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Description of Statistical Computation

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, 18 Dec 2008 09:25:12 -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/2008/Dec/18/t1229617537filcchh6xf30exl.htm/, Retrieved Sat, 24 May 2025 22:25:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34877, Retrieved Sat, 24 May 2025 22:25:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsACF
Estimated Impact279

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Standard Deviation-Mean Plot] [q1] [2008-12-08 12:37:39] [3ffd109c9e040b1ae7e5dbe576d4698c]
F    D    [Standard Deviation-Mean Plot] [SMP] [2008-12-08 12:41:29] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM        [Variance Reduction Matrix] [VRM] [2008-12-08 13:10:17] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM          [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:14:12] [3ffd109c9e040b1ae7e5dbe576d4698c]
F               [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:16:18] [3ffd109c9e040b1ae7e5dbe576d4698c]
- R P               [(Partial) Autocorrelation Function] [ACF] [2008-12-18 16:25:12] [962e6c9020896982bc8283b8971710a9] [Current]
-   P                 [(Partial) Autocorrelation Function] [ACF] [2008-12-24 12:57:31] [b28ef2aea2cd58ceb5ad90223572c703]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111
125326
122716
116615
113719
110737
112093
143565
149946
149147
134339
122683
115614
116566
111272
104609
101802
94542
93051
124129
130374
123946
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867
120327
117008
108811

Tables (Output of Computation)





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=34877&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=34877&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34877&T=0

As an alternative you can also use a QR Code:  
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
10.8088546.31730
20.5243154.0956.3e-05
30.2834632.21390.015292
40.1486251.16080.125123
50.0926990.7240.235915
60.0698360.54540.293721
70.0600760.46920.320296
80.0784870.6130.271076
90.1951071.52380.066359
100.3585882.80070.003411
110.5398924.21674.2e-05
120.6189544.83425e-06
130.4472533.49320.000447
140.2096531.63740.053344
150.0148770.11620.45394
16-0.091082-0.71140.239783
17-0.140891-1.10040.137742
18-0.166585-1.30110.099064
19-0.180372-1.40870.081993
20-0.166487-1.30030.099194
21-0.069498-0.54280.294625
220.0538230.42040.337845
230.1792341.39990.08331
240.2310781.80480.038023
250.1051710.82140.207305
26-0.056093-0.43810.331431
27-0.183593-1.43390.078353
28-0.235414-1.83860.035419
29-0.257592-2.01190.024329
30-0.264211-2.06360.021661
31-0.270081-2.10940.019511
32-0.259621-2.02770.023483
33-0.191255-1.49370.070198
34-0.118472-0.92530.179229
35-0.032256-0.25190.400972
360.0028660.02240.491109

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.808854 & 6.3173 & 0 \tabularnewline
2 & 0.524315 & 4.095 & 6.3e-05 \tabularnewline
3 & 0.283463 & 2.2139 & 0.015292 \tabularnewline
4 & 0.148625 & 1.1608 & 0.125123 \tabularnewline
5 & 0.092699 & 0.724 & 0.235915 \tabularnewline
6 & 0.069836 & 0.5454 & 0.293721 \tabularnewline
7 & 0.060076 & 0.4692 & 0.320296 \tabularnewline
8 & 0.078487 & 0.613 & 0.271076 \tabularnewline
9 & 0.195107 & 1.5238 & 0.066359 \tabularnewline
10 & 0.358588 & 2.8007 & 0.003411 \tabularnewline
11 & 0.539892 & 4.2167 & 4.2e-05 \tabularnewline
12 & 0.618954 & 4.8342 & 5e-06 \tabularnewline
13 & 0.447253 & 3.4932 & 0.000447 \tabularnewline
14 & 0.209653 & 1.6374 & 0.053344 \tabularnewline
15 & 0.014877 & 0.1162 & 0.45394 \tabularnewline
16 & -0.091082 & -0.7114 & 0.239783 \tabularnewline
17 & -0.140891 & -1.1004 & 0.137742 \tabularnewline
18 & -0.166585 & -1.3011 & 0.099064 \tabularnewline
19 & -0.180372 & -1.4087 & 0.081993 \tabularnewline
20 & -0.166487 & -1.3003 & 0.099194 \tabularnewline
21 & -0.069498 & -0.5428 & 0.294625 \tabularnewline
22 & 0.053823 & 0.4204 & 0.337845 \tabularnewline
23 & 0.179234 & 1.3999 & 0.08331 \tabularnewline
24 & 0.231078 & 1.8048 & 0.038023 \tabularnewline
25 & 0.105171 & 0.8214 & 0.207305 \tabularnewline
26 & -0.056093 & -0.4381 & 0.331431 \tabularnewline
27 & -0.183593 & -1.4339 & 0.078353 \tabularnewline
28 & -0.235414 & -1.8386 & 0.035419 \tabularnewline
29 & -0.257592 & -2.0119 & 0.024329 \tabularnewline
30 & -0.264211 & -2.0636 & 0.021661 \tabularnewline
31 & -0.270081 & -2.1094 & 0.019511 \tabularnewline
32 & -0.259621 & -2.0277 & 0.023483 \tabularnewline
33 & -0.191255 & -1.4937 & 0.070198 \tabularnewline
34 & -0.118472 & -0.9253 & 0.179229 \tabularnewline
35 & -0.032256 & -0.2519 & 0.400972 \tabularnewline
36 & 0.002866 & 0.0224 & 0.491109 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34877&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]0.808854[/C][C]6.3173[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.524315[/C][C]4.095[/C][C]6.3e-05[/C][/ROW]
[ROW][C]3[/C][C]0.283463[/C][C]2.2139[/C][C]0.015292[/C][/ROW]
[ROW][C]4[/C][C]0.148625[/C][C]1.1608[/C][C]0.125123[/C][/ROW]
[ROW][C]5[/C][C]0.092699[/C][C]0.724[/C][C]0.235915[/C][/ROW]
[ROW][C]6[/C][C]0.069836[/C][C]0.5454[/C][C]0.293721[/C][/ROW]
[ROW][C]7[/C][C]0.060076[/C][C]0.4692[/C][C]0.320296[/C][/ROW]
[ROW][C]8[/C][C]0.078487[/C][C]0.613[/C][C]0.271076[/C][/ROW]
[ROW][C]9[/C][C]0.195107[/C][C]1.5238[/C][C]0.066359[/C][/ROW]
[ROW][C]10[/C][C]0.358588[/C][C]2.8007[/C][C]0.003411[/C][/ROW]
[ROW][C]11[/C][C]0.539892[/C][C]4.2167[/C][C]4.2e-05[/C][/ROW]
[ROW][C]12[/C][C]0.618954[/C][C]4.8342[/C][C]5e-06[/C][/ROW]
[ROW][C]13[/C][C]0.447253[/C][C]3.4932[/C][C]0.000447[/C][/ROW]
[ROW][C]14[/C][C]0.209653[/C][C]1.6374[/C][C]0.053344[/C][/ROW]
[ROW][C]15[/C][C]0.014877[/C][C]0.1162[/C][C]0.45394[/C][/ROW]
[ROW][C]16[/C][C]-0.091082[/C][C]-0.7114[/C][C]0.239783[/C][/ROW]
[ROW][C]17[/C][C]-0.140891[/C][C]-1.1004[/C][C]0.137742[/C][/ROW]
[ROW][C]18[/C][C]-0.166585[/C][C]-1.3011[/C][C]0.099064[/C][/ROW]
[ROW][C]19[/C][C]-0.180372[/C][C]-1.4087[/C][C]0.081993[/C][/ROW]
[ROW][C]20[/C][C]-0.166487[/C][C]-1.3003[/C][C]0.099194[/C][/ROW]
[ROW][C]21[/C][C]-0.069498[/C][C]-0.5428[/C][C]0.294625[/C][/ROW]
[ROW][C]22[/C][C]0.053823[/C][C]0.4204[/C][C]0.337845[/C][/ROW]
[ROW][C]23[/C][C]0.179234[/C][C]1.3999[/C][C]0.08331[/C][/ROW]
[ROW][C]24[/C][C]0.231078[/C][C]1.8048[/C][C]0.038023[/C][/ROW]
[ROW][C]25[/C][C]0.105171[/C][C]0.8214[/C][C]0.207305[/C][/ROW]
[ROW][C]26[/C][C]-0.056093[/C][C]-0.4381[/C][C]0.331431[/C][/ROW]
[ROW][C]27[/C][C]-0.183593[/C][C]-1.4339[/C][C]0.078353[/C][/ROW]
[ROW][C]28[/C][C]-0.235414[/C][C]-1.8386[/C][C]0.035419[/C][/ROW]
[ROW][C]29[/C][C]-0.257592[/C][C]-2.0119[/C][C]0.024329[/C][/ROW]
[ROW][C]30[/C][C]-0.264211[/C][C]-2.0636[/C][C]0.021661[/C][/ROW]
[ROW][C]31[/C][C]-0.270081[/C][C]-2.1094[/C][C]0.019511[/C][/ROW]
[ROW][C]32[/C][C]-0.259621[/C][C]-2.0277[/C][C]0.023483[/C][/ROW]
[ROW][C]33[/C][C]-0.191255[/C][C]-1.4937[/C][C]0.070198[/C][/ROW]
[ROW][C]34[/C][C]-0.118472[/C][C]-0.9253[/C][C]0.179229[/C][/ROW]
[ROW][C]35[/C][C]-0.032256[/C][C]-0.2519[/C][C]0.400972[/C][/ROW]
[ROW][C]36[/C][C]0.002866[/C][C]0.0224[/C][C]0.491109[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34877&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34877&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8088546.31730
20.5243154.0956.3e-05
30.2834632.21390.015292
40.1486251.16080.125123
50.0926990.7240.235915
60.0698360.54540.293721
70.0600760.46920.320296
80.0784870.6130.271076
90.1951071.52380.066359
100.3585882.80070.003411
110.5398924.21674.2e-05
120.6189544.83425e-06
130.4472533.49320.000447
140.2096531.63740.053344
150.0148770.11620.45394
16-0.091082-0.71140.239783
17-0.140891-1.10040.137742
18-0.166585-1.30110.099064
19-0.180372-1.40870.081993
20-0.166487-1.30030.099194
21-0.069498-0.54280.294625
220.0538230.42040.337845
230.1792341.39990.08331
240.2310781.80480.038023
250.1051710.82140.207305
26-0.056093-0.43810.331431
27-0.183593-1.43390.078353
28-0.235414-1.83860.035419
29-0.257592-2.01190.024329
30-0.264211-2.06360.021661
31-0.270081-2.10940.019511
32-0.259621-2.02770.023483
33-0.191255-1.49370.070198
34-0.118472-0.92530.179229
35-0.032256-0.25190.400972
360.0028660.02240.491109






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8088546.31730
2-0.375784-2.9350.002348
30.013320.1040.458743
40.0868830.67860.249986
50.0050910.03980.484205
6-0.014057-0.10980.456469
70.0212840.16620.434261
80.091990.71850.237607
90.3174522.47940.00797
100.1551051.21140.115206
110.294732.30190.012384
120.0108870.0850.466259
13-0.518357-4.04857.4e-05
140.0875030.68340.248464
15-0.072215-0.5640.287406
16-0.121677-0.95030.172849
170.0082560.06450.4744
18-0.124739-0.97420.166891
19-0.005248-0.0410.48372
20-0.070924-0.55390.290825
21-0.083571-0.65270.258198
220.0188730.14740.44165
23-0.057225-0.44690.328251
240.0933230.72890.234434
25-0.096-0.74980.228133
260.0747740.5840.280686
270.0144850.11310.455148
28-0.00477-0.03730.485201
290.0303440.2370.406728
30-0.022445-0.17530.430712
31-0.018997-0.14840.441269
32-0.027153-0.21210.416378
33-0.117495-0.91770.181204
34-0.04271-0.33360.369921
35-0.005243-0.0410.483734
36-0.049782-0.38880.349387

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.808854 & 6.3173 & 0 \tabularnewline
2 & -0.375784 & -2.935 & 0.002348 \tabularnewline
3 & 0.01332 & 0.104 & 0.458743 \tabularnewline
4 & 0.086883 & 0.6786 & 0.249986 \tabularnewline
5 & 0.005091 & 0.0398 & 0.484205 \tabularnewline
6 & -0.014057 & -0.1098 & 0.456469 \tabularnewline
7 & 0.021284 & 0.1662 & 0.434261 \tabularnewline
8 & 0.09199 & 0.7185 & 0.237607 \tabularnewline
9 & 0.317452 & 2.4794 & 0.00797 \tabularnewline
10 & 0.155105 & 1.2114 & 0.115206 \tabularnewline
11 & 0.29473 & 2.3019 & 0.012384 \tabularnewline
12 & 0.010887 & 0.085 & 0.466259 \tabularnewline
13 & -0.518357 & -4.0485 & 7.4e-05 \tabularnewline
14 & 0.087503 & 0.6834 & 0.248464 \tabularnewline
15 & -0.072215 & -0.564 & 0.287406 \tabularnewline
16 & -0.121677 & -0.9503 & 0.172849 \tabularnewline
17 & 0.008256 & 0.0645 & 0.4744 \tabularnewline
18 & -0.124739 & -0.9742 & 0.166891 \tabularnewline
19 & -0.005248 & -0.041 & 0.48372 \tabularnewline
20 & -0.070924 & -0.5539 & 0.290825 \tabularnewline
21 & -0.083571 & -0.6527 & 0.258198 \tabularnewline
22 & 0.018873 & 0.1474 & 0.44165 \tabularnewline
23 & -0.057225 & -0.4469 & 0.328251 \tabularnewline
24 & 0.093323 & 0.7289 & 0.234434 \tabularnewline
25 & -0.096 & -0.7498 & 0.228133 \tabularnewline
26 & 0.074774 & 0.584 & 0.280686 \tabularnewline
27 & 0.014485 & 0.1131 & 0.455148 \tabularnewline
28 & -0.00477 & -0.0373 & 0.485201 \tabularnewline
29 & 0.030344 & 0.237 & 0.406728 \tabularnewline
30 & -0.022445 & -0.1753 & 0.430712 \tabularnewline
31 & -0.018997 & -0.1484 & 0.441269 \tabularnewline
32 & -0.027153 & -0.2121 & 0.416378 \tabularnewline
33 & -0.117495 & -0.9177 & 0.181204 \tabularnewline
34 & -0.04271 & -0.3336 & 0.369921 \tabularnewline
35 & -0.005243 & -0.041 & 0.483734 \tabularnewline
36 & -0.049782 & -0.3888 & 0.349387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34877&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]0.808854[/C][C]6.3173[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.375784[/C][C]-2.935[/C][C]0.002348[/C][/ROW]
[ROW][C]3[/C][C]0.01332[/C][C]0.104[/C][C]0.458743[/C][/ROW]
[ROW][C]4[/C][C]0.086883[/C][C]0.6786[/C][C]0.249986[/C][/ROW]
[ROW][C]5[/C][C]0.005091[/C][C]0.0398[/C][C]0.484205[/C][/ROW]
[ROW][C]6[/C][C]-0.014057[/C][C]-0.1098[/C][C]0.456469[/C][/ROW]
[ROW][C]7[/C][C]0.021284[/C][C]0.1662[/C][C]0.434261[/C][/ROW]
[ROW][C]8[/C][C]0.09199[/C][C]0.7185[/C][C]0.237607[/C][/ROW]
[ROW][C]9[/C][C]0.317452[/C][C]2.4794[/C][C]0.00797[/C][/ROW]
[ROW][C]10[/C][C]0.155105[/C][C]1.2114[/C][C]0.115206[/C][/ROW]
[ROW][C]11[/C][C]0.29473[/C][C]2.3019[/C][C]0.012384[/C][/ROW]
[ROW][C]12[/C][C]0.010887[/C][C]0.085[/C][C]0.466259[/C][/ROW]
[ROW][C]13[/C][C]-0.518357[/C][C]-4.0485[/C][C]7.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.087503[/C][C]0.6834[/C][C]0.248464[/C][/ROW]
[ROW][C]15[/C][C]-0.072215[/C][C]-0.564[/C][C]0.287406[/C][/ROW]
[ROW][C]16[/C][C]-0.121677[/C][C]-0.9503[/C][C]0.172849[/C][/ROW]
[ROW][C]17[/C][C]0.008256[/C][C]0.0645[/C][C]0.4744[/C][/ROW]
[ROW][C]18[/C][C]-0.124739[/C][C]-0.9742[/C][C]0.166891[/C][/ROW]
[ROW][C]19[/C][C]-0.005248[/C][C]-0.041[/C][C]0.48372[/C][/ROW]
[ROW][C]20[/C][C]-0.070924[/C][C]-0.5539[/C][C]0.290825[/C][/ROW]
[ROW][C]21[/C][C]-0.083571[/C][C]-0.6527[/C][C]0.258198[/C][/ROW]
[ROW][C]22[/C][C]0.018873[/C][C]0.1474[/C][C]0.44165[/C][/ROW]
[ROW][C]23[/C][C]-0.057225[/C][C]-0.4469[/C][C]0.328251[/C][/ROW]
[ROW][C]24[/C][C]0.093323[/C][C]0.7289[/C][C]0.234434[/C][/ROW]
[ROW][C]25[/C][C]-0.096[/C][C]-0.7498[/C][C]0.228133[/C][/ROW]
[ROW][C]26[/C][C]0.074774[/C][C]0.584[/C][C]0.280686[/C][/ROW]
[ROW][C]27[/C][C]0.014485[/C][C]0.1131[/C][C]0.455148[/C][/ROW]
[ROW][C]28[/C][C]-0.00477[/C][C]-0.0373[/C][C]0.485201[/C][/ROW]
[ROW][C]29[/C][C]0.030344[/C][C]0.237[/C][C]0.406728[/C][/ROW]
[ROW][C]30[/C][C]-0.022445[/C][C]-0.1753[/C][C]0.430712[/C][/ROW]
[ROW][C]31[/C][C]-0.018997[/C][C]-0.1484[/C][C]0.441269[/C][/ROW]
[ROW][C]32[/C][C]-0.027153[/C][C]-0.2121[/C][C]0.416378[/C][/ROW]
[ROW][C]33[/C][C]-0.117495[/C][C]-0.9177[/C][C]0.181204[/C][/ROW]
[ROW][C]34[/C][C]-0.04271[/C][C]-0.3336[/C][C]0.369921[/C][/ROW]
[ROW][C]35[/C][C]-0.005243[/C][C]-0.041[/C][C]0.483734[/C][/ROW]
[ROW][C]36[/C][C]-0.049782[/C][C]-0.3888[/C][C]0.349387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34877&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34877&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8088546.31730
2-0.375784-2.9350.002348
30.013320.1040.458743
40.0868830.67860.249986
50.0050910.03980.484205
6-0.014057-0.10980.456469
70.0212840.16620.434261
80.091990.71850.237607
90.3174522.47940.00797
100.1551051.21140.115206
110.294732.30190.012384
120.0108870.0850.466259
13-0.518357-4.04857.4e-05
140.0875030.68340.248464
15-0.072215-0.5640.287406
16-0.121677-0.95030.172849
170.0082560.06450.4744
18-0.124739-0.97420.166891
19-0.005248-0.0410.48372
20-0.070924-0.55390.290825
21-0.083571-0.65270.258198
220.0188730.14740.44165
23-0.057225-0.44690.328251
240.0933230.72890.234434
25-0.096-0.74980.228133
260.0747740.5840.280686
270.0144850.11310.455148
28-0.00477-0.03730.485201
290.0303440.2370.406728
30-0.022445-0.17530.430712
31-0.018997-0.14840.441269
32-0.027153-0.21210.416378
33-0.117495-0.91770.181204
34-0.04271-0.33360.369921
35-0.005243-0.0410.483734
36-0.049782-0.38880.349387


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')