Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 10 Dec 2009 04:56:28 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/10/t12604462695kpqido7ul0mxkf.htm/, Retrieved Fri, 29 Mar 2024 06:17:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65295, Retrieved Fri, 29 Mar 2024 06:17:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [paper - autocorre...] [2009-12-10 11:56:28] [a931a0a30926b49d162330b43e89b999] [Current]
-    D    [(Partial) Autocorrelation Function] [paper partiele au...] [2009-12-10 17:09:46] [03c44f58d7d4de05d4cfabfda8c46d2c]
-   PD      [(Partial) Autocorrelation Function] [partiele autocorr...] [2009-12-21 15:58:24] [12f02da0296cb21dc23d82ae014a8b71]
- R PD      [(Partial) Autocorrelation Function] [bijlage paper] [2009-12-24 16:33:26] [757146c69eaf0537be37c7b0c18216d8]
-         [(Partial) Autocorrelation Function] [autocorrelation f...] [2009-12-21 14:59:49] [03c44f58d7d4de05d4cfabfda8c46d2c]
-   P     [(Partial) Autocorrelation Function] [autcorrelatie fun...] [2009-12-21 15:23:56] [12f02da0296cb21dc23d82ae014a8b71]
Feedback Forum

Post a new message
Dataseries X:
108.5
112.3
116.6
115.5
120.1
132.9
128.1
129.3
132.5
131
124.9
120.8
122
122.1
127.4
135.2
137.3
135
136
138.4
134.7
138.4
133.9
133.6
141.2
151.8
155.4
156.6
161.6
160.7
156
159.5
168.7
169.9
169.9
185.9
190.8
195.8
211.9
227.1
251.3
256.7
251.9
251.2
270.3
267.2
243
229.9
187.2
178.2
175.2
192.4
187
184
194.1
212.7
217.5
200.5
205.9
196.5
206.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65295&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65295&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65295&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3195422.47520.00808
20.1279440.99110.16282
3-0.005332-0.04130.483597
40.0644550.49930.309708
5-0.007528-0.05830.476846
6-0.136257-1.05540.147728
7-0.146244-1.13280.130902
8-0.36189-2.80320.003403
9-0.105162-0.81460.209267
10-0.110552-0.85630.197612
110.1264830.97970.165576
12-0.059091-0.45770.324406
13-0.114061-0.88350.190244
14-0.021584-0.16720.433892
150.0080650.06250.475197
160.0950160.7360.232301
17-0.053075-0.41110.341227
18-0.058158-0.45050.32699
190.0227040.17590.430496
200.0498760.38630.350305
21-0.089368-0.69220.245727
22-0.113652-0.88030.191092
230.0032720.02530.489931
24-0.048642-0.37680.353835
25-0.013551-0.1050.458377
260.0618660.47920.316764
270.0042080.03260.487053
28-0.001337-0.01040.495886
29-0.027507-0.21310.415998
300.0567480.43960.330915
31-0.008494-0.06580.47388
32-0.050564-0.39170.348347
33-0.064478-0.49940.309646
34-0.053438-0.41390.3402
350.0708780.5490.292514
360.0957950.7420.230484

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.319542 & 2.4752 & 0.00808 \tabularnewline
2 & 0.127944 & 0.9911 & 0.16282 \tabularnewline
3 & -0.005332 & -0.0413 & 0.483597 \tabularnewline
4 & 0.064455 & 0.4993 & 0.309708 \tabularnewline
5 & -0.007528 & -0.0583 & 0.476846 \tabularnewline
6 & -0.136257 & -1.0554 & 0.147728 \tabularnewline
7 & -0.146244 & -1.1328 & 0.130902 \tabularnewline
8 & -0.36189 & -2.8032 & 0.003403 \tabularnewline
9 & -0.105162 & -0.8146 & 0.209267 \tabularnewline
10 & -0.110552 & -0.8563 & 0.197612 \tabularnewline
11 & 0.126483 & 0.9797 & 0.165576 \tabularnewline
12 & -0.059091 & -0.4577 & 0.324406 \tabularnewline
13 & -0.114061 & -0.8835 & 0.190244 \tabularnewline
14 & -0.021584 & -0.1672 & 0.433892 \tabularnewline
15 & 0.008065 & 0.0625 & 0.475197 \tabularnewline
16 & 0.095016 & 0.736 & 0.232301 \tabularnewline
17 & -0.053075 & -0.4111 & 0.341227 \tabularnewline
18 & -0.058158 & -0.4505 & 0.32699 \tabularnewline
19 & 0.022704 & 0.1759 & 0.430496 \tabularnewline
20 & 0.049876 & 0.3863 & 0.350305 \tabularnewline
21 & -0.089368 & -0.6922 & 0.245727 \tabularnewline
22 & -0.113652 & -0.8803 & 0.191092 \tabularnewline
23 & 0.003272 & 0.0253 & 0.489931 \tabularnewline
24 & -0.048642 & -0.3768 & 0.353835 \tabularnewline
25 & -0.013551 & -0.105 & 0.458377 \tabularnewline
26 & 0.061866 & 0.4792 & 0.316764 \tabularnewline
27 & 0.004208 & 0.0326 & 0.487053 \tabularnewline
28 & -0.001337 & -0.0104 & 0.495886 \tabularnewline
29 & -0.027507 & -0.2131 & 0.415998 \tabularnewline
30 & 0.056748 & 0.4396 & 0.330915 \tabularnewline
31 & -0.008494 & -0.0658 & 0.47388 \tabularnewline
32 & -0.050564 & -0.3917 & 0.348347 \tabularnewline
33 & -0.064478 & -0.4994 & 0.309646 \tabularnewline
34 & -0.053438 & -0.4139 & 0.3402 \tabularnewline
35 & 0.070878 & 0.549 & 0.292514 \tabularnewline
36 & 0.095795 & 0.742 & 0.230484 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65295&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.319542[/C][C]2.4752[/C][C]0.00808[/C][/ROW]
[ROW][C]2[/C][C]0.127944[/C][C]0.9911[/C][C]0.16282[/C][/ROW]
[ROW][C]3[/C][C]-0.005332[/C][C]-0.0413[/C][C]0.483597[/C][/ROW]
[ROW][C]4[/C][C]0.064455[/C][C]0.4993[/C][C]0.309708[/C][/ROW]
[ROW][C]5[/C][C]-0.007528[/C][C]-0.0583[/C][C]0.476846[/C][/ROW]
[ROW][C]6[/C][C]-0.136257[/C][C]-1.0554[/C][C]0.147728[/C][/ROW]
[ROW][C]7[/C][C]-0.146244[/C][C]-1.1328[/C][C]0.130902[/C][/ROW]
[ROW][C]8[/C][C]-0.36189[/C][C]-2.8032[/C][C]0.003403[/C][/ROW]
[ROW][C]9[/C][C]-0.105162[/C][C]-0.8146[/C][C]0.209267[/C][/ROW]
[ROW][C]10[/C][C]-0.110552[/C][C]-0.8563[/C][C]0.197612[/C][/ROW]
[ROW][C]11[/C][C]0.126483[/C][C]0.9797[/C][C]0.165576[/C][/ROW]
[ROW][C]12[/C][C]-0.059091[/C][C]-0.4577[/C][C]0.324406[/C][/ROW]
[ROW][C]13[/C][C]-0.114061[/C][C]-0.8835[/C][C]0.190244[/C][/ROW]
[ROW][C]14[/C][C]-0.021584[/C][C]-0.1672[/C][C]0.433892[/C][/ROW]
[ROW][C]15[/C][C]0.008065[/C][C]0.0625[/C][C]0.475197[/C][/ROW]
[ROW][C]16[/C][C]0.095016[/C][C]0.736[/C][C]0.232301[/C][/ROW]
[ROW][C]17[/C][C]-0.053075[/C][C]-0.4111[/C][C]0.341227[/C][/ROW]
[ROW][C]18[/C][C]-0.058158[/C][C]-0.4505[/C][C]0.32699[/C][/ROW]
[ROW][C]19[/C][C]0.022704[/C][C]0.1759[/C][C]0.430496[/C][/ROW]
[ROW][C]20[/C][C]0.049876[/C][C]0.3863[/C][C]0.350305[/C][/ROW]
[ROW][C]21[/C][C]-0.089368[/C][C]-0.6922[/C][C]0.245727[/C][/ROW]
[ROW][C]22[/C][C]-0.113652[/C][C]-0.8803[/C][C]0.191092[/C][/ROW]
[ROW][C]23[/C][C]0.003272[/C][C]0.0253[/C][C]0.489931[/C][/ROW]
[ROW][C]24[/C][C]-0.048642[/C][C]-0.3768[/C][C]0.353835[/C][/ROW]
[ROW][C]25[/C][C]-0.013551[/C][C]-0.105[/C][C]0.458377[/C][/ROW]
[ROW][C]26[/C][C]0.061866[/C][C]0.4792[/C][C]0.316764[/C][/ROW]
[ROW][C]27[/C][C]0.004208[/C][C]0.0326[/C][C]0.487053[/C][/ROW]
[ROW][C]28[/C][C]-0.001337[/C][C]-0.0104[/C][C]0.495886[/C][/ROW]
[ROW][C]29[/C][C]-0.027507[/C][C]-0.2131[/C][C]0.415998[/C][/ROW]
[ROW][C]30[/C][C]0.056748[/C][C]0.4396[/C][C]0.330915[/C][/ROW]
[ROW][C]31[/C][C]-0.008494[/C][C]-0.0658[/C][C]0.47388[/C][/ROW]
[ROW][C]32[/C][C]-0.050564[/C][C]-0.3917[/C][C]0.348347[/C][/ROW]
[ROW][C]33[/C][C]-0.064478[/C][C]-0.4994[/C][C]0.309646[/C][/ROW]
[ROW][C]34[/C][C]-0.053438[/C][C]-0.4139[/C][C]0.3402[/C][/ROW]
[ROW][C]35[/C][C]0.070878[/C][C]0.549[/C][C]0.292514[/C][/ROW]
[ROW][C]36[/C][C]0.095795[/C][C]0.742[/C][C]0.230484[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65295&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65295&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3195422.47520.00808
20.1279440.99110.16282
3-0.005332-0.04130.483597
40.0644550.49930.309708
5-0.007528-0.05830.476846
6-0.136257-1.05540.147728
7-0.146244-1.13280.130902
8-0.36189-2.80320.003403
9-0.105162-0.81460.209267
10-0.110552-0.85630.197612
110.1264830.97970.165576
12-0.059091-0.45770.324406
13-0.114061-0.88350.190244
14-0.021584-0.16720.433892
150.0080650.06250.475197
160.0950160.7360.232301
17-0.053075-0.41110.341227
18-0.058158-0.45050.32699
190.0227040.17590.430496
200.0498760.38630.350305
21-0.089368-0.69220.245727
22-0.113652-0.88030.191092
230.0032720.02530.489931
24-0.048642-0.37680.353835
25-0.013551-0.1050.458377
260.0618660.47920.316764
270.0042080.03260.487053
28-0.001337-0.01040.495886
29-0.027507-0.21310.415998
300.0567480.43960.330915
31-0.008494-0.06580.47388
32-0.050564-0.39170.348347
33-0.064478-0.49940.309646
34-0.053438-0.41390.3402
350.0708780.5490.292514
360.0957950.7420.230484







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3195422.47520.00808
20.0287750.22290.412188
3-0.060451-0.46830.32065
40.0887760.68770.247161
5-0.050571-0.39170.348327
6-0.151543-1.17390.122547
7-0.054829-0.42470.336286
8-0.327829-2.53940.006858
90.1160660.8990.186111
10-0.066615-0.5160.303877
110.1928821.49410.070201
12-0.137479-1.06490.145592
13-0.135426-1.0490.149192
140.0076980.05960.476324
15-0.071088-0.55060.291962
160.0028540.02210.491219
17-0.034971-0.27090.393704
18-0.126896-0.98290.164794
190.2401121.85990.033902
20-0.168294-1.30360.098675
21-0.172346-1.3350.093462
22-0.078738-0.60990.272115
230.0305260.23650.406943
240.0041170.03190.487332
25-0.055412-0.42920.33465
260.0693720.53740.296505
27-0.05539-0.4290.334713
28-0.055822-0.43240.333503
29-0.061628-0.47740.317417
30-0.128099-0.99220.16253
31-0.005033-0.0390.484517
32-0.011449-0.08870.464815
33-0.032763-0.25380.400265
34-0.067951-0.52630.300293
350.0444580.34440.365885
360.1144910.88680.189353

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.319542 & 2.4752 & 0.00808 \tabularnewline
2 & 0.028775 & 0.2229 & 0.412188 \tabularnewline
3 & -0.060451 & -0.4683 & 0.32065 \tabularnewline
4 & 0.088776 & 0.6877 & 0.247161 \tabularnewline
5 & -0.050571 & -0.3917 & 0.348327 \tabularnewline
6 & -0.151543 & -1.1739 & 0.122547 \tabularnewline
7 & -0.054829 & -0.4247 & 0.336286 \tabularnewline
8 & -0.327829 & -2.5394 & 0.006858 \tabularnewline
9 & 0.116066 & 0.899 & 0.186111 \tabularnewline
10 & -0.066615 & -0.516 & 0.303877 \tabularnewline
11 & 0.192882 & 1.4941 & 0.070201 \tabularnewline
12 & -0.137479 & -1.0649 & 0.145592 \tabularnewline
13 & -0.135426 & -1.049 & 0.149192 \tabularnewline
14 & 0.007698 & 0.0596 & 0.476324 \tabularnewline
15 & -0.071088 & -0.5506 & 0.291962 \tabularnewline
16 & 0.002854 & 0.0221 & 0.491219 \tabularnewline
17 & -0.034971 & -0.2709 & 0.393704 \tabularnewline
18 & -0.126896 & -0.9829 & 0.164794 \tabularnewline
19 & 0.240112 & 1.8599 & 0.033902 \tabularnewline
20 & -0.168294 & -1.3036 & 0.098675 \tabularnewline
21 & -0.172346 & -1.335 & 0.093462 \tabularnewline
22 & -0.078738 & -0.6099 & 0.272115 \tabularnewline
23 & 0.030526 & 0.2365 & 0.406943 \tabularnewline
24 & 0.004117 & 0.0319 & 0.487332 \tabularnewline
25 & -0.055412 & -0.4292 & 0.33465 \tabularnewline
26 & 0.069372 & 0.5374 & 0.296505 \tabularnewline
27 & -0.05539 & -0.429 & 0.334713 \tabularnewline
28 & -0.055822 & -0.4324 & 0.333503 \tabularnewline
29 & -0.061628 & -0.4774 & 0.317417 \tabularnewline
30 & -0.128099 & -0.9922 & 0.16253 \tabularnewline
31 & -0.005033 & -0.039 & 0.484517 \tabularnewline
32 & -0.011449 & -0.0887 & 0.464815 \tabularnewline
33 & -0.032763 & -0.2538 & 0.400265 \tabularnewline
34 & -0.067951 & -0.5263 & 0.300293 \tabularnewline
35 & 0.044458 & 0.3444 & 0.365885 \tabularnewline
36 & 0.114491 & 0.8868 & 0.189353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65295&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.319542[/C][C]2.4752[/C][C]0.00808[/C][/ROW]
[ROW][C]2[/C][C]0.028775[/C][C]0.2229[/C][C]0.412188[/C][/ROW]
[ROW][C]3[/C][C]-0.060451[/C][C]-0.4683[/C][C]0.32065[/C][/ROW]
[ROW][C]4[/C][C]0.088776[/C][C]0.6877[/C][C]0.247161[/C][/ROW]
[ROW][C]5[/C][C]-0.050571[/C][C]-0.3917[/C][C]0.348327[/C][/ROW]
[ROW][C]6[/C][C]-0.151543[/C][C]-1.1739[/C][C]0.122547[/C][/ROW]
[ROW][C]7[/C][C]-0.054829[/C][C]-0.4247[/C][C]0.336286[/C][/ROW]
[ROW][C]8[/C][C]-0.327829[/C][C]-2.5394[/C][C]0.006858[/C][/ROW]
[ROW][C]9[/C][C]0.116066[/C][C]0.899[/C][C]0.186111[/C][/ROW]
[ROW][C]10[/C][C]-0.066615[/C][C]-0.516[/C][C]0.303877[/C][/ROW]
[ROW][C]11[/C][C]0.192882[/C][C]1.4941[/C][C]0.070201[/C][/ROW]
[ROW][C]12[/C][C]-0.137479[/C][C]-1.0649[/C][C]0.145592[/C][/ROW]
[ROW][C]13[/C][C]-0.135426[/C][C]-1.049[/C][C]0.149192[/C][/ROW]
[ROW][C]14[/C][C]0.007698[/C][C]0.0596[/C][C]0.476324[/C][/ROW]
[ROW][C]15[/C][C]-0.071088[/C][C]-0.5506[/C][C]0.291962[/C][/ROW]
[ROW][C]16[/C][C]0.002854[/C][C]0.0221[/C][C]0.491219[/C][/ROW]
[ROW][C]17[/C][C]-0.034971[/C][C]-0.2709[/C][C]0.393704[/C][/ROW]
[ROW][C]18[/C][C]-0.126896[/C][C]-0.9829[/C][C]0.164794[/C][/ROW]
[ROW][C]19[/C][C]0.240112[/C][C]1.8599[/C][C]0.033902[/C][/ROW]
[ROW][C]20[/C][C]-0.168294[/C][C]-1.3036[/C][C]0.098675[/C][/ROW]
[ROW][C]21[/C][C]-0.172346[/C][C]-1.335[/C][C]0.093462[/C][/ROW]
[ROW][C]22[/C][C]-0.078738[/C][C]-0.6099[/C][C]0.272115[/C][/ROW]
[ROW][C]23[/C][C]0.030526[/C][C]0.2365[/C][C]0.406943[/C][/ROW]
[ROW][C]24[/C][C]0.004117[/C][C]0.0319[/C][C]0.487332[/C][/ROW]
[ROW][C]25[/C][C]-0.055412[/C][C]-0.4292[/C][C]0.33465[/C][/ROW]
[ROW][C]26[/C][C]0.069372[/C][C]0.5374[/C][C]0.296505[/C][/ROW]
[ROW][C]27[/C][C]-0.05539[/C][C]-0.429[/C][C]0.334713[/C][/ROW]
[ROW][C]28[/C][C]-0.055822[/C][C]-0.4324[/C][C]0.333503[/C][/ROW]
[ROW][C]29[/C][C]-0.061628[/C][C]-0.4774[/C][C]0.317417[/C][/ROW]
[ROW][C]30[/C][C]-0.128099[/C][C]-0.9922[/C][C]0.16253[/C][/ROW]
[ROW][C]31[/C][C]-0.005033[/C][C]-0.039[/C][C]0.484517[/C][/ROW]
[ROW][C]32[/C][C]-0.011449[/C][C]-0.0887[/C][C]0.464815[/C][/ROW]
[ROW][C]33[/C][C]-0.032763[/C][C]-0.2538[/C][C]0.400265[/C][/ROW]
[ROW][C]34[/C][C]-0.067951[/C][C]-0.5263[/C][C]0.300293[/C][/ROW]
[ROW][C]35[/C][C]0.044458[/C][C]0.3444[/C][C]0.365885[/C][/ROW]
[ROW][C]36[/C][C]0.114491[/C][C]0.8868[/C][C]0.189353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65295&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65295&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3195422.47520.00808
20.0287750.22290.412188
3-0.060451-0.46830.32065
40.0887760.68770.247161
5-0.050571-0.39170.348327
6-0.151543-1.17390.122547
7-0.054829-0.42470.336286
8-0.327829-2.53940.006858
90.1160660.8990.186111
10-0.066615-0.5160.303877
110.1928821.49410.070201
12-0.137479-1.06490.145592
13-0.135426-1.0490.149192
140.0076980.05960.476324
15-0.071088-0.55060.291962
160.0028540.02210.491219
17-0.034971-0.27090.393704
18-0.126896-0.98290.164794
190.2401121.85990.033902
20-0.168294-1.30360.098675
21-0.172346-1.3350.093462
22-0.078738-0.60990.272115
230.0305260.23650.406943
240.0041170.03190.487332
25-0.055412-0.42920.33465
260.0693720.53740.296505
27-0.05539-0.4290.334713
28-0.055822-0.43240.333503
29-0.061628-0.47740.317417
30-0.128099-0.99220.16253
31-0.005033-0.0390.484517
32-0.011449-0.08870.464815
33-0.032763-0.25380.400265
34-0.067951-0.52630.300293
350.0444580.34440.365885
360.1144910.88680.189353



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')