900030
178 -5.8502082 -5.0745130
179 0.6352480 -5.8502082
180 0.3867237 0.6352480
181 -3.9398184 0.3867237
182 -17.5925710 -3.9398184
183 -13.6636600 -17.5925710
184 -15.5166903 -13.6636600
185 -18.2756277 -15.5166903
186 -43.1735949 -18.2756277
187 -52.8618501 -43.1735949
188 -24.3019666 -52.8618501
189 -2.5643379 -24.3019666
190 -8.2634604 -2.5643379
191 15.1663115 -8.2634604
192 -8.9493191 15.1663115
193 8.2292599 -8.9493191
194 32.7038786 8.2292599
195 NA 32.7038786
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.5114159 12.7687615
[2,] -4.5707673 -4.5114159
[3,] -1.4044689 -4.5707673
[4,] -3.2491734 -1.4044689
[5,] -2.9294619 -3.2491734
[6,] 3.3986656 -2.9294619
[7,] -7.2058960 3.3986656
[8,] 4.8599607 -7.2058960
[9,] 10.8726355 4.8599607
[10,] 8.7604526 10.8726355
[11,] 7.0660784 8.7604526
[12,] -29.1836515 7.0660784
[13,] -1.2708514 -29.1836515
[14,] -2.7084181 -1.2708514
[15,] -0.2794616 -2.7084181
[16,] -4.5004017 -0.2794616
[17,] 8.7972063 -4.5004017
[18,] 30.6199516 8.7972063
[19,] 1.6985483 30.6199516
[20,] 14.6550240 1.6985483
[21,] 18.6127687 14.6550240
[22,] 29.8962235 18.6127687
[23,] 23.3266525 29.8962235
[24,] 16.0789304 23.3266525
[25,] 9.6026967 16.0789304
[26,] 21.8580665 9.6026967
[27,] -6.4045001 21.8580665
[28,] -4.8751505 -6.4045001
[29,] 14.5331422 -4.8751505
[30,] -0.9158338 14.5331422
[31,] 7.3541339 -0.9158338
[32,] 16.4525285 7.3541339
[33,] 17.2801993 16.4525285
[34,] 22.0669047 17.2801993
[35,] 8.0324724 22.0669047
[36,] -4.0598163 8.0324724
[37,] 5.6301031 -4.0598163
[38,] 16.8083339 5.6301031
[39,] 18.4008060 16.8083339
[40,] 17.2319201 18.4008060
[41,] 6.4753258 17.2319201
[42,] -1.9235606 6.4753258
[43,] 4.2945049 -1.9235606
[44,] 17.8214016 4.2945049
[45,] 14.7312680 17.8214016
[46,] 14.1427584 14.7312680
[47,] 45.8086554 14.1427584
[48,] -12.7060630 45.8086554
[49,] -13.3276264 -12.7060630
[50,] -11.1302293 -13.3276264
[51,] 1.1670536 -11.1302293
[52,] -15.4158281 1.1670536
[53,] -0.1079679 -15.4158281
[54,] 19.5923006 -0.1079679
[55,] 22.1562503 19.5923006
[56,] 18.4773238 22.1562503
[57,] 15.1286808 18.4773238
[58,] 30.6076954 15.1286808
[59,] 34.9223023 30.6076954
[60,] 14.3205441 34.9223023
[61,] 30.5943145 14.3205441
[62,] 8.6895046 30.5943145
[63,] -1.2611558 8.6895046
[64,] 10.8169025 -1.2611558
[65,] 37.1920657 10.8169025
[66,] -0.2170814 37.1920657
[67,] 8.4485464 -0.2170814
[68,] 9.5028594 8.4485464
[69,] -1.6505872 9.5028594
[70,] 14.2154370 -1.6505872
[71,] 5.0398267 14.2154370
[72,] -17.4152922 5.0398267
[73,] -6.6954738 -17.4152922
[74,] -8.5416369 -6.6954738
[75,] 7.2044127 -8.5416369
[76,] -21.1797186 7.2044127
[77,] -2.1230075 -21.1797186
[78,] 0.7890234 -2.1230075
[79,] 16.8144353 0.7890234
[80,] 0.7287899 16.8144353
[81,] -3.6269212 0.7287899
[82,] 0.3312369 -3.6269212
[83,] -11.9780972 0.3312369
[84,] -2.2751505 -11.9780972
[85,] -13.0619793 -2.2751505
[86,] 0.2350693 -13.0619793
[87,] -2.6681951 0.2350693
[88,] 18.9974270 -2.6681951
[89,] 0.7373603 18.9974270
[90,] 2.3216851 0.7373603
[91,] -21.4984173 2.3216851
[92,] -17.6458362 -21.4984173
[93,] 10.2310665 -17.6458362
[94,] -5.3574489 10.2310665
[95,] -25.5649742 -5.3574489
[96,] -19.2520917 -25.5649742
[97,] -6.1339783 -19.2520917
[98,] 4.9498384 -6.1339783
[99,] 15.9313262 4.9498384
[100,] 18.9723554 15.9313262
[101,] 7.3298523 18.9723554
[102,] -7.0357777 7.3298523
[103,] 14.8629761 -7.0357777
[104,] -14.9997758 14.8629761
[105,] -4.3100704 -14.9997758
[106,] -18.8065006 -4.3100704
[107,] -5.1607171 -18.8065006
[108,] -19.4117723 -5.1607171
[109,] 8.4926805 -19.4117723
[110,] 14.3034267 8.4926805
[111,] -9.8159066 14.3034267
[112,] -15.9376725 -9.8159066
[113,] 13.6238043 -15.9376725
[114,] 6.5203638 13.6238043
[115,] 0.6124355 6.5203638
[116,] -9.7196546 0.6124355
[117,] -5.4092093 -9.7196546
[118,] 10.2445042 -5.4092093
[119,] 20.2838774 10.2445042
[120,] -8.3848291 20.2838774
[121,] 17.7938374 -8.3848291
[122,] -3.3248231 17.7938374
[123,] 14.2443004 -3.3248231
[124,] -2.4842041 14.2443004
[125,] 7.8447609 -2.4842041
[126,] 9.1802576 7.8447609
[127,] 15.4959726 9.1802576
[128,] -19.4752720 15.4959726
[129,] -18.7922931 -19.4752720
[130,] -17.1944221 -18.7922931
[131,] -24.5785537 -17.1944221
[132,] -14.7181582 -24.5785537
[133,] -14.8255021 -14.7181582
[134,] -0.6649599 -14.8255021
[135,] -31.6898310 -0.6649599
[136,] -5.8302941 -31.6898310
[137,] -25.0924831 -5.8302941
[138,] -24.6022805 -25.0924831
[139,] -25.6150686 -24.6022805
[140,] 2.1758853 -25.6150686
[141,] 4.0333080 2.1758853
[142,] 5.9693771 4.0333080
[143,] 24.9722282 5.9693771
[144,] -0.7843086 24.9722282
[145,] 26.3019874 -0.7843086
[146,] 8.1618809 26.3019874
[147,] -14.4643459 8.1618809
[148,] -21.8179543 -14.4643459
[149,] -16.1378030 -21.8179543
[150,] 6.4886904 -16.1378030
[151,] -1.4821137 6.4886904
[152,] -27.8413139 -1.4821137
[153,] -3.5549840 -27.8413139
[154,] -5.1170363 -3.5549840
[155,] -28.4965954 -5.1170363
[156,] -25.5748679 -28.4965954
[157,] -7.1099855 -25.5748679
[158,] -28.7949980 -7.1099855
[159,] 5.6626398 -28.7949980
[160,] 18.2245278 5.6626398
[161,] -14.7904266 18.2245278
[162,] 8.5865902 -14.7904266
[163,] -16.5939691 8.5865902
[164,] 6.2175268 -16.5939691
[165,] 32.5295276 6.2175268
[166,] -0.9069044 32.5295276
[167,] 12.8013955 -0.9069044
[168,] -10.8965828 12.8013955
[169,] -6.0231023 -10.8965828
[170,] 3.7686143 -6.0231023
[171,] -22.1989935 3.7686143
[172,] -19.9273667 -22.1989935
[173,] -14.5847619 -19.9273667
[174,] -20.8450755 -14.5847619
[175,] -18.7326375 -20.8450755
[176,] -17.4900030 -18.7326375
[177,] -5.0745130 -17.4900030
[178,] -5.8502082 -5.0745130
[179,] 0.6352480 -5.8502082
[180,] 0.3867237 0.6352480
[181,] -3.9398184 0.3867237
[182,] -17.5925710 -3.9398184
[183,] -13.6636600 -17.5925710
[184,] -15.5166903 -13.6636600
[185,] -18.2756277 -15.5166903
[186,] -43.1735949 -18.2756277
[187,] -52.8618501 -43.1735949
[188,] -24.3019666 -52.8618501
[189,] -2.5643379 -24.3019666
[190,] -8.2634604 -2.5643379
[191,] 15.1663115 -8.2634604
[192,] -8.9493191 15.1663115
[193,] 8.2292599 -8.9493191
[194,] 32.7038786 8.2292599
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.5114159 12.7687615
2 -4.5707673 -4.5114159
3 -1.4044689 -4.5707673
4 -3.2491734 -1.4044689
5 -2.9294619 -3.2491734
6 3.3986656 -2.9294619
7 -7.2058960 3.3986656
8 4.8599607 -7.2058960
9 10.8726355 4.8599607
10 8.7604526 10.8726355
11 7.0660784 8.7604526
12 -29.1836515 7.0660784
13 -1.2708514 -29.1836515
14 -2.7084181 -1.2708514
15 -0.2794616 -2.7084181
16 -4.5004017 -0.2794616
17 8.7972063 -4.5004017
18 30.6199516 8.7972063
19 1.6985483 30.6199516
20 14.6550240 1.6985483
21 18.6127687 14.6550240
22 29.8962235 18.6127687
23 23.3266525 29.8962235
24 16.0789304 23.3266525
25 9.6026967 16.0789304
26 21.8580665 9.6026967
27 -6.4045001 21.8580665
28 -4.8751505 -6.4045001
29 14.5331422 -4.8751505
30 -0.9158338 14.5331422
31 7.3541339 -0.9158338
32 16.4525285 7.3541339
33 17.2801993 16.4525285
34 22.0669047 17.2801993
35 8.0324724 22.0669047
36 -4.0598163 8.0324724
37 5.6301031 -4.0598163
38 16.8083339 5.6301031
39 18.4008060 16.8083339
40 17.2319201 18.4008060
41 6.4753258 17.2319201
42 -1.9235606 6.4753258
43 4.2945049 -1.9235606
44 17.8214016 4.2945049
45 14.7312680 17.8214016
46 14.1427584 14.7312680
47 45.8086554 14.1427584
48 -12.7060630 45.8086554
49 -13.3276264 -12.7060630
50 -11.1302293 -13.3276264
51 1.1670536 -11.1302293
52 -15.4158281 1.1670536
53 -0.1079679 -15.4158281
54 19.5923006 -0.1079679
55 22.1562503 19.5923006
56 18.4773238 22.1562503
57 15.1286808 18.4773238
58 30.6076954 15.1286808
59 34.9223023 30.6076954
60 14.3205441 34.9223023
61 30.5943145 14.3205441
62 8.6895046 30.5943145
63 -1.2611558 8.6895046
64 10.8169025 -1.2611558
65 37.1920657 10.8169025
66 -0.2170814 37.1920657
67 8.4485464 -0.2170814
68 9.5028594 8.4485464
69 -1.6505872 9.5028594
70 14.2154370 -1.6505872
71 5.0398267 14.2154370
72 -17.4152922 5.0398267
73 -6.6954738 -17.4152922
74 -8.5416369 -6.6954738
75 7.2044127 -8.5416369
76 -21.1797186 7.2044127
77 -2.1230075 -21.1797186
78 0.7890234 -2.1230075
79 16.8144353 0.7890234
80 0.7287899 16.8144353
81 -3.6269212 0.7287899
82 0.3312369 -3.6269212
83 -11.9780972 0.3312369
84 -2.2751505 -11.9780972
85 -13.0619793 -2.2751505
86 0.2350693 -13.0619793
87 -2.6681951 0.2350693
88 18.9974270 -2.6681951
89 0.7373603 18.9974270
90 2.3216851 0.7373603
91 -21.4984173 2.3216851
92 -17.6458362 -21.4984173
93 10.2310665 -17.6458362
94 -5.3574489 10.2310665
95 -25.5649742 -5.3574489
96 -19.2520917 -25.5649742
97 -6.1339783 -19.2520917
98 4.9498384 -6.1339783
99 15.9313262 4.9498384
100 18.9723554 15.9313262
101 7.3298523 18.9723554
102 -7.0357777 7.3298523
103 14.8629761 -7.0357777
104 -14.9997758 14.8629761
105 -4.3100704 -14.9997758
106 -18.8065006 -4.3100704
107 -5.1607171 -18.8065006
108 -19.4117723 -5.1607171
109 8.4926805 -19.4117723
110 14.3034267 8.4926805
111 -9.8159066 14.3034267
112 -15.9376725 -9.8159066
113 13.6238043 -15.9376725
114 6.5203638 13.6238043
115 0.6124355 6.5203638
116 -9.7196546 0.6124355
117 -5.4092093 -9.7196546
118 10.2445042 -5.4092093
119 20.2838774 10.2445042
120 -8.3848291 20.2838774
121 17.7938374 -8.3848291
122 -3.3248231 17.7938374
123 14.2443004 -3.3248231
124 -2.4842041 14.2443004
125 7.8447609 -2.4842041
126 9.1802576 7.8447609
127 15.4959726 9.1802576
128 -19.4752720 15.4959726
129 -18.7922931 -19.4752720
130 -17.1944221 -18.7922931
131 -24.5785537 -17.1944221
132 -14.7181582 -24.5785537
133 -14.8255021 -14.7181582
134 -0.6649599 -14.8255021
135 -31.6898310 -0.6649599
136 -5.8302941 -31.6898310
137 -25.0924831 -5.8302941
138 -24.6022805 -25.0924831
139 -25.6150686 -24.6022805
140 2.1758853 -25.6150686
141 4.0333080 2.1758853
142 5.9693771 4.0333080
143 24.9722282 5.9693771
144 -0.7843086 24.9722282
145 26.3019874 -0.7843086
146 8.1618809 26.3019874
147 -14.4643459 8.1618809
148 -21.8179543 -14.4643459
149 -16.1378030 -21.8179543
150 6.4886904 -16.1378030
151 -1.4821137 6.4886904
152 -27.8413139 -1.4821137
153 -3.5549840 -27.8413139
154 -5.1170363 -3.5549840
155 -28.4965954 -5.1170363
156 -25.5748679 -28.4965954
157 -7.1099855 -25.5748679
158 -28.7949980 -7.1099855
159 5.6626398 -28.7949980
160 18.2245278 5.6626398
161 -14.7904266 18.2245278
162 8.5865902 -14.7904266
163 -16.5939691 8.5865902
164 6.2175268 -16.5939691
165 32.5295276 6.2175268
166 -0.9069044 32.5295276
167 12.8013955 -0.9069044
168 -10.8965828 12.8013955
169 -6.0231023 -10.8965828
170 3.7686143 -6.0231023
171 -22.1989935 3.7686143
172 -19.9273667 -22.1989935
173 -14.5847619 -19.9273667
174 -20.8450755 -14.5847619
175 -18.7326375 -20.8450755
176 -17.4900030 -18.7326375
177 -5.0745130 -17.4900030
178 -5.8502082 -5.0745130
179 0.6352480 -5.8502082
180 0.3867237 0.6352480
181 -3.9398184 0.3867237
182 -17.5925710 -3.9398184
183 -13.6636600 -17.5925710
184 -15.5166903 -13.6636600
185 -18.2756277 -15.5166903
186 -43.1735949 -18.2756277
187 -52.8618501 -43.1735949
188 -24.3019666 -52.8618501
189 -2.5643379 -24.3019666
190 -8.2634604 -2.5643379
191 15.1663115 -8.2634604
192 -8.9493191 15.1663115
193 8.2292599 -8.9493191
194 32.7038786 8.2292599
> 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/79chx1386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/85ux51386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/90ns81386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ug881386521634.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
+ if (rownames(mysum$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/11im6b1386521634.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$coefficients)[i],header=TRUE)
+ a<-table.element(a,signif(mysum$coefficients[i,1],6))
+ a<-table.element(a, signif(mysum$coefficients[i,2],6))
+ a<-table.element(a, signif(mysum$coefficients[i,3],4))
+ a<-table.element(a, signif(mysum$coefficients[i,4],6))
+ a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1270mr1386521634.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, signif(sqrt(mysum$r.squared),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$adj.r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[1],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[2],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[3],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, signif(mysum$sigma,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, signif(sum(myerror*myerror),6))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13l85j1386521634.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,signif(x[i],6))
+ a<-table.element(a,signif(x[i]-mysum$resid[i],6))
+ a<-table.element(a,signif(mysum$resid[i],6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14i7kw1386521634.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,signif(gqarr[mypoint-kp3+1,1],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/151vy21386521634.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,signif(numsignificant1,6))
+ a<-table.element(a,signif(numsignificant1/numgqtests,6))
+ 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,signif(numsignificant5,6))
+ a<-table.element(a,signif(numsignificant5/numgqtests,6))
+ 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,signif(numsignificant10,6))
+ a<-table.element(a,signif(numsignificant10/numgqtests,6))
+ 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/168a3a1386521634.tab")
+ }
>
> try(system("convert tmp/1x5cm1386521634.ps tmp/1x5cm1386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zrh51386521634.ps tmp/2zrh51386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x9m71386521634.ps tmp/3x9m71386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/4na2v1386521634.ps tmp/4na2v1386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/5d8a21386521634.ps tmp/5d8a21386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ohhv1386521634.ps tmp/6ohhv1386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/79chx1386521634.ps tmp/79chx1386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/85ux51386521634.ps tmp/85ux51386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/90ns81386521634.ps tmp/90ns81386521634.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ug881386521634.ps tmp/10ug881386521634.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
33.088 5.919 39.374