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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, 29 Dec 2009 02:16:06 -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/29/t1262078246mxgpcvek4l0q6v4.htm/, Retrieved Fri, 03 May 2024 14:22:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71065, Retrieved Fri, 03 May 2024 14:22:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149
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 12:16:10] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-27 16:22:38] [9b30bff5dd5a100f8196daf92e735633]
-   PD            [(Partial) Autocorrelation Function] [] [2009-12-29 09:16:06] [54e293c1fb7c46e2abc5c1dda68d8adb] [Current]
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Dataseries X:
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523




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=71065&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=71065&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71065&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
10.9424997.36120
20.872446.8140
30.7946276.20620
40.706375.51690
50.6172714.8215e-06
60.5288314.13035.6e-05
70.4344473.39310.000609
80.3510042.74140.004008
90.2702392.11060.019456
100.1939311.51460.067513
110.1278750.99870.160933
120.0624620.48780.313704
130.0045320.03540.485939
14-0.041011-0.32030.374916
15-0.098438-0.76880.222482
16-0.162592-1.26990.104474
17-0.211222-1.64970.052073
18-0.265826-2.07620.02105
19-0.313527-2.44870.008613
20-0.365183-2.85220.00296
21-0.415762-3.24720.000948
22-0.460123-3.59370.000326
23-0.492802-3.84890.000143
24-0.517687-4.04337.5e-05
25-0.515691-4.02777.9e-05
26-0.514539-4.01878.2e-05
27-0.500947-3.91250.000116
28-0.467883-3.65430.000269
29-0.44023-3.43830.00053
30-0.415458-3.24480.000955
31-0.38207-2.98410.002044
32-0.350236-2.73540.004073
33-0.312914-2.44390.008717
34-0.265301-2.07210.021247
35-0.226459-1.76870.040971
36-0.188778-1.47440.072758

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.942499 & 7.3612 & 0 \tabularnewline
2 & 0.87244 & 6.814 & 0 \tabularnewline
3 & 0.794627 & 6.2062 & 0 \tabularnewline
4 & 0.70637 & 5.5169 & 0 \tabularnewline
5 & 0.617271 & 4.821 & 5e-06 \tabularnewline
6 & 0.528831 & 4.1303 & 5.6e-05 \tabularnewline
7 & 0.434447 & 3.3931 & 0.000609 \tabularnewline
8 & 0.351004 & 2.7414 & 0.004008 \tabularnewline
9 & 0.270239 & 2.1106 & 0.019456 \tabularnewline
10 & 0.193931 & 1.5146 & 0.067513 \tabularnewline
11 & 0.127875 & 0.9987 & 0.160933 \tabularnewline
12 & 0.062462 & 0.4878 & 0.313704 \tabularnewline
13 & 0.004532 & 0.0354 & 0.485939 \tabularnewline
14 & -0.041011 & -0.3203 & 0.374916 \tabularnewline
15 & -0.098438 & -0.7688 & 0.222482 \tabularnewline
16 & -0.162592 & -1.2699 & 0.104474 \tabularnewline
17 & -0.211222 & -1.6497 & 0.052073 \tabularnewline
18 & -0.265826 & -2.0762 & 0.02105 \tabularnewline
19 & -0.313527 & -2.4487 & 0.008613 \tabularnewline
20 & -0.365183 & -2.8522 & 0.00296 \tabularnewline
21 & -0.415762 & -3.2472 & 0.000948 \tabularnewline
22 & -0.460123 & -3.5937 & 0.000326 \tabularnewline
23 & -0.492802 & -3.8489 & 0.000143 \tabularnewline
24 & -0.517687 & -4.0433 & 7.5e-05 \tabularnewline
25 & -0.515691 & -4.0277 & 7.9e-05 \tabularnewline
26 & -0.514539 & -4.0187 & 8.2e-05 \tabularnewline
27 & -0.500947 & -3.9125 & 0.000116 \tabularnewline
28 & -0.467883 & -3.6543 & 0.000269 \tabularnewline
29 & -0.44023 & -3.4383 & 0.00053 \tabularnewline
30 & -0.415458 & -3.2448 & 0.000955 \tabularnewline
31 & -0.38207 & -2.9841 & 0.002044 \tabularnewline
32 & -0.350236 & -2.7354 & 0.004073 \tabularnewline
33 & -0.312914 & -2.4439 & 0.008717 \tabularnewline
34 & -0.265301 & -2.0721 & 0.021247 \tabularnewline
35 & -0.226459 & -1.7687 & 0.040971 \tabularnewline
36 & -0.188778 & -1.4744 & 0.072758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71065&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]0.942499[/C][C]7.3612[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.87244[/C][C]6.814[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.794627[/C][C]6.2062[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.70637[/C][C]5.5169[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.617271[/C][C]4.821[/C][C]5e-06[/C][/ROW]
[ROW][C]6[/C][C]0.528831[/C][C]4.1303[/C][C]5.6e-05[/C][/ROW]
[ROW][C]7[/C][C]0.434447[/C][C]3.3931[/C][C]0.000609[/C][/ROW]
[ROW][C]8[/C][C]0.351004[/C][C]2.7414[/C][C]0.004008[/C][/ROW]
[ROW][C]9[/C][C]0.270239[/C][C]2.1106[/C][C]0.019456[/C][/ROW]
[ROW][C]10[/C][C]0.193931[/C][C]1.5146[/C][C]0.067513[/C][/ROW]
[ROW][C]11[/C][C]0.127875[/C][C]0.9987[/C][C]0.160933[/C][/ROW]
[ROW][C]12[/C][C]0.062462[/C][C]0.4878[/C][C]0.313704[/C][/ROW]
[ROW][C]13[/C][C]0.004532[/C][C]0.0354[/C][C]0.485939[/C][/ROW]
[ROW][C]14[/C][C]-0.041011[/C][C]-0.3203[/C][C]0.374916[/C][/ROW]
[ROW][C]15[/C][C]-0.098438[/C][C]-0.7688[/C][C]0.222482[/C][/ROW]
[ROW][C]16[/C][C]-0.162592[/C][C]-1.2699[/C][C]0.104474[/C][/ROW]
[ROW][C]17[/C][C]-0.211222[/C][C]-1.6497[/C][C]0.052073[/C][/ROW]
[ROW][C]18[/C][C]-0.265826[/C][C]-2.0762[/C][C]0.02105[/C][/ROW]
[ROW][C]19[/C][C]-0.313527[/C][C]-2.4487[/C][C]0.008613[/C][/ROW]
[ROW][C]20[/C][C]-0.365183[/C][C]-2.8522[/C][C]0.00296[/C][/ROW]
[ROW][C]21[/C][C]-0.415762[/C][C]-3.2472[/C][C]0.000948[/C][/ROW]
[ROW][C]22[/C][C]-0.460123[/C][C]-3.5937[/C][C]0.000326[/C][/ROW]
[ROW][C]23[/C][C]-0.492802[/C][C]-3.8489[/C][C]0.000143[/C][/ROW]
[ROW][C]24[/C][C]-0.517687[/C][C]-4.0433[/C][C]7.5e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.515691[/C][C]-4.0277[/C][C]7.9e-05[/C][/ROW]
[ROW][C]26[/C][C]-0.514539[/C][C]-4.0187[/C][C]8.2e-05[/C][/ROW]
[ROW][C]27[/C][C]-0.500947[/C][C]-3.9125[/C][C]0.000116[/C][/ROW]
[ROW][C]28[/C][C]-0.467883[/C][C]-3.6543[/C][C]0.000269[/C][/ROW]
[ROW][C]29[/C][C]-0.44023[/C][C]-3.4383[/C][C]0.00053[/C][/ROW]
[ROW][C]30[/C][C]-0.415458[/C][C]-3.2448[/C][C]0.000955[/C][/ROW]
[ROW][C]31[/C][C]-0.38207[/C][C]-2.9841[/C][C]0.002044[/C][/ROW]
[ROW][C]32[/C][C]-0.350236[/C][C]-2.7354[/C][C]0.004073[/C][/ROW]
[ROW][C]33[/C][C]-0.312914[/C][C]-2.4439[/C][C]0.008717[/C][/ROW]
[ROW][C]34[/C][C]-0.265301[/C][C]-2.0721[/C][C]0.021247[/C][/ROW]
[ROW][C]35[/C][C]-0.226459[/C][C]-1.7687[/C][C]0.040971[/C][/ROW]
[ROW][C]36[/C][C]-0.188778[/C][C]-1.4744[/C][C]0.072758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71065&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71065&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
10.9424997.36120
20.872446.8140
30.7946276.20620
40.706375.51690
50.6172714.8215e-06
60.5288314.13035.6e-05
70.4344473.39310.000609
80.3510042.74140.004008
90.2702392.11060.019456
100.1939311.51460.067513
110.1278750.99870.160933
120.0624620.48780.313704
130.0045320.03540.485939
14-0.041011-0.32030.374916
15-0.098438-0.76880.222482
16-0.162592-1.26990.104474
17-0.211222-1.64970.052073
18-0.265826-2.07620.02105
19-0.313527-2.44870.008613
20-0.365183-2.85220.00296
21-0.415762-3.24720.000948
22-0.460123-3.59370.000326
23-0.492802-3.84890.000143
24-0.517687-4.04337.5e-05
25-0.515691-4.02777.9e-05
26-0.514539-4.01878.2e-05
27-0.500947-3.91250.000116
28-0.467883-3.65430.000269
29-0.44023-3.43830.00053
30-0.415458-3.24480.000955
31-0.38207-2.98410.002044
32-0.350236-2.73540.004073
33-0.312914-2.44390.008717
34-0.265301-2.07210.021247
35-0.226459-1.76870.040971
36-0.188778-1.47440.072758







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9424997.36120
2-0.142035-1.10930.135821
3-0.096586-0.75440.226767
4-0.127196-0.99340.162211
5-0.040753-0.31830.375675
6-0.040897-0.31940.375251
7-0.109236-0.85320.198454
80.0442480.34560.36542
9-0.051843-0.40490.343481
10-0.025273-0.19740.422089
110.0088440.06910.472579
12-0.075843-0.59230.277903
130.0017550.01370.494553
140.0221250.17280.431689
15-0.183853-1.43590.078064
16-0.132836-1.03750.151803
170.0773390.6040.274031
18-0.11966-0.93460.176846
19-0.01392-0.10870.456892
20-0.146699-1.14580.128186
21-0.036477-0.28490.388346
22-0.047039-0.36740.357302
23-0.00372-0.02910.488458
24-0.003245-0.02530.489931
250.1260640.98460.164356
26-0.111761-0.87290.193076
270.0409490.31980.375097
280.0569810.4450.328934
29-0.119744-0.93520.176679
30-0.043947-0.34320.3663
31-0.01101-0.0860.465876
32-0.02087-0.1630.435529
330.0271440.2120.416407
340.0700880.54740.293049
35-0.050091-0.39120.348499
36-0.05019-0.3920.348213

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.942499 & 7.3612 & 0 \tabularnewline
2 & -0.142035 & -1.1093 & 0.135821 \tabularnewline
3 & -0.096586 & -0.7544 & 0.226767 \tabularnewline
4 & -0.127196 & -0.9934 & 0.162211 \tabularnewline
5 & -0.040753 & -0.3183 & 0.375675 \tabularnewline
6 & -0.040897 & -0.3194 & 0.375251 \tabularnewline
7 & -0.109236 & -0.8532 & 0.198454 \tabularnewline
8 & 0.044248 & 0.3456 & 0.36542 \tabularnewline
9 & -0.051843 & -0.4049 & 0.343481 \tabularnewline
10 & -0.025273 & -0.1974 & 0.422089 \tabularnewline
11 & 0.008844 & 0.0691 & 0.472579 \tabularnewline
12 & -0.075843 & -0.5923 & 0.277903 \tabularnewline
13 & 0.001755 & 0.0137 & 0.494553 \tabularnewline
14 & 0.022125 & 0.1728 & 0.431689 \tabularnewline
15 & -0.183853 & -1.4359 & 0.078064 \tabularnewline
16 & -0.132836 & -1.0375 & 0.151803 \tabularnewline
17 & 0.077339 & 0.604 & 0.274031 \tabularnewline
18 & -0.11966 & -0.9346 & 0.176846 \tabularnewline
19 & -0.01392 & -0.1087 & 0.456892 \tabularnewline
20 & -0.146699 & -1.1458 & 0.128186 \tabularnewline
21 & -0.036477 & -0.2849 & 0.388346 \tabularnewline
22 & -0.047039 & -0.3674 & 0.357302 \tabularnewline
23 & -0.00372 & -0.0291 & 0.488458 \tabularnewline
24 & -0.003245 & -0.0253 & 0.489931 \tabularnewline
25 & 0.126064 & 0.9846 & 0.164356 \tabularnewline
26 & -0.111761 & -0.8729 & 0.193076 \tabularnewline
27 & 0.040949 & 0.3198 & 0.375097 \tabularnewline
28 & 0.056981 & 0.445 & 0.328934 \tabularnewline
29 & -0.119744 & -0.9352 & 0.176679 \tabularnewline
30 & -0.043947 & -0.3432 & 0.3663 \tabularnewline
31 & -0.01101 & -0.086 & 0.465876 \tabularnewline
32 & -0.02087 & -0.163 & 0.435529 \tabularnewline
33 & 0.027144 & 0.212 & 0.416407 \tabularnewline
34 & 0.070088 & 0.5474 & 0.293049 \tabularnewline
35 & -0.050091 & -0.3912 & 0.348499 \tabularnewline
36 & -0.05019 & -0.392 & 0.348213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71065&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]0.942499[/C][C]7.3612[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.142035[/C][C]-1.1093[/C][C]0.135821[/C][/ROW]
[ROW][C]3[/C][C]-0.096586[/C][C]-0.7544[/C][C]0.226767[/C][/ROW]
[ROW][C]4[/C][C]-0.127196[/C][C]-0.9934[/C][C]0.162211[/C][/ROW]
[ROW][C]5[/C][C]-0.040753[/C][C]-0.3183[/C][C]0.375675[/C][/ROW]
[ROW][C]6[/C][C]-0.040897[/C][C]-0.3194[/C][C]0.375251[/C][/ROW]
[ROW][C]7[/C][C]-0.109236[/C][C]-0.8532[/C][C]0.198454[/C][/ROW]
[ROW][C]8[/C][C]0.044248[/C][C]0.3456[/C][C]0.36542[/C][/ROW]
[ROW][C]9[/C][C]-0.051843[/C][C]-0.4049[/C][C]0.343481[/C][/ROW]
[ROW][C]10[/C][C]-0.025273[/C][C]-0.1974[/C][C]0.422089[/C][/ROW]
[ROW][C]11[/C][C]0.008844[/C][C]0.0691[/C][C]0.472579[/C][/ROW]
[ROW][C]12[/C][C]-0.075843[/C][C]-0.5923[/C][C]0.277903[/C][/ROW]
[ROW][C]13[/C][C]0.001755[/C][C]0.0137[/C][C]0.494553[/C][/ROW]
[ROW][C]14[/C][C]0.022125[/C][C]0.1728[/C][C]0.431689[/C][/ROW]
[ROW][C]15[/C][C]-0.183853[/C][C]-1.4359[/C][C]0.078064[/C][/ROW]
[ROW][C]16[/C][C]-0.132836[/C][C]-1.0375[/C][C]0.151803[/C][/ROW]
[ROW][C]17[/C][C]0.077339[/C][C]0.604[/C][C]0.274031[/C][/ROW]
[ROW][C]18[/C][C]-0.11966[/C][C]-0.9346[/C][C]0.176846[/C][/ROW]
[ROW][C]19[/C][C]-0.01392[/C][C]-0.1087[/C][C]0.456892[/C][/ROW]
[ROW][C]20[/C][C]-0.146699[/C][C]-1.1458[/C][C]0.128186[/C][/ROW]
[ROW][C]21[/C][C]-0.036477[/C][C]-0.2849[/C][C]0.388346[/C][/ROW]
[ROW][C]22[/C][C]-0.047039[/C][C]-0.3674[/C][C]0.357302[/C][/ROW]
[ROW][C]23[/C][C]-0.00372[/C][C]-0.0291[/C][C]0.488458[/C][/ROW]
[ROW][C]24[/C][C]-0.003245[/C][C]-0.0253[/C][C]0.489931[/C][/ROW]
[ROW][C]25[/C][C]0.126064[/C][C]0.9846[/C][C]0.164356[/C][/ROW]
[ROW][C]26[/C][C]-0.111761[/C][C]-0.8729[/C][C]0.193076[/C][/ROW]
[ROW][C]27[/C][C]0.040949[/C][C]0.3198[/C][C]0.375097[/C][/ROW]
[ROW][C]28[/C][C]0.056981[/C][C]0.445[/C][C]0.328934[/C][/ROW]
[ROW][C]29[/C][C]-0.119744[/C][C]-0.9352[/C][C]0.176679[/C][/ROW]
[ROW][C]30[/C][C]-0.043947[/C][C]-0.3432[/C][C]0.3663[/C][/ROW]
[ROW][C]31[/C][C]-0.01101[/C][C]-0.086[/C][C]0.465876[/C][/ROW]
[ROW][C]32[/C][C]-0.02087[/C][C]-0.163[/C][C]0.435529[/C][/ROW]
[ROW][C]33[/C][C]0.027144[/C][C]0.212[/C][C]0.416407[/C][/ROW]
[ROW][C]34[/C][C]0.070088[/C][C]0.5474[/C][C]0.293049[/C][/ROW]
[ROW][C]35[/C][C]-0.050091[/C][C]-0.3912[/C][C]0.348499[/C][/ROW]
[ROW][C]36[/C][C]-0.05019[/C][C]-0.392[/C][C]0.348213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71065&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71065&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
10.9424997.36120
2-0.142035-1.10930.135821
3-0.096586-0.75440.226767
4-0.127196-0.99340.162211
5-0.040753-0.31830.375675
6-0.040897-0.31940.375251
7-0.109236-0.85320.198454
80.0442480.34560.36542
9-0.051843-0.40490.343481
10-0.025273-0.19740.422089
110.0088440.06910.472579
12-0.075843-0.59230.277903
130.0017550.01370.494553
140.0221250.17280.431689
15-0.183853-1.43590.078064
16-0.132836-1.03750.151803
170.0773390.6040.274031
18-0.11966-0.93460.176846
19-0.01392-0.10870.456892
20-0.146699-1.14580.128186
21-0.036477-0.28490.388346
22-0.047039-0.36740.357302
23-0.00372-0.02910.488458
24-0.003245-0.02530.489931
250.1260640.98460.164356
26-0.111761-0.87290.193076
270.0409490.31980.375097
280.0569810.4450.328934
29-0.119744-0.93520.176679
30-0.043947-0.34320.3663
31-0.01101-0.0860.465876
32-0.02087-0.1630.435529
330.0271440.2120.416407
340.0700880.54740.293049
35-0.050091-0.39120.348499
36-0.05019-0.3920.348213



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')