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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 computationWed, 25 Nov 2009 10:53:25 -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/Nov/25/t1259171944jwht7oieysqxg3i.htm/, Retrieved Wed, 05 Nov 2025 00:39:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59524, Retrieved Wed, 05 Nov 2025 00:39:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact388

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-25 17:53:25] [7c5623390f136c6c339940134868d3e2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516

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=59524&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=59524&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59524&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
10.0091090.070.472227
20.081640.62710.266511
30.110670.85010.199361
40.0473490.36370.358694
5-0.000326-0.00250.499006
60.1247470.95820.170936
70.014160.10880.456878
80.112920.86740.19463
90.0116210.08930.464587
10-0.07886-0.60570.273508
110.2183961.67750.049364
12-0.167234-1.28450.101986
13-0.058576-0.44990.327206
140.0875140.67220.252037
15-0.056924-0.43720.331765
16-0.075307-0.57840.282583
17-0.017041-0.13090.448152
18-0.046904-0.36030.359965
190.0071580.0550.478169
200.0091590.07030.472077
21-0.051082-0.39240.348099
220.0267950.20580.418822
230.0068950.0530.478971
24-0.195327-1.50030.06943
25-0.104494-0.80260.212703
26-0.157307-1.20830.115876
270.008380.06440.474448
28-0.06052-0.46490.321871
290.072730.55870.289256
30-0.042574-0.3270.372406
31-0.002378-0.01830.492743
32-0.05545-0.42590.335857
33-0.048857-0.37530.354399
34-0.026353-0.20240.420141
35-0.008655-0.06650.473611
36-0.046052-0.35370.362401

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.009109 & 0.07 & 0.472227 \tabularnewline
2 & 0.08164 & 0.6271 & 0.266511 \tabularnewline
3 & 0.11067 & 0.8501 & 0.199361 \tabularnewline
4 & 0.047349 & 0.3637 & 0.358694 \tabularnewline
5 & -0.000326 & -0.0025 & 0.499006 \tabularnewline
6 & 0.124747 & 0.9582 & 0.170936 \tabularnewline
7 & 0.01416 & 0.1088 & 0.456878 \tabularnewline
8 & 0.11292 & 0.8674 & 0.19463 \tabularnewline
9 & 0.011621 & 0.0893 & 0.464587 \tabularnewline
10 & -0.07886 & -0.6057 & 0.273508 \tabularnewline
11 & 0.218396 & 1.6775 & 0.049364 \tabularnewline
12 & -0.167234 & -1.2845 & 0.101986 \tabularnewline
13 & -0.058576 & -0.4499 & 0.327206 \tabularnewline
14 & 0.087514 & 0.6722 & 0.252037 \tabularnewline
15 & -0.056924 & -0.4372 & 0.331765 \tabularnewline
16 & -0.075307 & -0.5784 & 0.282583 \tabularnewline
17 & -0.017041 & -0.1309 & 0.448152 \tabularnewline
18 & -0.046904 & -0.3603 & 0.359965 \tabularnewline
19 & 0.007158 & 0.055 & 0.478169 \tabularnewline
20 & 0.009159 & 0.0703 & 0.472077 \tabularnewline
21 & -0.051082 & -0.3924 & 0.348099 \tabularnewline
22 & 0.026795 & 0.2058 & 0.418822 \tabularnewline
23 & 0.006895 & 0.053 & 0.478971 \tabularnewline
24 & -0.195327 & -1.5003 & 0.06943 \tabularnewline
25 & -0.104494 & -0.8026 & 0.212703 \tabularnewline
26 & -0.157307 & -1.2083 & 0.115876 \tabularnewline
27 & 0.00838 & 0.0644 & 0.474448 \tabularnewline
28 & -0.06052 & -0.4649 & 0.321871 \tabularnewline
29 & 0.07273 & 0.5587 & 0.289256 \tabularnewline
30 & -0.042574 & -0.327 & 0.372406 \tabularnewline
31 & -0.002378 & -0.0183 & 0.492743 \tabularnewline
32 & -0.05545 & -0.4259 & 0.335857 \tabularnewline
33 & -0.048857 & -0.3753 & 0.354399 \tabularnewline
34 & -0.026353 & -0.2024 & 0.420141 \tabularnewline
35 & -0.008655 & -0.0665 & 0.473611 \tabularnewline
36 & -0.046052 & -0.3537 & 0.362401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59524&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]0.009109[/C][C]0.07[/C][C]0.472227[/C][/ROW]
[ROW][C]2[/C][C]0.08164[/C][C]0.6271[/C][C]0.266511[/C][/ROW]
[ROW][C]3[/C][C]0.11067[/C][C]0.8501[/C][C]0.199361[/C][/ROW]
[ROW][C]4[/C][C]0.047349[/C][C]0.3637[/C][C]0.358694[/C][/ROW]
[ROW][C]5[/C][C]-0.000326[/C][C]-0.0025[/C][C]0.499006[/C][/ROW]
[ROW][C]6[/C][C]0.124747[/C][C]0.9582[/C][C]0.170936[/C][/ROW]
[ROW][C]7[/C][C]0.01416[/C][C]0.1088[/C][C]0.456878[/C][/ROW]
[ROW][C]8[/C][C]0.11292[/C][C]0.8674[/C][C]0.19463[/C][/ROW]
[ROW][C]9[/C][C]0.011621[/C][C]0.0893[/C][C]0.464587[/C][/ROW]
[ROW][C]10[/C][C]-0.07886[/C][C]-0.6057[/C][C]0.273508[/C][/ROW]
[ROW][C]11[/C][C]0.218396[/C][C]1.6775[/C][C]0.049364[/C][/ROW]
[ROW][C]12[/C][C]-0.167234[/C][C]-1.2845[/C][C]0.101986[/C][/ROW]
[ROW][C]13[/C][C]-0.058576[/C][C]-0.4499[/C][C]0.327206[/C][/ROW]
[ROW][C]14[/C][C]0.087514[/C][C]0.6722[/C][C]0.252037[/C][/ROW]
[ROW][C]15[/C][C]-0.056924[/C][C]-0.4372[/C][C]0.331765[/C][/ROW]
[ROW][C]16[/C][C]-0.075307[/C][C]-0.5784[/C][C]0.282583[/C][/ROW]
[ROW][C]17[/C][C]-0.017041[/C][C]-0.1309[/C][C]0.448152[/C][/ROW]
[ROW][C]18[/C][C]-0.046904[/C][C]-0.3603[/C][C]0.359965[/C][/ROW]
[ROW][C]19[/C][C]0.007158[/C][C]0.055[/C][C]0.478169[/C][/ROW]
[ROW][C]20[/C][C]0.009159[/C][C]0.0703[/C][C]0.472077[/C][/ROW]
[ROW][C]21[/C][C]-0.051082[/C][C]-0.3924[/C][C]0.348099[/C][/ROW]
[ROW][C]22[/C][C]0.026795[/C][C]0.2058[/C][C]0.418822[/C][/ROW]
[ROW][C]23[/C][C]0.006895[/C][C]0.053[/C][C]0.478971[/C][/ROW]
[ROW][C]24[/C][C]-0.195327[/C][C]-1.5003[/C][C]0.06943[/C][/ROW]
[ROW][C]25[/C][C]-0.104494[/C][C]-0.8026[/C][C]0.212703[/C][/ROW]
[ROW][C]26[/C][C]-0.157307[/C][C]-1.2083[/C][C]0.115876[/C][/ROW]
[ROW][C]27[/C][C]0.00838[/C][C]0.0644[/C][C]0.474448[/C][/ROW]
[ROW][C]28[/C][C]-0.06052[/C][C]-0.4649[/C][C]0.321871[/C][/ROW]
[ROW][C]29[/C][C]0.07273[/C][C]0.5587[/C][C]0.289256[/C][/ROW]
[ROW][C]30[/C][C]-0.042574[/C][C]-0.327[/C][C]0.372406[/C][/ROW]
[ROW][C]31[/C][C]-0.002378[/C][C]-0.0183[/C][C]0.492743[/C][/ROW]
[ROW][C]32[/C][C]-0.05545[/C][C]-0.4259[/C][C]0.335857[/C][/ROW]
[ROW][C]33[/C][C]-0.048857[/C][C]-0.3753[/C][C]0.354399[/C][/ROW]
[ROW][C]34[/C][C]-0.026353[/C][C]-0.2024[/C][C]0.420141[/C][/ROW]
[ROW][C]35[/C][C]-0.008655[/C][C]-0.0665[/C][C]0.473611[/C][/ROW]
[ROW][C]36[/C][C]-0.046052[/C][C]-0.3537[/C][C]0.362401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59524&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59524&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
10.0091090.070.472227
20.081640.62710.266511
30.110670.85010.199361
40.0473490.36370.358694
5-0.000326-0.00250.499006
60.1247470.95820.170936
70.014160.10880.456878
80.112920.86740.19463
90.0116210.08930.464587
10-0.07886-0.60570.273508
110.2183961.67750.049364
12-0.167234-1.28450.101986
13-0.058576-0.44990.327206
140.0875140.67220.252037
15-0.056924-0.43720.331765
16-0.075307-0.57840.282583
17-0.017041-0.13090.448152
18-0.046904-0.36030.359965
190.0071580.0550.478169
200.0091590.07030.472077
21-0.051082-0.39240.348099
220.0267950.20580.418822
230.0068950.0530.478971
24-0.195327-1.50030.06943
25-0.104494-0.80260.212703
26-0.157307-1.20830.115876
270.008380.06440.474448
28-0.06052-0.46490.321871
290.072730.55870.289256
30-0.042574-0.3270.372406
31-0.002378-0.01830.492743
32-0.05545-0.42590.335857
33-0.048857-0.37530.354399
34-0.026353-0.20240.420141
35-0.008655-0.06650.473611
36-0.046052-0.35370.362401






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0091090.070.472227
20.0815640.62650.266701
30.1099850.84480.200815
40.0405910.31180.378152
5-0.018374-0.14110.444124
60.1077460.82760.205613
70.0069370.05330.478842
80.0984830.75650.226191
9-0.01327-0.10190.45958
10-0.109235-0.8390.202415
110.2095271.60940.056433
12-0.195501-1.50170.069258
13-0.064977-0.49910.309783
140.0713120.54780.292964
15-0.057294-0.44010.330743
16-0.036017-0.27670.391506
17-0.079334-0.60940.272308
180.0218230.16760.433725
190.0136750.1050.458349
200.030160.23170.408802
210.013060.10030.460218
22-0.06241-0.47940.316721
230.1157410.8890.188801
24-0.210498-1.61690.055621
25-0.17491-1.34350.092126
26-0.103164-0.79240.215645
270.0770040.59150.278231
28-0.020199-0.15510.438617
290.081050.62260.267986
300.0125240.09620.461843
310.0008590.00660.497379
320.0383080.29420.3848
33-0.063182-0.48530.314628
34-0.061851-0.47510.318239
350.0846440.65020.259056
36-0.066789-0.5130.304929

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.009109 & 0.07 & 0.472227 \tabularnewline
2 & 0.081564 & 0.6265 & 0.266701 \tabularnewline
3 & 0.109985 & 0.8448 & 0.200815 \tabularnewline
4 & 0.040591 & 0.3118 & 0.378152 \tabularnewline
5 & -0.018374 & -0.1411 & 0.444124 \tabularnewline
6 & 0.107746 & 0.8276 & 0.205613 \tabularnewline
7 & 0.006937 & 0.0533 & 0.478842 \tabularnewline
8 & 0.098483 & 0.7565 & 0.226191 \tabularnewline
9 & -0.01327 & -0.1019 & 0.45958 \tabularnewline
10 & -0.109235 & -0.839 & 0.202415 \tabularnewline
11 & 0.209527 & 1.6094 & 0.056433 \tabularnewline
12 & -0.195501 & -1.5017 & 0.069258 \tabularnewline
13 & -0.064977 & -0.4991 & 0.309783 \tabularnewline
14 & 0.071312 & 0.5478 & 0.292964 \tabularnewline
15 & -0.057294 & -0.4401 & 0.330743 \tabularnewline
16 & -0.036017 & -0.2767 & 0.391506 \tabularnewline
17 & -0.079334 & -0.6094 & 0.272308 \tabularnewline
18 & 0.021823 & 0.1676 & 0.433725 \tabularnewline
19 & 0.013675 & 0.105 & 0.458349 \tabularnewline
20 & 0.03016 & 0.2317 & 0.408802 \tabularnewline
21 & 0.01306 & 0.1003 & 0.460218 \tabularnewline
22 & -0.06241 & -0.4794 & 0.316721 \tabularnewline
23 & 0.115741 & 0.889 & 0.188801 \tabularnewline
24 & -0.210498 & -1.6169 & 0.055621 \tabularnewline
25 & -0.17491 & -1.3435 & 0.092126 \tabularnewline
26 & -0.103164 & -0.7924 & 0.215645 \tabularnewline
27 & 0.077004 & 0.5915 & 0.278231 \tabularnewline
28 & -0.020199 & -0.1551 & 0.438617 \tabularnewline
29 & 0.08105 & 0.6226 & 0.267986 \tabularnewline
30 & 0.012524 & 0.0962 & 0.461843 \tabularnewline
31 & 0.000859 & 0.0066 & 0.497379 \tabularnewline
32 & 0.038308 & 0.2942 & 0.3848 \tabularnewline
33 & -0.063182 & -0.4853 & 0.314628 \tabularnewline
34 & -0.061851 & -0.4751 & 0.318239 \tabularnewline
35 & 0.084644 & 0.6502 & 0.259056 \tabularnewline
36 & -0.066789 & -0.513 & 0.304929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59524&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]0.009109[/C][C]0.07[/C][C]0.472227[/C][/ROW]
[ROW][C]2[/C][C]0.081564[/C][C]0.6265[/C][C]0.266701[/C][/ROW]
[ROW][C]3[/C][C]0.109985[/C][C]0.8448[/C][C]0.200815[/C][/ROW]
[ROW][C]4[/C][C]0.040591[/C][C]0.3118[/C][C]0.378152[/C][/ROW]
[ROW][C]5[/C][C]-0.018374[/C][C]-0.1411[/C][C]0.444124[/C][/ROW]
[ROW][C]6[/C][C]0.107746[/C][C]0.8276[/C][C]0.205613[/C][/ROW]
[ROW][C]7[/C][C]0.006937[/C][C]0.0533[/C][C]0.478842[/C][/ROW]
[ROW][C]8[/C][C]0.098483[/C][C]0.7565[/C][C]0.226191[/C][/ROW]
[ROW][C]9[/C][C]-0.01327[/C][C]-0.1019[/C][C]0.45958[/C][/ROW]
[ROW][C]10[/C][C]-0.109235[/C][C]-0.839[/C][C]0.202415[/C][/ROW]
[ROW][C]11[/C][C]0.209527[/C][C]1.6094[/C][C]0.056433[/C][/ROW]
[ROW][C]12[/C][C]-0.195501[/C][C]-1.5017[/C][C]0.069258[/C][/ROW]
[ROW][C]13[/C][C]-0.064977[/C][C]-0.4991[/C][C]0.309783[/C][/ROW]
[ROW][C]14[/C][C]0.071312[/C][C]0.5478[/C][C]0.292964[/C][/ROW]
[ROW][C]15[/C][C]-0.057294[/C][C]-0.4401[/C][C]0.330743[/C][/ROW]
[ROW][C]16[/C][C]-0.036017[/C][C]-0.2767[/C][C]0.391506[/C][/ROW]
[ROW][C]17[/C][C]-0.079334[/C][C]-0.6094[/C][C]0.272308[/C][/ROW]
[ROW][C]18[/C][C]0.021823[/C][C]0.1676[/C][C]0.433725[/C][/ROW]
[ROW][C]19[/C][C]0.013675[/C][C]0.105[/C][C]0.458349[/C][/ROW]
[ROW][C]20[/C][C]0.03016[/C][C]0.2317[/C][C]0.408802[/C][/ROW]
[ROW][C]21[/C][C]0.01306[/C][C]0.1003[/C][C]0.460218[/C][/ROW]
[ROW][C]22[/C][C]-0.06241[/C][C]-0.4794[/C][C]0.316721[/C][/ROW]
[ROW][C]23[/C][C]0.115741[/C][C]0.889[/C][C]0.188801[/C][/ROW]
[ROW][C]24[/C][C]-0.210498[/C][C]-1.6169[/C][C]0.055621[/C][/ROW]
[ROW][C]25[/C][C]-0.17491[/C][C]-1.3435[/C][C]0.092126[/C][/ROW]
[ROW][C]26[/C][C]-0.103164[/C][C]-0.7924[/C][C]0.215645[/C][/ROW]
[ROW][C]27[/C][C]0.077004[/C][C]0.5915[/C][C]0.278231[/C][/ROW]
[ROW][C]28[/C][C]-0.020199[/C][C]-0.1551[/C][C]0.438617[/C][/ROW]
[ROW][C]29[/C][C]0.08105[/C][C]0.6226[/C][C]0.267986[/C][/ROW]
[ROW][C]30[/C][C]0.012524[/C][C]0.0962[/C][C]0.461843[/C][/ROW]
[ROW][C]31[/C][C]0.000859[/C][C]0.0066[/C][C]0.497379[/C][/ROW]
[ROW][C]32[/C][C]0.038308[/C][C]0.2942[/C][C]0.3848[/C][/ROW]
[ROW][C]33[/C][C]-0.063182[/C][C]-0.4853[/C][C]0.314628[/C][/ROW]
[ROW][C]34[/C][C]-0.061851[/C][C]-0.4751[/C][C]0.318239[/C][/ROW]
[ROW][C]35[/C][C]0.084644[/C][C]0.6502[/C][C]0.259056[/C][/ROW]
[ROW][C]36[/C][C]-0.066789[/C][C]-0.513[/C][C]0.304929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59524&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59524&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
10.0091090.070.472227
20.0815640.62650.266701
30.1099850.84480.200815
40.0405910.31180.378152
5-0.018374-0.14110.444124
60.1077460.82760.205613
70.0069370.05330.478842
80.0984830.75650.226191
9-0.01327-0.10190.45958
10-0.109235-0.8390.202415
110.2095271.60940.056433
12-0.195501-1.50170.069258
13-0.064977-0.49910.309783
140.0713120.54780.292964
15-0.057294-0.44010.330743
16-0.036017-0.27670.391506
17-0.079334-0.60940.272308
180.0218230.16760.433725
190.0136750.1050.458349
200.030160.23170.408802
210.013060.10030.460218
22-0.06241-0.47940.316721
230.1157410.8890.188801
24-0.210498-1.61690.055621
25-0.17491-1.34350.092126
26-0.103164-0.79240.215645
270.0770040.59150.278231
28-0.020199-0.15510.438617
290.081050.62260.267986
300.0125240.09620.461843
310.0008590.00660.497379
320.0383080.29420.3848
33-0.063182-0.48530.314628
34-0.061851-0.47510.318239
350.0846440.65020.259056
36-0.066789-0.5130.304929


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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')