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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 computationMon, 23 Nov 2009 14:12:39 -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/23/t1259010845cd4gch12enqksq1.htm/, Retrieved Mon, 30 Dec 2024 17:43:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58910, Retrieved Mon, 30 Dec 2024 17:43:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact289

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       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD        [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:04:43] [0df1a6455bedfaf424729b1e006090d0]
-   PD            [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:12:39] [e339dd08bcbfc073ac7494f09a949034] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.6
23.7
22
21.3
20.7
20.4
20.3
20.4
19.8
19.5
23.1
23.5
23.5
22.9
21.9
21.5
20.5
20.2
19.4
19.2
18.8
18.8
22.6
23.3
23
21.4
19.9
18.8
18.6
18.4
18.6
19.9
19.2
18.4
21.1
20.5
19.1
18.1
17
17.1
17.4
16.8
15.3
14.3
13.4
15.3
22.1
23.7
22.2
19.5
16.6
17.3
19.8
21.2
21.5
20.6
19.1
19.6
23.5
24

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=58910&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=58910&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58910&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
10.6140684.20985.7e-05
2-0.010503-0.0720.471452
3-0.518978-3.55790.000433
4-0.640176-4.38883.2e-05
5-0.322877-2.21350.015875
60.1439970.98720.164301
70.4579743.13970.001461
80.4632263.17570.00132
90.1869381.28160.103138
10-0.207014-1.41920.081217
11-0.446149-3.05860.001832
12-0.500137-3.42880.000636
13-0.25116-1.72190.045835
140.0922640.63250.265052
150.3079492.11120.020051
160.2776071.90320.031576
170.1333570.91420.182627
18-0.059635-0.40880.342258
19-0.226463-1.55260.063619
20-0.212526-1.4570.075882
21-0.125656-0.86150.196682
220.0372960.25570.399654
230.1741061.19360.11931
240.2061561.41330.082073
250.128470.88070.191468
260.0059030.04050.483945
27-0.155503-1.06610.145918
28-0.185372-1.27080.105018
29-0.134003-0.91870.181476
30-0.053294-0.36540.358239
310.0904810.62030.269027
320.1569431.07590.143722
330.1306770.89590.187442
340.0324550.22250.412444
35-0.058755-0.40280.34446
36-0.081589-0.55930.28929

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.614068 & 4.2098 & 5.7e-05 \tabularnewline
2 & -0.010503 & -0.072 & 0.471452 \tabularnewline
3 & -0.518978 & -3.5579 & 0.000433 \tabularnewline
4 & -0.640176 & -4.3888 & 3.2e-05 \tabularnewline
5 & -0.322877 & -2.2135 & 0.015875 \tabularnewline
6 & 0.143997 & 0.9872 & 0.164301 \tabularnewline
7 & 0.457974 & 3.1397 & 0.001461 \tabularnewline
8 & 0.463226 & 3.1757 & 0.00132 \tabularnewline
9 & 0.186938 & 1.2816 & 0.103138 \tabularnewline
10 & -0.207014 & -1.4192 & 0.081217 \tabularnewline
11 & -0.446149 & -3.0586 & 0.001832 \tabularnewline
12 & -0.500137 & -3.4288 & 0.000636 \tabularnewline
13 & -0.25116 & -1.7219 & 0.045835 \tabularnewline
14 & 0.092264 & 0.6325 & 0.265052 \tabularnewline
15 & 0.307949 & 2.1112 & 0.020051 \tabularnewline
16 & 0.277607 & 1.9032 & 0.031576 \tabularnewline
17 & 0.133357 & 0.9142 & 0.182627 \tabularnewline
18 & -0.059635 & -0.4088 & 0.342258 \tabularnewline
19 & -0.226463 & -1.5526 & 0.063619 \tabularnewline
20 & -0.212526 & -1.457 & 0.075882 \tabularnewline
21 & -0.125656 & -0.8615 & 0.196682 \tabularnewline
22 & 0.037296 & 0.2557 & 0.399654 \tabularnewline
23 & 0.174106 & 1.1936 & 0.11931 \tabularnewline
24 & 0.206156 & 1.4133 & 0.082073 \tabularnewline
25 & 0.12847 & 0.8807 & 0.191468 \tabularnewline
26 & 0.005903 & 0.0405 & 0.483945 \tabularnewline
27 & -0.155503 & -1.0661 & 0.145918 \tabularnewline
28 & -0.185372 & -1.2708 & 0.105018 \tabularnewline
29 & -0.134003 & -0.9187 & 0.181476 \tabularnewline
30 & -0.053294 & -0.3654 & 0.358239 \tabularnewline
31 & 0.090481 & 0.6203 & 0.269027 \tabularnewline
32 & 0.156943 & 1.0759 & 0.143722 \tabularnewline
33 & 0.130677 & 0.8959 & 0.187442 \tabularnewline
34 & 0.032455 & 0.2225 & 0.412444 \tabularnewline
35 & -0.058755 & -0.4028 & 0.34446 \tabularnewline
36 & -0.081589 & -0.5593 & 0.28929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58910&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]0.614068[/C][C]4.2098[/C][C]5.7e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.010503[/C][C]-0.072[/C][C]0.471452[/C][/ROW]
[ROW][C]3[/C][C]-0.518978[/C][C]-3.5579[/C][C]0.000433[/C][/ROW]
[ROW][C]4[/C][C]-0.640176[/C][C]-4.3888[/C][C]3.2e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.322877[/C][C]-2.2135[/C][C]0.015875[/C][/ROW]
[ROW][C]6[/C][C]0.143997[/C][C]0.9872[/C][C]0.164301[/C][/ROW]
[ROW][C]7[/C][C]0.457974[/C][C]3.1397[/C][C]0.001461[/C][/ROW]
[ROW][C]8[/C][C]0.463226[/C][C]3.1757[/C][C]0.00132[/C][/ROW]
[ROW][C]9[/C][C]0.186938[/C][C]1.2816[/C][C]0.103138[/C][/ROW]
[ROW][C]10[/C][C]-0.207014[/C][C]-1.4192[/C][C]0.081217[/C][/ROW]
[ROW][C]11[/C][C]-0.446149[/C][C]-3.0586[/C][C]0.001832[/C][/ROW]
[ROW][C]12[/C][C]-0.500137[/C][C]-3.4288[/C][C]0.000636[/C][/ROW]
[ROW][C]13[/C][C]-0.25116[/C][C]-1.7219[/C][C]0.045835[/C][/ROW]
[ROW][C]14[/C][C]0.092264[/C][C]0.6325[/C][C]0.265052[/C][/ROW]
[ROW][C]15[/C][C]0.307949[/C][C]2.1112[/C][C]0.020051[/C][/ROW]
[ROW][C]16[/C][C]0.277607[/C][C]1.9032[/C][C]0.031576[/C][/ROW]
[ROW][C]17[/C][C]0.133357[/C][C]0.9142[/C][C]0.182627[/C][/ROW]
[ROW][C]18[/C][C]-0.059635[/C][C]-0.4088[/C][C]0.342258[/C][/ROW]
[ROW][C]19[/C][C]-0.226463[/C][C]-1.5526[/C][C]0.063619[/C][/ROW]
[ROW][C]20[/C][C]-0.212526[/C][C]-1.457[/C][C]0.075882[/C][/ROW]
[ROW][C]21[/C][C]-0.125656[/C][C]-0.8615[/C][C]0.196682[/C][/ROW]
[ROW][C]22[/C][C]0.037296[/C][C]0.2557[/C][C]0.399654[/C][/ROW]
[ROW][C]23[/C][C]0.174106[/C][C]1.1936[/C][C]0.11931[/C][/ROW]
[ROW][C]24[/C][C]0.206156[/C][C]1.4133[/C][C]0.082073[/C][/ROW]
[ROW][C]25[/C][C]0.12847[/C][C]0.8807[/C][C]0.191468[/C][/ROW]
[ROW][C]26[/C][C]0.005903[/C][C]0.0405[/C][C]0.483945[/C][/ROW]
[ROW][C]27[/C][C]-0.155503[/C][C]-1.0661[/C][C]0.145918[/C][/ROW]
[ROW][C]28[/C][C]-0.185372[/C][C]-1.2708[/C][C]0.105018[/C][/ROW]
[ROW][C]29[/C][C]-0.134003[/C][C]-0.9187[/C][C]0.181476[/C][/ROW]
[ROW][C]30[/C][C]-0.053294[/C][C]-0.3654[/C][C]0.358239[/C][/ROW]
[ROW][C]31[/C][C]0.090481[/C][C]0.6203[/C][C]0.269027[/C][/ROW]
[ROW][C]32[/C][C]0.156943[/C][C]1.0759[/C][C]0.143722[/C][/ROW]
[ROW][C]33[/C][C]0.130677[/C][C]0.8959[/C][C]0.187442[/C][/ROW]
[ROW][C]34[/C][C]0.032455[/C][C]0.2225[/C][C]0.412444[/C][/ROW]
[ROW][C]35[/C][C]-0.058755[/C][C]-0.4028[/C][C]0.34446[/C][/ROW]
[ROW][C]36[/C][C]-0.081589[/C][C]-0.5593[/C][C]0.28929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58910&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58910&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
10.6140684.20985.7e-05
2-0.010503-0.0720.471452
3-0.518978-3.55790.000433
4-0.640176-4.38883.2e-05
5-0.322877-2.21350.015875
60.1439970.98720.164301
70.4579743.13970.001461
80.4632263.17570.00132
90.1869381.28160.103138
10-0.207014-1.41920.081217
11-0.446149-3.05860.001832
12-0.500137-3.42880.000636
13-0.25116-1.72190.045835
140.0922640.63250.265052
150.3079492.11120.020051
160.2776071.90320.031576
170.1333570.91420.182627
18-0.059635-0.40880.342258
19-0.226463-1.55260.063619
20-0.212526-1.4570.075882
21-0.125656-0.86150.196682
220.0372960.25570.399654
230.1741061.19360.11931
240.2061561.41330.082073
250.128470.88070.191468
260.0059030.04050.483945
27-0.155503-1.06610.145918
28-0.185372-1.27080.105018
29-0.134003-0.91870.181476
30-0.053294-0.36540.358239
310.0904810.62030.269027
320.1569431.07590.143722
330.1306770.89590.187442
340.0324550.22250.412444
35-0.058755-0.40280.34446
36-0.081589-0.55930.28929






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6140684.20985.7e-05
2-0.622202-4.26564.8e-05
3-0.331202-2.27060.013898
4-0.087786-0.60180.275089
50.1495761.02540.155202
60.0312490.21420.415646
70.0252630.17320.431622
80.0563760.38650.350437
90.0077470.05310.478934
10-0.144839-0.9930.162905
11-0.04888-0.33510.369519
12-0.329399-2.25820.014307
130.0589310.4040.34402
14-0.126481-0.86710.195145
15-0.122246-0.83810.203114
16-0.201806-1.38350.086522
170.2609581.7890.040027
18-0.009736-0.06670.473532
19-0.161941-1.11020.136278
200.0811870.55660.290225
21-0.07692-0.52730.300221
22-0.057437-0.39380.347766
23-0.037841-0.25940.39822
24-0.133531-0.91540.182316
25-0.044555-0.30550.380685
260.0260710.17870.429459
27-0.17898-1.2270.112962
28-0.04173-0.28610.388035
29-0.075897-0.52030.30264
30-0.041459-0.28420.388741
31-0.077689-0.53260.298406
32-0.061449-0.42130.337737
33-0.089243-0.61180.271804
34-0.033004-0.22630.410989
35-0.000805-0.00550.497811
360.1009810.69230.24608

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.614068 & 4.2098 & 5.7e-05 \tabularnewline
2 & -0.622202 & -4.2656 & 4.8e-05 \tabularnewline
3 & -0.331202 & -2.2706 & 0.013898 \tabularnewline
4 & -0.087786 & -0.6018 & 0.275089 \tabularnewline
5 & 0.149576 & 1.0254 & 0.155202 \tabularnewline
6 & 0.031249 & 0.2142 & 0.415646 \tabularnewline
7 & 0.025263 & 0.1732 & 0.431622 \tabularnewline
8 & 0.056376 & 0.3865 & 0.350437 \tabularnewline
9 & 0.007747 & 0.0531 & 0.478934 \tabularnewline
10 & -0.144839 & -0.993 & 0.162905 \tabularnewline
11 & -0.04888 & -0.3351 & 0.369519 \tabularnewline
12 & -0.329399 & -2.2582 & 0.014307 \tabularnewline
13 & 0.058931 & 0.404 & 0.34402 \tabularnewline
14 & -0.126481 & -0.8671 & 0.195145 \tabularnewline
15 & -0.122246 & -0.8381 & 0.203114 \tabularnewline
16 & -0.201806 & -1.3835 & 0.086522 \tabularnewline
17 & 0.260958 & 1.789 & 0.040027 \tabularnewline
18 & -0.009736 & -0.0667 & 0.473532 \tabularnewline
19 & -0.161941 & -1.1102 & 0.136278 \tabularnewline
20 & 0.081187 & 0.5566 & 0.290225 \tabularnewline
21 & -0.07692 & -0.5273 & 0.300221 \tabularnewline
22 & -0.057437 & -0.3938 & 0.347766 \tabularnewline
23 & -0.037841 & -0.2594 & 0.39822 \tabularnewline
24 & -0.133531 & -0.9154 & 0.182316 \tabularnewline
25 & -0.044555 & -0.3055 & 0.380685 \tabularnewline
26 & 0.026071 & 0.1787 & 0.429459 \tabularnewline
27 & -0.17898 & -1.227 & 0.112962 \tabularnewline
28 & -0.04173 & -0.2861 & 0.388035 \tabularnewline
29 & -0.075897 & -0.5203 & 0.30264 \tabularnewline
30 & -0.041459 & -0.2842 & 0.388741 \tabularnewline
31 & -0.077689 & -0.5326 & 0.298406 \tabularnewline
32 & -0.061449 & -0.4213 & 0.337737 \tabularnewline
33 & -0.089243 & -0.6118 & 0.271804 \tabularnewline
34 & -0.033004 & -0.2263 & 0.410989 \tabularnewline
35 & -0.000805 & -0.0055 & 0.497811 \tabularnewline
36 & 0.100981 & 0.6923 & 0.24608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58910&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]0.614068[/C][C]4.2098[/C][C]5.7e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.622202[/C][C]-4.2656[/C][C]4.8e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.331202[/C][C]-2.2706[/C][C]0.013898[/C][/ROW]
[ROW][C]4[/C][C]-0.087786[/C][C]-0.6018[/C][C]0.275089[/C][/ROW]
[ROW][C]5[/C][C]0.149576[/C][C]1.0254[/C][C]0.155202[/C][/ROW]
[ROW][C]6[/C][C]0.031249[/C][C]0.2142[/C][C]0.415646[/C][/ROW]
[ROW][C]7[/C][C]0.025263[/C][C]0.1732[/C][C]0.431622[/C][/ROW]
[ROW][C]8[/C][C]0.056376[/C][C]0.3865[/C][C]0.350437[/C][/ROW]
[ROW][C]9[/C][C]0.007747[/C][C]0.0531[/C][C]0.478934[/C][/ROW]
[ROW][C]10[/C][C]-0.144839[/C][C]-0.993[/C][C]0.162905[/C][/ROW]
[ROW][C]11[/C][C]-0.04888[/C][C]-0.3351[/C][C]0.369519[/C][/ROW]
[ROW][C]12[/C][C]-0.329399[/C][C]-2.2582[/C][C]0.014307[/C][/ROW]
[ROW][C]13[/C][C]0.058931[/C][C]0.404[/C][C]0.34402[/C][/ROW]
[ROW][C]14[/C][C]-0.126481[/C][C]-0.8671[/C][C]0.195145[/C][/ROW]
[ROW][C]15[/C][C]-0.122246[/C][C]-0.8381[/C][C]0.203114[/C][/ROW]
[ROW][C]16[/C][C]-0.201806[/C][C]-1.3835[/C][C]0.086522[/C][/ROW]
[ROW][C]17[/C][C]0.260958[/C][C]1.789[/C][C]0.040027[/C][/ROW]
[ROW][C]18[/C][C]-0.009736[/C][C]-0.0667[/C][C]0.473532[/C][/ROW]
[ROW][C]19[/C][C]-0.161941[/C][C]-1.1102[/C][C]0.136278[/C][/ROW]
[ROW][C]20[/C][C]0.081187[/C][C]0.5566[/C][C]0.290225[/C][/ROW]
[ROW][C]21[/C][C]-0.07692[/C][C]-0.5273[/C][C]0.300221[/C][/ROW]
[ROW][C]22[/C][C]-0.057437[/C][C]-0.3938[/C][C]0.347766[/C][/ROW]
[ROW][C]23[/C][C]-0.037841[/C][C]-0.2594[/C][C]0.39822[/C][/ROW]
[ROW][C]24[/C][C]-0.133531[/C][C]-0.9154[/C][C]0.182316[/C][/ROW]
[ROW][C]25[/C][C]-0.044555[/C][C]-0.3055[/C][C]0.380685[/C][/ROW]
[ROW][C]26[/C][C]0.026071[/C][C]0.1787[/C][C]0.429459[/C][/ROW]
[ROW][C]27[/C][C]-0.17898[/C][C]-1.227[/C][C]0.112962[/C][/ROW]
[ROW][C]28[/C][C]-0.04173[/C][C]-0.2861[/C][C]0.388035[/C][/ROW]
[ROW][C]29[/C][C]-0.075897[/C][C]-0.5203[/C][C]0.30264[/C][/ROW]
[ROW][C]30[/C][C]-0.041459[/C][C]-0.2842[/C][C]0.388741[/C][/ROW]
[ROW][C]31[/C][C]-0.077689[/C][C]-0.5326[/C][C]0.298406[/C][/ROW]
[ROW][C]32[/C][C]-0.061449[/C][C]-0.4213[/C][C]0.337737[/C][/ROW]
[ROW][C]33[/C][C]-0.089243[/C][C]-0.6118[/C][C]0.271804[/C][/ROW]
[ROW][C]34[/C][C]-0.033004[/C][C]-0.2263[/C][C]0.410989[/C][/ROW]
[ROW][C]35[/C][C]-0.000805[/C][C]-0.0055[/C][C]0.497811[/C][/ROW]
[ROW][C]36[/C][C]0.100981[/C][C]0.6923[/C][C]0.24608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58910&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58910&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
10.6140684.20985.7e-05
2-0.622202-4.26564.8e-05
3-0.331202-2.27060.013898
4-0.087786-0.60180.275089
50.1495761.02540.155202
60.0312490.21420.415646
70.0252630.17320.431622
80.0563760.38650.350437
90.0077470.05310.478934
10-0.144839-0.9930.162905
11-0.04888-0.33510.369519
12-0.329399-2.25820.014307
130.0589310.4040.34402
14-0.126481-0.86710.195145
15-0.122246-0.83810.203114
16-0.201806-1.38350.086522
170.2609581.7890.040027
18-0.009736-0.06670.473532
19-0.161941-1.11020.136278
200.0811870.55660.290225
21-0.07692-0.52730.300221
22-0.057437-0.39380.347766
23-0.037841-0.25940.39822
24-0.133531-0.91540.182316
25-0.044555-0.30550.380685
260.0260710.17870.429459
27-0.17898-1.2270.112962
28-0.04173-0.28610.388035
29-0.075897-0.52030.30264
30-0.041459-0.28420.388741
31-0.077689-0.53260.298406
32-0.061449-0.42130.337737
33-0.089243-0.61180.271804
34-0.033004-0.22630.410989
35-0.000805-0.00550.497811
360.1009810.69230.24608


Figures (Output of Computation)

Input Parameters & R Code

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