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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 computationTue, 01 Dec 2009 04:16:28 -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/01/t12596662554rs388k5jgu5bxi.htm/, Retrieved Fri, 19 Apr 2024 15:45:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61983, Retrieved Fri, 19 Apr 2024 15:45:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
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] [] [2009-12-01 11:16:28] [54f12ba6dfaf5b88c7c2745223d9c32f] [Current]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036




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=61983&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=61983&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61983&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
1-0.574021-3.97690.000117
20.3225682.23480.01506
3-0.132112-0.91530.182306
40.0046140.0320.487316
5-0.121875-0.84440.201325
60.1717971.19020.119902
7-0.216051-1.49680.07049
80.2245451.55570.063175
9-0.134734-0.93350.177627
100.0066310.04590.481775
110.0676170.46850.320786
12-0.144649-1.00220.160646
13-0.018805-0.13030.448443
14-0.068296-0.47320.319118
150.0916470.6350.264238
16-0.075974-0.52640.300529
170.1091670.75630.226573
18-0.062388-0.43220.333754
190.033410.23150.408965
20-0.107041-0.74160.230971
210.2436641.68820.048935
22-0.32643-2.26160.014146
230.32572.25650.014315
24-0.239968-1.66250.05146
250.1499241.03870.152074
260.0075920.05260.479134
270.0808830.56040.288915
28-0.154184-1.06820.145382
290.1768671.22540.113207
30-0.207527-1.43780.078491
310.1521021.05380.148627
32-0.052568-0.36420.358652
33-0.061359-0.42510.336328
340.09230.63950.262777
35-0.071608-0.49610.311038
36-0.020851-0.14450.44287

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.574021 & -3.9769 & 0.000117 \tabularnewline
2 & 0.322568 & 2.2348 & 0.01506 \tabularnewline
3 & -0.132112 & -0.9153 & 0.182306 \tabularnewline
4 & 0.004614 & 0.032 & 0.487316 \tabularnewline
5 & -0.121875 & -0.8444 & 0.201325 \tabularnewline
6 & 0.171797 & 1.1902 & 0.119902 \tabularnewline
7 & -0.216051 & -1.4968 & 0.07049 \tabularnewline
8 & 0.224545 & 1.5557 & 0.063175 \tabularnewline
9 & -0.134734 & -0.9335 & 0.177627 \tabularnewline
10 & 0.006631 & 0.0459 & 0.481775 \tabularnewline
11 & 0.067617 & 0.4685 & 0.320786 \tabularnewline
12 & -0.144649 & -1.0022 & 0.160646 \tabularnewline
13 & -0.018805 & -0.1303 & 0.448443 \tabularnewline
14 & -0.068296 & -0.4732 & 0.319118 \tabularnewline
15 & 0.091647 & 0.635 & 0.264238 \tabularnewline
16 & -0.075974 & -0.5264 & 0.300529 \tabularnewline
17 & 0.109167 & 0.7563 & 0.226573 \tabularnewline
18 & -0.062388 & -0.4322 & 0.333754 \tabularnewline
19 & 0.03341 & 0.2315 & 0.408965 \tabularnewline
20 & -0.107041 & -0.7416 & 0.230971 \tabularnewline
21 & 0.243664 & 1.6882 & 0.048935 \tabularnewline
22 & -0.32643 & -2.2616 & 0.014146 \tabularnewline
23 & 0.3257 & 2.2565 & 0.014315 \tabularnewline
24 & -0.239968 & -1.6625 & 0.05146 \tabularnewline
25 & 0.149924 & 1.0387 & 0.152074 \tabularnewline
26 & 0.007592 & 0.0526 & 0.479134 \tabularnewline
27 & 0.080883 & 0.5604 & 0.288915 \tabularnewline
28 & -0.154184 & -1.0682 & 0.145382 \tabularnewline
29 & 0.176867 & 1.2254 & 0.113207 \tabularnewline
30 & -0.207527 & -1.4378 & 0.078491 \tabularnewline
31 & 0.152102 & 1.0538 & 0.148627 \tabularnewline
32 & -0.052568 & -0.3642 & 0.358652 \tabularnewline
33 & -0.061359 & -0.4251 & 0.336328 \tabularnewline
34 & 0.0923 & 0.6395 & 0.262777 \tabularnewline
35 & -0.071608 & -0.4961 & 0.311038 \tabularnewline
36 & -0.020851 & -0.1445 & 0.44287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61983&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]-0.574021[/C][C]-3.9769[/C][C]0.000117[/C][/ROW]
[ROW][C]2[/C][C]0.322568[/C][C]2.2348[/C][C]0.01506[/C][/ROW]
[ROW][C]3[/C][C]-0.132112[/C][C]-0.9153[/C][C]0.182306[/C][/ROW]
[ROW][C]4[/C][C]0.004614[/C][C]0.032[/C][C]0.487316[/C][/ROW]
[ROW][C]5[/C][C]-0.121875[/C][C]-0.8444[/C][C]0.201325[/C][/ROW]
[ROW][C]6[/C][C]0.171797[/C][C]1.1902[/C][C]0.119902[/C][/ROW]
[ROW][C]7[/C][C]-0.216051[/C][C]-1.4968[/C][C]0.07049[/C][/ROW]
[ROW][C]8[/C][C]0.224545[/C][C]1.5557[/C][C]0.063175[/C][/ROW]
[ROW][C]9[/C][C]-0.134734[/C][C]-0.9335[/C][C]0.177627[/C][/ROW]
[ROW][C]10[/C][C]0.006631[/C][C]0.0459[/C][C]0.481775[/C][/ROW]
[ROW][C]11[/C][C]0.067617[/C][C]0.4685[/C][C]0.320786[/C][/ROW]
[ROW][C]12[/C][C]-0.144649[/C][C]-1.0022[/C][C]0.160646[/C][/ROW]
[ROW][C]13[/C][C]-0.018805[/C][C]-0.1303[/C][C]0.448443[/C][/ROW]
[ROW][C]14[/C][C]-0.068296[/C][C]-0.4732[/C][C]0.319118[/C][/ROW]
[ROW][C]15[/C][C]0.091647[/C][C]0.635[/C][C]0.264238[/C][/ROW]
[ROW][C]16[/C][C]-0.075974[/C][C]-0.5264[/C][C]0.300529[/C][/ROW]
[ROW][C]17[/C][C]0.109167[/C][C]0.7563[/C][C]0.226573[/C][/ROW]
[ROW][C]18[/C][C]-0.062388[/C][C]-0.4322[/C][C]0.333754[/C][/ROW]
[ROW][C]19[/C][C]0.03341[/C][C]0.2315[/C][C]0.408965[/C][/ROW]
[ROW][C]20[/C][C]-0.107041[/C][C]-0.7416[/C][C]0.230971[/C][/ROW]
[ROW][C]21[/C][C]0.243664[/C][C]1.6882[/C][C]0.048935[/C][/ROW]
[ROW][C]22[/C][C]-0.32643[/C][C]-2.2616[/C][C]0.014146[/C][/ROW]
[ROW][C]23[/C][C]0.3257[/C][C]2.2565[/C][C]0.014315[/C][/ROW]
[ROW][C]24[/C][C]-0.239968[/C][C]-1.6625[/C][C]0.05146[/C][/ROW]
[ROW][C]25[/C][C]0.149924[/C][C]1.0387[/C][C]0.152074[/C][/ROW]
[ROW][C]26[/C][C]0.007592[/C][C]0.0526[/C][C]0.479134[/C][/ROW]
[ROW][C]27[/C][C]0.080883[/C][C]0.5604[/C][C]0.288915[/C][/ROW]
[ROW][C]28[/C][C]-0.154184[/C][C]-1.0682[/C][C]0.145382[/C][/ROW]
[ROW][C]29[/C][C]0.176867[/C][C]1.2254[/C][C]0.113207[/C][/ROW]
[ROW][C]30[/C][C]-0.207527[/C][C]-1.4378[/C][C]0.078491[/C][/ROW]
[ROW][C]31[/C][C]0.152102[/C][C]1.0538[/C][C]0.148627[/C][/ROW]
[ROW][C]32[/C][C]-0.052568[/C][C]-0.3642[/C][C]0.358652[/C][/ROW]
[ROW][C]33[/C][C]-0.061359[/C][C]-0.4251[/C][C]0.336328[/C][/ROW]
[ROW][C]34[/C][C]0.0923[/C][C]0.6395[/C][C]0.262777[/C][/ROW]
[ROW][C]35[/C][C]-0.071608[/C][C]-0.4961[/C][C]0.311038[/C][/ROW]
[ROW][C]36[/C][C]-0.020851[/C][C]-0.1445[/C][C]0.44287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61983&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61983&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
1-0.574021-3.97690.000117
20.3225682.23480.01506
3-0.132112-0.91530.182306
40.0046140.0320.487316
5-0.121875-0.84440.201325
60.1717971.19020.119902
7-0.216051-1.49680.07049
80.2245451.55570.063175
9-0.134734-0.93350.177627
100.0066310.04590.481775
110.0676170.46850.320786
12-0.144649-1.00220.160646
13-0.018805-0.13030.448443
14-0.068296-0.47320.319118
150.0916470.6350.264238
16-0.075974-0.52640.300529
170.1091670.75630.226573
18-0.062388-0.43220.333754
190.033410.23150.408965
20-0.107041-0.74160.230971
210.2436641.68820.048935
22-0.32643-2.26160.014146
230.32572.25650.014315
24-0.239968-1.66250.05146
250.1499241.03870.152074
260.0075920.05260.479134
270.0808830.56040.288915
28-0.154184-1.06820.145382
290.1768671.22540.113207
30-0.207527-1.43780.078491
310.1521021.05380.148627
32-0.052568-0.36420.358652
33-0.061359-0.42510.336328
340.09230.63950.262777
35-0.071608-0.49610.311038
36-0.020851-0.14450.44287







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.574021-3.97690.000117
2-0.01034-0.07160.471595
30.073130.50670.307357
4-0.060393-0.41840.338755
5-0.243378-1.68620.049127
60.0492570.34130.367198
7-0.063977-0.44320.329791
80.0480530.33290.370322
90.0215550.14930.440957
10-0.122881-0.85130.199403
110.03650.25290.400719
12-0.109768-0.76050.22534
13-0.212272-1.47070.073954
14-0.298027-2.06480.022184
150.0125110.08670.465645
160.0028280.01960.492224
17-0.071842-0.49770.310471
18-0.065412-0.45320.326229
19-0.094603-0.65540.25766
20-0.168415-1.16680.124525
210.2105731.45890.075554
22-0.158702-1.09950.138512
23-0.084766-0.58730.279885
24-0.075248-0.52130.302266
25-0.060102-0.41640.339486
260.0240420.16660.434204
270.1153630.79930.214038
28-0.067855-0.47010.320201
29-0.10213-0.70760.241314
300.021150.14650.442058
310.0464050.32150.374611
32-0.037627-0.26070.397725
33-0.112726-0.7810.219322
34-0.004874-0.03380.486602
350.0056540.03920.484459
36-0.090598-0.62770.266595

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.574021 & -3.9769 & 0.000117 \tabularnewline
2 & -0.01034 & -0.0716 & 0.471595 \tabularnewline
3 & 0.07313 & 0.5067 & 0.307357 \tabularnewline
4 & -0.060393 & -0.4184 & 0.338755 \tabularnewline
5 & -0.243378 & -1.6862 & 0.049127 \tabularnewline
6 & 0.049257 & 0.3413 & 0.367198 \tabularnewline
7 & -0.063977 & -0.4432 & 0.329791 \tabularnewline
8 & 0.048053 & 0.3329 & 0.370322 \tabularnewline
9 & 0.021555 & 0.1493 & 0.440957 \tabularnewline
10 & -0.122881 & -0.8513 & 0.199403 \tabularnewline
11 & 0.0365 & 0.2529 & 0.400719 \tabularnewline
12 & -0.109768 & -0.7605 & 0.22534 \tabularnewline
13 & -0.212272 & -1.4707 & 0.073954 \tabularnewline
14 & -0.298027 & -2.0648 & 0.022184 \tabularnewline
15 & 0.012511 & 0.0867 & 0.465645 \tabularnewline
16 & 0.002828 & 0.0196 & 0.492224 \tabularnewline
17 & -0.071842 & -0.4977 & 0.310471 \tabularnewline
18 & -0.065412 & -0.4532 & 0.326229 \tabularnewline
19 & -0.094603 & -0.6554 & 0.25766 \tabularnewline
20 & -0.168415 & -1.1668 & 0.124525 \tabularnewline
21 & 0.210573 & 1.4589 & 0.075554 \tabularnewline
22 & -0.158702 & -1.0995 & 0.138512 \tabularnewline
23 & -0.084766 & -0.5873 & 0.279885 \tabularnewline
24 & -0.075248 & -0.5213 & 0.302266 \tabularnewline
25 & -0.060102 & -0.4164 & 0.339486 \tabularnewline
26 & 0.024042 & 0.1666 & 0.434204 \tabularnewline
27 & 0.115363 & 0.7993 & 0.214038 \tabularnewline
28 & -0.067855 & -0.4701 & 0.320201 \tabularnewline
29 & -0.10213 & -0.7076 & 0.241314 \tabularnewline
30 & 0.02115 & 0.1465 & 0.442058 \tabularnewline
31 & 0.046405 & 0.3215 & 0.374611 \tabularnewline
32 & -0.037627 & -0.2607 & 0.397725 \tabularnewline
33 & -0.112726 & -0.781 & 0.219322 \tabularnewline
34 & -0.004874 & -0.0338 & 0.486602 \tabularnewline
35 & 0.005654 & 0.0392 & 0.484459 \tabularnewline
36 & -0.090598 & -0.6277 & 0.266595 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61983&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]-0.574021[/C][C]-3.9769[/C][C]0.000117[/C][/ROW]
[ROW][C]2[/C][C]-0.01034[/C][C]-0.0716[/C][C]0.471595[/C][/ROW]
[ROW][C]3[/C][C]0.07313[/C][C]0.5067[/C][C]0.307357[/C][/ROW]
[ROW][C]4[/C][C]-0.060393[/C][C]-0.4184[/C][C]0.338755[/C][/ROW]
[ROW][C]5[/C][C]-0.243378[/C][C]-1.6862[/C][C]0.049127[/C][/ROW]
[ROW][C]6[/C][C]0.049257[/C][C]0.3413[/C][C]0.367198[/C][/ROW]
[ROW][C]7[/C][C]-0.063977[/C][C]-0.4432[/C][C]0.329791[/C][/ROW]
[ROW][C]8[/C][C]0.048053[/C][C]0.3329[/C][C]0.370322[/C][/ROW]
[ROW][C]9[/C][C]0.021555[/C][C]0.1493[/C][C]0.440957[/C][/ROW]
[ROW][C]10[/C][C]-0.122881[/C][C]-0.8513[/C][C]0.199403[/C][/ROW]
[ROW][C]11[/C][C]0.0365[/C][C]0.2529[/C][C]0.400719[/C][/ROW]
[ROW][C]12[/C][C]-0.109768[/C][C]-0.7605[/C][C]0.22534[/C][/ROW]
[ROW][C]13[/C][C]-0.212272[/C][C]-1.4707[/C][C]0.073954[/C][/ROW]
[ROW][C]14[/C][C]-0.298027[/C][C]-2.0648[/C][C]0.022184[/C][/ROW]
[ROW][C]15[/C][C]0.012511[/C][C]0.0867[/C][C]0.465645[/C][/ROW]
[ROW][C]16[/C][C]0.002828[/C][C]0.0196[/C][C]0.492224[/C][/ROW]
[ROW][C]17[/C][C]-0.071842[/C][C]-0.4977[/C][C]0.310471[/C][/ROW]
[ROW][C]18[/C][C]-0.065412[/C][C]-0.4532[/C][C]0.326229[/C][/ROW]
[ROW][C]19[/C][C]-0.094603[/C][C]-0.6554[/C][C]0.25766[/C][/ROW]
[ROW][C]20[/C][C]-0.168415[/C][C]-1.1668[/C][C]0.124525[/C][/ROW]
[ROW][C]21[/C][C]0.210573[/C][C]1.4589[/C][C]0.075554[/C][/ROW]
[ROW][C]22[/C][C]-0.158702[/C][C]-1.0995[/C][C]0.138512[/C][/ROW]
[ROW][C]23[/C][C]-0.084766[/C][C]-0.5873[/C][C]0.279885[/C][/ROW]
[ROW][C]24[/C][C]-0.075248[/C][C]-0.5213[/C][C]0.302266[/C][/ROW]
[ROW][C]25[/C][C]-0.060102[/C][C]-0.4164[/C][C]0.339486[/C][/ROW]
[ROW][C]26[/C][C]0.024042[/C][C]0.1666[/C][C]0.434204[/C][/ROW]
[ROW][C]27[/C][C]0.115363[/C][C]0.7993[/C][C]0.214038[/C][/ROW]
[ROW][C]28[/C][C]-0.067855[/C][C]-0.4701[/C][C]0.320201[/C][/ROW]
[ROW][C]29[/C][C]-0.10213[/C][C]-0.7076[/C][C]0.241314[/C][/ROW]
[ROW][C]30[/C][C]0.02115[/C][C]0.1465[/C][C]0.442058[/C][/ROW]
[ROW][C]31[/C][C]0.046405[/C][C]0.3215[/C][C]0.374611[/C][/ROW]
[ROW][C]32[/C][C]-0.037627[/C][C]-0.2607[/C][C]0.397725[/C][/ROW]
[ROW][C]33[/C][C]-0.112726[/C][C]-0.781[/C][C]0.219322[/C][/ROW]
[ROW][C]34[/C][C]-0.004874[/C][C]-0.0338[/C][C]0.486602[/C][/ROW]
[ROW][C]35[/C][C]0.005654[/C][C]0.0392[/C][C]0.484459[/C][/ROW]
[ROW][C]36[/C][C]-0.090598[/C][C]-0.6277[/C][C]0.266595[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61983&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61983&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
1-0.574021-3.97690.000117
2-0.01034-0.07160.471595
30.073130.50670.307357
4-0.060393-0.41840.338755
5-0.243378-1.68620.049127
60.0492570.34130.367198
7-0.063977-0.44320.329791
80.0480530.33290.370322
90.0215550.14930.440957
10-0.122881-0.85130.199403
110.03650.25290.400719
12-0.109768-0.76050.22534
13-0.212272-1.47070.073954
14-0.298027-2.06480.022184
150.0125110.08670.465645
160.0028280.01960.492224
17-0.071842-0.49770.310471
18-0.065412-0.45320.326229
19-0.094603-0.65540.25766
20-0.168415-1.16680.124525
210.2105731.45890.075554
22-0.158702-1.09950.138512
23-0.084766-0.58730.279885
24-0.075248-0.52130.302266
25-0.060102-0.41640.339486
260.0240420.16660.434204
270.1153630.79930.214038
28-0.067855-0.47010.320201
29-0.10213-0.70760.241314
300.021150.14650.442058
310.0464050.32150.374611
32-0.037627-0.26070.397725
33-0.112726-0.7810.219322
34-0.004874-0.03380.486602
350.0056540.03920.484459
36-0.090598-0.62770.266595



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')