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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 computationFri, 05 Dec 2008 06:24:16 -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/05/t1228483527shpz1wbvkd0bthi.htm/, Retrieved Fri, 09 May 2025 23:01:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29242, Retrieved Fri, 09 May 2025 23:01:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact328

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   [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-03 15:12:42] [6fea0e9a9b3b29a63badf2c274e82506]
-    D    [(Partial) Autocorrelation Function] [Taak 10 Stap 2 AC...] [2008-12-04 18:21:05] [819b576fab25b35cfda70f80599828ec]
-   P       [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:18:35] [6fea0e9a9b3b29a63badf2c274e82506]
-   P           [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:24:16] [286e96bd53289970f8e5f25a93fb50b3] [Current]
-   P             [(Partial) Autocorrelation Function] [Taak 10 deel 2 st...] [2008-12-05 13:28:10] [6fea0e9a9b3b29a63badf2c274e82506]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
58.972
59.249
63.955
53.785
52.760
44.795
37.348
32.370
32.717
40.974
33.591
21.124
58.608
46.865
51.378
46.235
47.206
45.382
41.227
33.795
31.295
42.625
33.625
21.538
56.421
53.152
53.536
52.408
41.454
38.271
35.306
26.414
31.917
38.030
27.534
18.387
50.556
43.901
48.572
43.899
37.532
40.357
35.489
29.027
34.485
42.598
30.306
26.451
47.460
50.104
61.465
53.726
39.477
43.895
31.481
29.896
33.842
39.120
33.702
25.094

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=29242&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=29242&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29242&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
1-0.277261-2.12970.01869
2-0.143529-1.10250.137367
30.1349551.03660.152073
4-0.089698-0.6890.246767
5-0.036615-0.28120.389753
6-0.074884-0.57520.283673
7-0.116684-0.89630.186876
80.0523790.40230.344446
90.0912380.70080.243088
10-0.172544-1.32530.095085
11-0.209298-1.60760.056626
120.6841925.25541e-06
13-0.1873-1.43870.077762
14-0.080116-0.61540.270335
150.102780.78950.216499
16-0.133505-1.02550.154664
170.0475170.3650.358213
18-0.09379-0.72040.237057
19-0.136577-1.04910.149212
200.1014730.77940.21942
210.0319830.24570.403395
22-0.141688-1.08830.140438
23-0.085184-0.65430.257728
240.4432713.40480.000598
25-0.119444-0.91750.181317
260.0028420.02180.491328
270.0093060.07150.47163
28-0.086095-0.66130.255494
290.0808560.62110.268473
30-0.11797-0.90610.184273
31-0.063657-0.4890.313341
320.0919250.70610.241456
330.0083390.06410.474572
34-0.063588-0.48840.313528
35-0.064047-0.4920.312288
360.2007941.54230.06417

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.277261 & -2.1297 & 0.01869 \tabularnewline
2 & -0.143529 & -1.1025 & 0.137367 \tabularnewline
3 & 0.134955 & 1.0366 & 0.152073 \tabularnewline
4 & -0.089698 & -0.689 & 0.246767 \tabularnewline
5 & -0.036615 & -0.2812 & 0.389753 \tabularnewline
6 & -0.074884 & -0.5752 & 0.283673 \tabularnewline
7 & -0.116684 & -0.8963 & 0.186876 \tabularnewline
8 & 0.052379 & 0.4023 & 0.344446 \tabularnewline
9 & 0.091238 & 0.7008 & 0.243088 \tabularnewline
10 & -0.172544 & -1.3253 & 0.095085 \tabularnewline
11 & -0.209298 & -1.6076 & 0.056626 \tabularnewline
12 & 0.684192 & 5.2554 & 1e-06 \tabularnewline
13 & -0.1873 & -1.4387 & 0.077762 \tabularnewline
14 & -0.080116 & -0.6154 & 0.270335 \tabularnewline
15 & 0.10278 & 0.7895 & 0.216499 \tabularnewline
16 & -0.133505 & -1.0255 & 0.154664 \tabularnewline
17 & 0.047517 & 0.365 & 0.358213 \tabularnewline
18 & -0.09379 & -0.7204 & 0.237057 \tabularnewline
19 & -0.136577 & -1.0491 & 0.149212 \tabularnewline
20 & 0.101473 & 0.7794 & 0.21942 \tabularnewline
21 & 0.031983 & 0.2457 & 0.403395 \tabularnewline
22 & -0.141688 & -1.0883 & 0.140438 \tabularnewline
23 & -0.085184 & -0.6543 & 0.257728 \tabularnewline
24 & 0.443271 & 3.4048 & 0.000598 \tabularnewline
25 & -0.119444 & -0.9175 & 0.181317 \tabularnewline
26 & 0.002842 & 0.0218 & 0.491328 \tabularnewline
27 & 0.009306 & 0.0715 & 0.47163 \tabularnewline
28 & -0.086095 & -0.6613 & 0.255494 \tabularnewline
29 & 0.080856 & 0.6211 & 0.268473 \tabularnewline
30 & -0.11797 & -0.9061 & 0.184273 \tabularnewline
31 & -0.063657 & -0.489 & 0.313341 \tabularnewline
32 & 0.091925 & 0.7061 & 0.241456 \tabularnewline
33 & 0.008339 & 0.0641 & 0.474572 \tabularnewline
34 & -0.063588 & -0.4884 & 0.313528 \tabularnewline
35 & -0.064047 & -0.492 & 0.312288 \tabularnewline
36 & 0.200794 & 1.5423 & 0.06417 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29242&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]-0.277261[/C][C]-2.1297[/C][C]0.01869[/C][/ROW]
[ROW][C]2[/C][C]-0.143529[/C][C]-1.1025[/C][C]0.137367[/C][/ROW]
[ROW][C]3[/C][C]0.134955[/C][C]1.0366[/C][C]0.152073[/C][/ROW]
[ROW][C]4[/C][C]-0.089698[/C][C]-0.689[/C][C]0.246767[/C][/ROW]
[ROW][C]5[/C][C]-0.036615[/C][C]-0.2812[/C][C]0.389753[/C][/ROW]
[ROW][C]6[/C][C]-0.074884[/C][C]-0.5752[/C][C]0.283673[/C][/ROW]
[ROW][C]7[/C][C]-0.116684[/C][C]-0.8963[/C][C]0.186876[/C][/ROW]
[ROW][C]8[/C][C]0.052379[/C][C]0.4023[/C][C]0.344446[/C][/ROW]
[ROW][C]9[/C][C]0.091238[/C][C]0.7008[/C][C]0.243088[/C][/ROW]
[ROW][C]10[/C][C]-0.172544[/C][C]-1.3253[/C][C]0.095085[/C][/ROW]
[ROW][C]11[/C][C]-0.209298[/C][C]-1.6076[/C][C]0.056626[/C][/ROW]
[ROW][C]12[/C][C]0.684192[/C][C]5.2554[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.1873[/C][C]-1.4387[/C][C]0.077762[/C][/ROW]
[ROW][C]14[/C][C]-0.080116[/C][C]-0.6154[/C][C]0.270335[/C][/ROW]
[ROW][C]15[/C][C]0.10278[/C][C]0.7895[/C][C]0.216499[/C][/ROW]
[ROW][C]16[/C][C]-0.133505[/C][C]-1.0255[/C][C]0.154664[/C][/ROW]
[ROW][C]17[/C][C]0.047517[/C][C]0.365[/C][C]0.358213[/C][/ROW]
[ROW][C]18[/C][C]-0.09379[/C][C]-0.7204[/C][C]0.237057[/C][/ROW]
[ROW][C]19[/C][C]-0.136577[/C][C]-1.0491[/C][C]0.149212[/C][/ROW]
[ROW][C]20[/C][C]0.101473[/C][C]0.7794[/C][C]0.21942[/C][/ROW]
[ROW][C]21[/C][C]0.031983[/C][C]0.2457[/C][C]0.403395[/C][/ROW]
[ROW][C]22[/C][C]-0.141688[/C][C]-1.0883[/C][C]0.140438[/C][/ROW]
[ROW][C]23[/C][C]-0.085184[/C][C]-0.6543[/C][C]0.257728[/C][/ROW]
[ROW][C]24[/C][C]0.443271[/C][C]3.4048[/C][C]0.000598[/C][/ROW]
[ROW][C]25[/C][C]-0.119444[/C][C]-0.9175[/C][C]0.181317[/C][/ROW]
[ROW][C]26[/C][C]0.002842[/C][C]0.0218[/C][C]0.491328[/C][/ROW]
[ROW][C]27[/C][C]0.009306[/C][C]0.0715[/C][C]0.47163[/C][/ROW]
[ROW][C]28[/C][C]-0.086095[/C][C]-0.6613[/C][C]0.255494[/C][/ROW]
[ROW][C]29[/C][C]0.080856[/C][C]0.6211[/C][C]0.268473[/C][/ROW]
[ROW][C]30[/C][C]-0.11797[/C][C]-0.9061[/C][C]0.184273[/C][/ROW]
[ROW][C]31[/C][C]-0.063657[/C][C]-0.489[/C][C]0.313341[/C][/ROW]
[ROW][C]32[/C][C]0.091925[/C][C]0.7061[/C][C]0.241456[/C][/ROW]
[ROW][C]33[/C][C]0.008339[/C][C]0.0641[/C][C]0.474572[/C][/ROW]
[ROW][C]34[/C][C]-0.063588[/C][C]-0.4884[/C][C]0.313528[/C][/ROW]
[ROW][C]35[/C][C]-0.064047[/C][C]-0.492[/C][C]0.312288[/C][/ROW]
[ROW][C]36[/C][C]0.200794[/C][C]1.5423[/C][C]0.06417[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29242&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29242&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
1-0.277261-2.12970.01869
2-0.143529-1.10250.137367
30.1349551.03660.152073
4-0.089698-0.6890.246767
5-0.036615-0.28120.389753
6-0.074884-0.57520.283673
7-0.116684-0.89630.186876
80.0523790.40230.344446
90.0912380.70080.243088
10-0.172544-1.32530.095085
11-0.209298-1.60760.056626
120.6841925.25541e-06
13-0.1873-1.43870.077762
14-0.080116-0.61540.270335
150.102780.78950.216499
16-0.133505-1.02550.154664
170.0475170.3650.358213
18-0.09379-0.72040.237057
19-0.136577-1.04910.149212
200.1014730.77940.21942
210.0319830.24570.403395
22-0.141688-1.08830.140438
23-0.085184-0.65430.257728
240.4432713.40480.000598
25-0.119444-0.91750.181317
260.0028420.02180.491328
270.0093060.07150.47163
28-0.086095-0.66130.255494
290.0808560.62110.268473
30-0.11797-0.90610.184273
31-0.063657-0.4890.313341
320.0919250.70610.241456
330.0083390.06410.474572
34-0.063588-0.48840.313528
35-0.064047-0.4920.312288
360.2007941.54230.06417






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.277261-2.12970.01869
2-0.238757-1.83390.035855
30.0223560.17170.432123
4-0.081643-0.62710.266503
5-0.065302-0.50160.30891
6-0.162573-1.24870.108345
7-0.236368-1.81560.037259
8-0.135242-1.03880.151564
90.006180.04750.481149
10-0.193628-1.48730.071133
11-0.485186-3.72680.000218
120.4835583.71430.000227
130.104440.80220.212823
140.056860.43680.331942
15-0.071526-0.54940.2924
16-0.07717-0.59280.277805
17-0.003057-0.02350.490672
18-0.048462-0.37220.355524
19-0.008624-0.06620.473703
20-0.094421-0.72530.235579
21-0.13857-1.06440.145747
22-0.090022-0.69150.24599
230.0818450.62870.265997
240.030670.23560.407287
25-0.038835-0.29830.383261
260.0184880.1420.443778
27-0.121991-0.9370.176281
280.0378830.2910.386042
290.009610.07380.470704
30-0.005472-0.0420.483308
310.0538260.41340.340391
32-0.034101-0.26190.397143
330.0609660.46830.320653
340.1157390.8890.188804
350.0484430.37210.355576
36-0.190394-1.46240.074463

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.277261 & -2.1297 & 0.01869 \tabularnewline
2 & -0.238757 & -1.8339 & 0.035855 \tabularnewline
3 & 0.022356 & 0.1717 & 0.432123 \tabularnewline
4 & -0.081643 & -0.6271 & 0.266503 \tabularnewline
5 & -0.065302 & -0.5016 & 0.30891 \tabularnewline
6 & -0.162573 & -1.2487 & 0.108345 \tabularnewline
7 & -0.236368 & -1.8156 & 0.037259 \tabularnewline
8 & -0.135242 & -1.0388 & 0.151564 \tabularnewline
9 & 0.00618 & 0.0475 & 0.481149 \tabularnewline
10 & -0.193628 & -1.4873 & 0.071133 \tabularnewline
11 & -0.485186 & -3.7268 & 0.000218 \tabularnewline
12 & 0.483558 & 3.7143 & 0.000227 \tabularnewline
13 & 0.10444 & 0.8022 & 0.212823 \tabularnewline
14 & 0.05686 & 0.4368 & 0.331942 \tabularnewline
15 & -0.071526 & -0.5494 & 0.2924 \tabularnewline
16 & -0.07717 & -0.5928 & 0.277805 \tabularnewline
17 & -0.003057 & -0.0235 & 0.490672 \tabularnewline
18 & -0.048462 & -0.3722 & 0.355524 \tabularnewline
19 & -0.008624 & -0.0662 & 0.473703 \tabularnewline
20 & -0.094421 & -0.7253 & 0.235579 \tabularnewline
21 & -0.13857 & -1.0644 & 0.145747 \tabularnewline
22 & -0.090022 & -0.6915 & 0.24599 \tabularnewline
23 & 0.081845 & 0.6287 & 0.265997 \tabularnewline
24 & 0.03067 & 0.2356 & 0.407287 \tabularnewline
25 & -0.038835 & -0.2983 & 0.383261 \tabularnewline
26 & 0.018488 & 0.142 & 0.443778 \tabularnewline
27 & -0.121991 & -0.937 & 0.176281 \tabularnewline
28 & 0.037883 & 0.291 & 0.386042 \tabularnewline
29 & 0.00961 & 0.0738 & 0.470704 \tabularnewline
30 & -0.005472 & -0.042 & 0.483308 \tabularnewline
31 & 0.053826 & 0.4134 & 0.340391 \tabularnewline
32 & -0.034101 & -0.2619 & 0.397143 \tabularnewline
33 & 0.060966 & 0.4683 & 0.320653 \tabularnewline
34 & 0.115739 & 0.889 & 0.188804 \tabularnewline
35 & 0.048443 & 0.3721 & 0.355576 \tabularnewline
36 & -0.190394 & -1.4624 & 0.074463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29242&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]-0.277261[/C][C]-2.1297[/C][C]0.01869[/C][/ROW]
[ROW][C]2[/C][C]-0.238757[/C][C]-1.8339[/C][C]0.035855[/C][/ROW]
[ROW][C]3[/C][C]0.022356[/C][C]0.1717[/C][C]0.432123[/C][/ROW]
[ROW][C]4[/C][C]-0.081643[/C][C]-0.6271[/C][C]0.266503[/C][/ROW]
[ROW][C]5[/C][C]-0.065302[/C][C]-0.5016[/C][C]0.30891[/C][/ROW]
[ROW][C]6[/C][C]-0.162573[/C][C]-1.2487[/C][C]0.108345[/C][/ROW]
[ROW][C]7[/C][C]-0.236368[/C][C]-1.8156[/C][C]0.037259[/C][/ROW]
[ROW][C]8[/C][C]-0.135242[/C][C]-1.0388[/C][C]0.151564[/C][/ROW]
[ROW][C]9[/C][C]0.00618[/C][C]0.0475[/C][C]0.481149[/C][/ROW]
[ROW][C]10[/C][C]-0.193628[/C][C]-1.4873[/C][C]0.071133[/C][/ROW]
[ROW][C]11[/C][C]-0.485186[/C][C]-3.7268[/C][C]0.000218[/C][/ROW]
[ROW][C]12[/C][C]0.483558[/C][C]3.7143[/C][C]0.000227[/C][/ROW]
[ROW][C]13[/C][C]0.10444[/C][C]0.8022[/C][C]0.212823[/C][/ROW]
[ROW][C]14[/C][C]0.05686[/C][C]0.4368[/C][C]0.331942[/C][/ROW]
[ROW][C]15[/C][C]-0.071526[/C][C]-0.5494[/C][C]0.2924[/C][/ROW]
[ROW][C]16[/C][C]-0.07717[/C][C]-0.5928[/C][C]0.277805[/C][/ROW]
[ROW][C]17[/C][C]-0.003057[/C][C]-0.0235[/C][C]0.490672[/C][/ROW]
[ROW][C]18[/C][C]-0.048462[/C][C]-0.3722[/C][C]0.355524[/C][/ROW]
[ROW][C]19[/C][C]-0.008624[/C][C]-0.0662[/C][C]0.473703[/C][/ROW]
[ROW][C]20[/C][C]-0.094421[/C][C]-0.7253[/C][C]0.235579[/C][/ROW]
[ROW][C]21[/C][C]-0.13857[/C][C]-1.0644[/C][C]0.145747[/C][/ROW]
[ROW][C]22[/C][C]-0.090022[/C][C]-0.6915[/C][C]0.24599[/C][/ROW]
[ROW][C]23[/C][C]0.081845[/C][C]0.6287[/C][C]0.265997[/C][/ROW]
[ROW][C]24[/C][C]0.03067[/C][C]0.2356[/C][C]0.407287[/C][/ROW]
[ROW][C]25[/C][C]-0.038835[/C][C]-0.2983[/C][C]0.383261[/C][/ROW]
[ROW][C]26[/C][C]0.018488[/C][C]0.142[/C][C]0.443778[/C][/ROW]
[ROW][C]27[/C][C]-0.121991[/C][C]-0.937[/C][C]0.176281[/C][/ROW]
[ROW][C]28[/C][C]0.037883[/C][C]0.291[/C][C]0.386042[/C][/ROW]
[ROW][C]29[/C][C]0.00961[/C][C]0.0738[/C][C]0.470704[/C][/ROW]
[ROW][C]30[/C][C]-0.005472[/C][C]-0.042[/C][C]0.483308[/C][/ROW]
[ROW][C]31[/C][C]0.053826[/C][C]0.4134[/C][C]0.340391[/C][/ROW]
[ROW][C]32[/C][C]-0.034101[/C][C]-0.2619[/C][C]0.397143[/C][/ROW]
[ROW][C]33[/C][C]0.060966[/C][C]0.4683[/C][C]0.320653[/C][/ROW]
[ROW][C]34[/C][C]0.115739[/C][C]0.889[/C][C]0.188804[/C][/ROW]
[ROW][C]35[/C][C]0.048443[/C][C]0.3721[/C][C]0.355576[/C][/ROW]
[ROW][C]36[/C][C]-0.190394[/C][C]-1.4624[/C][C]0.074463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29242&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29242&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
1-0.277261-2.12970.01869
2-0.238757-1.83390.035855
30.0223560.17170.432123
4-0.081643-0.62710.266503
5-0.065302-0.50160.30891
6-0.162573-1.24870.108345
7-0.236368-1.81560.037259
8-0.135242-1.03880.151564
90.006180.04750.481149
10-0.193628-1.48730.071133
11-0.485186-3.72680.000218
120.4835583.71430.000227
130.104440.80220.212823
140.056860.43680.331942
15-0.071526-0.54940.2924
16-0.07717-0.59280.277805
17-0.003057-0.02350.490672
18-0.048462-0.37220.355524
19-0.008624-0.06620.473703
20-0.094421-0.72530.235579
21-0.13857-1.06440.145747
22-0.090022-0.69150.24599
230.0818450.62870.265997
240.030670.23560.407287
25-0.038835-0.29830.383261
260.0184880.1420.443778
27-0.121991-0.9370.176281
280.0378830.2910.386042
290.009610.07380.470704
30-0.005472-0.0420.483308
310.0538260.41340.340391
32-0.034101-0.26190.397143
330.0609660.46830.320653
340.1157390.8890.188804
350.0484430.37210.355576
36-0.190394-1.46240.074463


Figures (Output of Computation)

Input Parameters & R Code

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