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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 computationThu, 26 Nov 2009 02:50:36 -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/26/t1259229096k4dxjoqkbci9gqj.htm/, Retrieved Mon, 29 Apr 2024 07:52:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59743, Retrieved Mon, 29 Apr 2024 07:52:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-26 09:50:36] [830aa0f7fb5acd5849dbc0c6ad889830] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2009-12-15 15:25:00] [6ba840d2473f9a55d7b3e13093db69b8]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519164
517009
509933
509127
500857
506971
569323
579714
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

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=59743&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=59743&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59743&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
10.9583847.42360
20.91717.10380
30.87176.75220
40.8273536.40870
50.7810066.04960
60.7330475.67820
70.6857155.31151e-06
80.6349164.9184e-06
90.5747554.4521.9e-05
100.505643.91670.000116
110.4400643.40870.000586
120.3669272.84220.003057
130.3090582.3940.009905
140.2545241.97150.026639
150.1949121.50980.068174
160.13871.07440.14348
170.0818360.63390.264278
180.0289820.22450.411568
19-0.022852-0.1770.430047
20-0.071056-0.55040.292046
21-0.120478-0.93320.177224
22-0.158134-1.22490.112701
23-0.198569-1.53810.06464
24-0.241451-1.87030.033163
25-0.27476-2.12830.018715
26-0.303148-2.34820.01109
27-0.321295-2.48870.007806
28-0.345914-2.67940.004752
29-0.370639-2.8710.002823
30-0.399027-3.09080.001513
31-0.422448-3.27230.000886
32-0.444585-3.44370.000526
33-0.460851-3.56970.000355
34-0.463025-3.58660.000337
35-0.46123-3.57270.000352
36-0.452365-3.5040.000436

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958384 & 7.4236 & 0 \tabularnewline
2 & 0.9171 & 7.1038 & 0 \tabularnewline
3 & 0.8717 & 6.7522 & 0 \tabularnewline
4 & 0.827353 & 6.4087 & 0 \tabularnewline
5 & 0.781006 & 6.0496 & 0 \tabularnewline
6 & 0.733047 & 5.6782 & 0 \tabularnewline
7 & 0.685715 & 5.3115 & 1e-06 \tabularnewline
8 & 0.634916 & 4.918 & 4e-06 \tabularnewline
9 & 0.574755 & 4.452 & 1.9e-05 \tabularnewline
10 & 0.50564 & 3.9167 & 0.000116 \tabularnewline
11 & 0.440064 & 3.4087 & 0.000586 \tabularnewline
12 & 0.366927 & 2.8422 & 0.003057 \tabularnewline
13 & 0.309058 & 2.394 & 0.009905 \tabularnewline
14 & 0.254524 & 1.9715 & 0.026639 \tabularnewline
15 & 0.194912 & 1.5098 & 0.068174 \tabularnewline
16 & 0.1387 & 1.0744 & 0.14348 \tabularnewline
17 & 0.081836 & 0.6339 & 0.264278 \tabularnewline
18 & 0.028982 & 0.2245 & 0.411568 \tabularnewline
19 & -0.022852 & -0.177 & 0.430047 \tabularnewline
20 & -0.071056 & -0.5504 & 0.292046 \tabularnewline
21 & -0.120478 & -0.9332 & 0.177224 \tabularnewline
22 & -0.158134 & -1.2249 & 0.112701 \tabularnewline
23 & -0.198569 & -1.5381 & 0.06464 \tabularnewline
24 & -0.241451 & -1.8703 & 0.033163 \tabularnewline
25 & -0.27476 & -2.1283 & 0.018715 \tabularnewline
26 & -0.303148 & -2.3482 & 0.01109 \tabularnewline
27 & -0.321295 & -2.4887 & 0.007806 \tabularnewline
28 & -0.345914 & -2.6794 & 0.004752 \tabularnewline
29 & -0.370639 & -2.871 & 0.002823 \tabularnewline
30 & -0.399027 & -3.0908 & 0.001513 \tabularnewline
31 & -0.422448 & -3.2723 & 0.000886 \tabularnewline
32 & -0.444585 & -3.4437 & 0.000526 \tabularnewline
33 & -0.460851 & -3.5697 & 0.000355 \tabularnewline
34 & -0.463025 & -3.5866 & 0.000337 \tabularnewline
35 & -0.46123 & -3.5727 & 0.000352 \tabularnewline
36 & -0.452365 & -3.504 & 0.000436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59743&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]0.958384[/C][C]7.4236[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.9171[/C][C]7.1038[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.8717[/C][C]6.7522[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.827353[/C][C]6.4087[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.781006[/C][C]6.0496[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.733047[/C][C]5.6782[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.685715[/C][C]5.3115[/C][C]1e-06[/C][/ROW]
[ROW][C]8[/C][C]0.634916[/C][C]4.918[/C][C]4e-06[/C][/ROW]
[ROW][C]9[/C][C]0.574755[/C][C]4.452[/C][C]1.9e-05[/C][/ROW]
[ROW][C]10[/C][C]0.50564[/C][C]3.9167[/C][C]0.000116[/C][/ROW]
[ROW][C]11[/C][C]0.440064[/C][C]3.4087[/C][C]0.000586[/C][/ROW]
[ROW][C]12[/C][C]0.366927[/C][C]2.8422[/C][C]0.003057[/C][/ROW]
[ROW][C]13[/C][C]0.309058[/C][C]2.394[/C][C]0.009905[/C][/ROW]
[ROW][C]14[/C][C]0.254524[/C][C]1.9715[/C][C]0.026639[/C][/ROW]
[ROW][C]15[/C][C]0.194912[/C][C]1.5098[/C][C]0.068174[/C][/ROW]
[ROW][C]16[/C][C]0.1387[/C][C]1.0744[/C][C]0.14348[/C][/ROW]
[ROW][C]17[/C][C]0.081836[/C][C]0.6339[/C][C]0.264278[/C][/ROW]
[ROW][C]18[/C][C]0.028982[/C][C]0.2245[/C][C]0.411568[/C][/ROW]
[ROW][C]19[/C][C]-0.022852[/C][C]-0.177[/C][C]0.430047[/C][/ROW]
[ROW][C]20[/C][C]-0.071056[/C][C]-0.5504[/C][C]0.292046[/C][/ROW]
[ROW][C]21[/C][C]-0.120478[/C][C]-0.9332[/C][C]0.177224[/C][/ROW]
[ROW][C]22[/C][C]-0.158134[/C][C]-1.2249[/C][C]0.112701[/C][/ROW]
[ROW][C]23[/C][C]-0.198569[/C][C]-1.5381[/C][C]0.06464[/C][/ROW]
[ROW][C]24[/C][C]-0.241451[/C][C]-1.8703[/C][C]0.033163[/C][/ROW]
[ROW][C]25[/C][C]-0.27476[/C][C]-2.1283[/C][C]0.018715[/C][/ROW]
[ROW][C]26[/C][C]-0.303148[/C][C]-2.3482[/C][C]0.01109[/C][/ROW]
[ROW][C]27[/C][C]-0.321295[/C][C]-2.4887[/C][C]0.007806[/C][/ROW]
[ROW][C]28[/C][C]-0.345914[/C][C]-2.6794[/C][C]0.004752[/C][/ROW]
[ROW][C]29[/C][C]-0.370639[/C][C]-2.871[/C][C]0.002823[/C][/ROW]
[ROW][C]30[/C][C]-0.399027[/C][C]-3.0908[/C][C]0.001513[/C][/ROW]
[ROW][C]31[/C][C]-0.422448[/C][C]-3.2723[/C][C]0.000886[/C][/ROW]
[ROW][C]32[/C][C]-0.444585[/C][C]-3.4437[/C][C]0.000526[/C][/ROW]
[ROW][C]33[/C][C]-0.460851[/C][C]-3.5697[/C][C]0.000355[/C][/ROW]
[ROW][C]34[/C][C]-0.463025[/C][C]-3.5866[/C][C]0.000337[/C][/ROW]
[ROW][C]35[/C][C]-0.46123[/C][C]-3.5727[/C][C]0.000352[/C][/ROW]
[ROW][C]36[/C][C]-0.452365[/C][C]-3.504[/C][C]0.000436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59743&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59743&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
10.9583847.42360
20.91717.10380
30.87176.75220
40.8273536.40870
50.7810066.04960
60.7330475.67820
70.6857155.31151e-06
80.6349164.9184e-06
90.5747554.4521.9e-05
100.505643.91670.000116
110.4400643.40870.000586
120.3669272.84220.003057
130.3090582.3940.009905
140.2545241.97150.026639
150.1949121.50980.068174
160.13871.07440.14348
170.0818360.63390.264278
180.0289820.22450.411568
19-0.022852-0.1770.430047
20-0.071056-0.55040.292046
21-0.120478-0.93320.177224
22-0.158134-1.22490.112701
23-0.198569-1.53810.06464
24-0.241451-1.87030.033163
25-0.27476-2.12830.018715
26-0.303148-2.34820.01109
27-0.321295-2.48870.007806
28-0.345914-2.67940.004752
29-0.370639-2.8710.002823
30-0.399027-3.09080.001513
31-0.422448-3.27230.000886
32-0.444585-3.44370.000526
33-0.460851-3.56970.000355
34-0.463025-3.58660.000337
35-0.46123-3.57270.000352
36-0.452365-3.5040.000436






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9583847.42360
2-0.017189-0.13310.447262
3-0.072022-0.55790.289501
4-0.011765-0.09110.463847
5-0.04642-0.35960.360215
6-0.047427-0.36740.357318
7-0.017836-0.13820.44529
8-0.06968-0.53970.295688
9-0.149266-1.15620.12609
10-0.151151-1.17080.123152
116e-055e-040.499815
12-0.139135-1.07770.142733
130.1353671.04860.149295
140.0194520.15070.440368
15-0.12871-0.9970.161389
160.0047540.03680.485374
17-0.032773-0.25390.400236
180.0043830.0340.486514
19-0.014906-0.11550.454234
20-0.004092-0.03170.48741
21-0.099353-0.76960.222282
220.044320.34330.366286
23-0.052773-0.40880.34208
24-0.129591-1.00380.159752
250.0944650.73170.233593
260.039790.30820.379494
270.0201260.15590.438319
28-0.11705-0.90670.184106
29-0.07171-0.55550.290321
30-0.120701-0.93490.176782
31-0.002462-0.01910.492423
320.0130080.10080.460038
33-0.040475-0.31350.377488
340.1461431.1320.131066
350.0069440.05380.478643
36-0.027642-0.21410.415593

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.958384 & 7.4236 & 0 \tabularnewline
2 & -0.017189 & -0.1331 & 0.447262 \tabularnewline
3 & -0.072022 & -0.5579 & 0.289501 \tabularnewline
4 & -0.011765 & -0.0911 & 0.463847 \tabularnewline
5 & -0.04642 & -0.3596 & 0.360215 \tabularnewline
6 & -0.047427 & -0.3674 & 0.357318 \tabularnewline
7 & -0.017836 & -0.1382 & 0.44529 \tabularnewline
8 & -0.06968 & -0.5397 & 0.295688 \tabularnewline
9 & -0.149266 & -1.1562 & 0.12609 \tabularnewline
10 & -0.151151 & -1.1708 & 0.123152 \tabularnewline
11 & 6e-05 & 5e-04 & 0.499815 \tabularnewline
12 & -0.139135 & -1.0777 & 0.142733 \tabularnewline
13 & 0.135367 & 1.0486 & 0.149295 \tabularnewline
14 & 0.019452 & 0.1507 & 0.440368 \tabularnewline
15 & -0.12871 & -0.997 & 0.161389 \tabularnewline
16 & 0.004754 & 0.0368 & 0.485374 \tabularnewline
17 & -0.032773 & -0.2539 & 0.400236 \tabularnewline
18 & 0.004383 & 0.034 & 0.486514 \tabularnewline
19 & -0.014906 & -0.1155 & 0.454234 \tabularnewline
20 & -0.004092 & -0.0317 & 0.48741 \tabularnewline
21 & -0.099353 & -0.7696 & 0.222282 \tabularnewline
22 & 0.04432 & 0.3433 & 0.366286 \tabularnewline
23 & -0.052773 & -0.4088 & 0.34208 \tabularnewline
24 & -0.129591 & -1.0038 & 0.159752 \tabularnewline
25 & 0.094465 & 0.7317 & 0.233593 \tabularnewline
26 & 0.03979 & 0.3082 & 0.379494 \tabularnewline
27 & 0.020126 & 0.1559 & 0.438319 \tabularnewline
28 & -0.11705 & -0.9067 & 0.184106 \tabularnewline
29 & -0.07171 & -0.5555 & 0.290321 \tabularnewline
30 & -0.120701 & -0.9349 & 0.176782 \tabularnewline
31 & -0.002462 & -0.0191 & 0.492423 \tabularnewline
32 & 0.013008 & 0.1008 & 0.460038 \tabularnewline
33 & -0.040475 & -0.3135 & 0.377488 \tabularnewline
34 & 0.146143 & 1.132 & 0.131066 \tabularnewline
35 & 0.006944 & 0.0538 & 0.478643 \tabularnewline
36 & -0.027642 & -0.2141 & 0.415593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59743&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]0.958384[/C][C]7.4236[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.017189[/C][C]-0.1331[/C][C]0.447262[/C][/ROW]
[ROW][C]3[/C][C]-0.072022[/C][C]-0.5579[/C][C]0.289501[/C][/ROW]
[ROW][C]4[/C][C]-0.011765[/C][C]-0.0911[/C][C]0.463847[/C][/ROW]
[ROW][C]5[/C][C]-0.04642[/C][C]-0.3596[/C][C]0.360215[/C][/ROW]
[ROW][C]6[/C][C]-0.047427[/C][C]-0.3674[/C][C]0.357318[/C][/ROW]
[ROW][C]7[/C][C]-0.017836[/C][C]-0.1382[/C][C]0.44529[/C][/ROW]
[ROW][C]8[/C][C]-0.06968[/C][C]-0.5397[/C][C]0.295688[/C][/ROW]
[ROW][C]9[/C][C]-0.149266[/C][C]-1.1562[/C][C]0.12609[/C][/ROW]
[ROW][C]10[/C][C]-0.151151[/C][C]-1.1708[/C][C]0.123152[/C][/ROW]
[ROW][C]11[/C][C]6e-05[/C][C]5e-04[/C][C]0.499815[/C][/ROW]
[ROW][C]12[/C][C]-0.139135[/C][C]-1.0777[/C][C]0.142733[/C][/ROW]
[ROW][C]13[/C][C]0.135367[/C][C]1.0486[/C][C]0.149295[/C][/ROW]
[ROW][C]14[/C][C]0.019452[/C][C]0.1507[/C][C]0.440368[/C][/ROW]
[ROW][C]15[/C][C]-0.12871[/C][C]-0.997[/C][C]0.161389[/C][/ROW]
[ROW][C]16[/C][C]0.004754[/C][C]0.0368[/C][C]0.485374[/C][/ROW]
[ROW][C]17[/C][C]-0.032773[/C][C]-0.2539[/C][C]0.400236[/C][/ROW]
[ROW][C]18[/C][C]0.004383[/C][C]0.034[/C][C]0.486514[/C][/ROW]
[ROW][C]19[/C][C]-0.014906[/C][C]-0.1155[/C][C]0.454234[/C][/ROW]
[ROW][C]20[/C][C]-0.004092[/C][C]-0.0317[/C][C]0.48741[/C][/ROW]
[ROW][C]21[/C][C]-0.099353[/C][C]-0.7696[/C][C]0.222282[/C][/ROW]
[ROW][C]22[/C][C]0.04432[/C][C]0.3433[/C][C]0.366286[/C][/ROW]
[ROW][C]23[/C][C]-0.052773[/C][C]-0.4088[/C][C]0.34208[/C][/ROW]
[ROW][C]24[/C][C]-0.129591[/C][C]-1.0038[/C][C]0.159752[/C][/ROW]
[ROW][C]25[/C][C]0.094465[/C][C]0.7317[/C][C]0.233593[/C][/ROW]
[ROW][C]26[/C][C]0.03979[/C][C]0.3082[/C][C]0.379494[/C][/ROW]
[ROW][C]27[/C][C]0.020126[/C][C]0.1559[/C][C]0.438319[/C][/ROW]
[ROW][C]28[/C][C]-0.11705[/C][C]-0.9067[/C][C]0.184106[/C][/ROW]
[ROW][C]29[/C][C]-0.07171[/C][C]-0.5555[/C][C]0.290321[/C][/ROW]
[ROW][C]30[/C][C]-0.120701[/C][C]-0.9349[/C][C]0.176782[/C][/ROW]
[ROW][C]31[/C][C]-0.002462[/C][C]-0.0191[/C][C]0.492423[/C][/ROW]
[ROW][C]32[/C][C]0.013008[/C][C]0.1008[/C][C]0.460038[/C][/ROW]
[ROW][C]33[/C][C]-0.040475[/C][C]-0.3135[/C][C]0.377488[/C][/ROW]
[ROW][C]34[/C][C]0.146143[/C][C]1.132[/C][C]0.131066[/C][/ROW]
[ROW][C]35[/C][C]0.006944[/C][C]0.0538[/C][C]0.478643[/C][/ROW]
[ROW][C]36[/C][C]-0.027642[/C][C]-0.2141[/C][C]0.415593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59743&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59743&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
10.9583847.42360
2-0.017189-0.13310.447262
3-0.072022-0.55790.289501
4-0.011765-0.09110.463847
5-0.04642-0.35960.360215
6-0.047427-0.36740.357318
7-0.017836-0.13820.44529
8-0.06968-0.53970.295688
9-0.149266-1.15620.12609
10-0.151151-1.17080.123152
116e-055e-040.499815
12-0.139135-1.07770.142733
130.1353671.04860.149295
140.0194520.15070.440368
15-0.12871-0.9970.161389
160.0047540.03680.485374
17-0.032773-0.25390.400236
180.0043830.0340.486514
19-0.014906-0.11550.454234
20-0.004092-0.03170.48741
21-0.099353-0.76960.222282
220.044320.34330.366286
23-0.052773-0.40880.34208
24-0.129591-1.00380.159752
250.0944650.73170.233593
260.039790.30820.379494
270.0201260.15590.438319
28-0.11705-0.90670.184106
29-0.07171-0.55550.290321
30-0.120701-0.93490.176782
31-0.002462-0.01910.492423
320.0130080.10080.460038
33-0.040475-0.31350.377488
340.1461431.1320.131066
350.0069440.05380.478643
36-0.027642-0.21410.415593


Figures (Output of Computation)

Input Parameters & R Code

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')