Free Statistics

of Irreproducible Research!

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, 27 Nov 2009 02:07:06 -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/Nov/27/t1259312957j6zx1gm6ay348vj.htm/, Retrieved Mon, 29 Apr 2024 05:04:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60488, Retrieved Mon, 29 Apr 2024 05:04:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166
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]
- R  D          [(Partial) Autocorrelation Function] [Workshop8 ACF d=0...] [2009-11-27 09:07:06] [5ed0eef5d4509bbfdac0ae6d87f3b4bf] [Current]
Feedback Forum

Post a new message
Dataseries X:
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=60488&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=60488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60488&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
10.9362367.06840
20.8649646.53030
30.7843335.92160
40.6869755.18661e-06
50.5820774.39462.4e-05
60.4809523.63110.000303
70.3734472.81950.003302
80.2847252.14960.017921
90.2018021.52360.066573
100.131280.99110.162902
110.0726260.54830.292808
120.0099070.07480.470318
13-0.048216-0.3640.358594
14-0.098365-0.74260.230375
15-0.15828-1.1950.118521
16-0.228713-1.72670.044815
17-0.283873-2.14320.01819
18-0.34702-2.61990.005626
19-0.400865-3.02650.001855
20-0.454079-3.42820.000567
21-0.50084-3.78130.000188
22-0.53185-4.01548.8e-05
23-0.547708-4.13515.9e-05
24-0.549922-4.15185.6e-05
25-0.5298-3.99999.2e-05
26-0.515573-3.89250.000131
27-0.486367-3.6720.000266
28-0.438482-3.31050.00081
29-0.38676-2.920.002503
30-0.335231-2.53090.00708
31-0.282831-2.13530.018522
32-0.237188-1.79070.039323
33-0.18388-1.38830.08523
34-0.132956-1.00380.159859
35-0.091291-0.68920.246738
36-0.060071-0.45350.325945

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936236 & 7.0684 & 0 \tabularnewline
2 & 0.864964 & 6.5303 & 0 \tabularnewline
3 & 0.784333 & 5.9216 & 0 \tabularnewline
4 & 0.686975 & 5.1866 & 1e-06 \tabularnewline
5 & 0.582077 & 4.3946 & 2.4e-05 \tabularnewline
6 & 0.480952 & 3.6311 & 0.000303 \tabularnewline
7 & 0.373447 & 2.8195 & 0.003302 \tabularnewline
8 & 0.284725 & 2.1496 & 0.017921 \tabularnewline
9 & 0.201802 & 1.5236 & 0.066573 \tabularnewline
10 & 0.13128 & 0.9911 & 0.162902 \tabularnewline
11 & 0.072626 & 0.5483 & 0.292808 \tabularnewline
12 & 0.009907 & 0.0748 & 0.470318 \tabularnewline
13 & -0.048216 & -0.364 & 0.358594 \tabularnewline
14 & -0.098365 & -0.7426 & 0.230375 \tabularnewline
15 & -0.15828 & -1.195 & 0.118521 \tabularnewline
16 & -0.228713 & -1.7267 & 0.044815 \tabularnewline
17 & -0.283873 & -2.1432 & 0.01819 \tabularnewline
18 & -0.34702 & -2.6199 & 0.005626 \tabularnewline
19 & -0.400865 & -3.0265 & 0.001855 \tabularnewline
20 & -0.454079 & -3.4282 & 0.000567 \tabularnewline
21 & -0.50084 & -3.7813 & 0.000188 \tabularnewline
22 & -0.53185 & -4.0154 & 8.8e-05 \tabularnewline
23 & -0.547708 & -4.1351 & 5.9e-05 \tabularnewline
24 & -0.549922 & -4.1518 & 5.6e-05 \tabularnewline
25 & -0.5298 & -3.9999 & 9.2e-05 \tabularnewline
26 & -0.515573 & -3.8925 & 0.000131 \tabularnewline
27 & -0.486367 & -3.672 & 0.000266 \tabularnewline
28 & -0.438482 & -3.3105 & 0.00081 \tabularnewline
29 & -0.38676 & -2.92 & 0.002503 \tabularnewline
30 & -0.335231 & -2.5309 & 0.00708 \tabularnewline
31 & -0.282831 & -2.1353 & 0.018522 \tabularnewline
32 & -0.237188 & -1.7907 & 0.039323 \tabularnewline
33 & -0.18388 & -1.3883 & 0.08523 \tabularnewline
34 & -0.132956 & -1.0038 & 0.159859 \tabularnewline
35 & -0.091291 & -0.6892 & 0.246738 \tabularnewline
36 & -0.060071 & -0.4535 & 0.325945 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60488&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]0.936236[/C][C]7.0684[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.864964[/C][C]6.5303[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.784333[/C][C]5.9216[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.686975[/C][C]5.1866[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.582077[/C][C]4.3946[/C][C]2.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.480952[/C][C]3.6311[/C][C]0.000303[/C][/ROW]
[ROW][C]7[/C][C]0.373447[/C][C]2.8195[/C][C]0.003302[/C][/ROW]
[ROW][C]8[/C][C]0.284725[/C][C]2.1496[/C][C]0.017921[/C][/ROW]
[ROW][C]9[/C][C]0.201802[/C][C]1.5236[/C][C]0.066573[/C][/ROW]
[ROW][C]10[/C][C]0.13128[/C][C]0.9911[/C][C]0.162902[/C][/ROW]
[ROW][C]11[/C][C]0.072626[/C][C]0.5483[/C][C]0.292808[/C][/ROW]
[ROW][C]12[/C][C]0.009907[/C][C]0.0748[/C][C]0.470318[/C][/ROW]
[ROW][C]13[/C][C]-0.048216[/C][C]-0.364[/C][C]0.358594[/C][/ROW]
[ROW][C]14[/C][C]-0.098365[/C][C]-0.7426[/C][C]0.230375[/C][/ROW]
[ROW][C]15[/C][C]-0.15828[/C][C]-1.195[/C][C]0.118521[/C][/ROW]
[ROW][C]16[/C][C]-0.228713[/C][C]-1.7267[/C][C]0.044815[/C][/ROW]
[ROW][C]17[/C][C]-0.283873[/C][C]-2.1432[/C][C]0.01819[/C][/ROW]
[ROW][C]18[/C][C]-0.34702[/C][C]-2.6199[/C][C]0.005626[/C][/ROW]
[ROW][C]19[/C][C]-0.400865[/C][C]-3.0265[/C][C]0.001855[/C][/ROW]
[ROW][C]20[/C][C]-0.454079[/C][C]-3.4282[/C][C]0.000567[/C][/ROW]
[ROW][C]21[/C][C]-0.50084[/C][C]-3.7813[/C][C]0.000188[/C][/ROW]
[ROW][C]22[/C][C]-0.53185[/C][C]-4.0154[/C][C]8.8e-05[/C][/ROW]
[ROW][C]23[/C][C]-0.547708[/C][C]-4.1351[/C][C]5.9e-05[/C][/ROW]
[ROW][C]24[/C][C]-0.549922[/C][C]-4.1518[/C][C]5.6e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.5298[/C][C]-3.9999[/C][C]9.2e-05[/C][/ROW]
[ROW][C]26[/C][C]-0.515573[/C][C]-3.8925[/C][C]0.000131[/C][/ROW]
[ROW][C]27[/C][C]-0.486367[/C][C]-3.672[/C][C]0.000266[/C][/ROW]
[ROW][C]28[/C][C]-0.438482[/C][C]-3.3105[/C][C]0.00081[/C][/ROW]
[ROW][C]29[/C][C]-0.38676[/C][C]-2.92[/C][C]0.002503[/C][/ROW]
[ROW][C]30[/C][C]-0.335231[/C][C]-2.5309[/C][C]0.00708[/C][/ROW]
[ROW][C]31[/C][C]-0.282831[/C][C]-2.1353[/C][C]0.018522[/C][/ROW]
[ROW][C]32[/C][C]-0.237188[/C][C]-1.7907[/C][C]0.039323[/C][/ROW]
[ROW][C]33[/C][C]-0.18388[/C][C]-1.3883[/C][C]0.08523[/C][/ROW]
[ROW][C]34[/C][C]-0.132956[/C][C]-1.0038[/C][C]0.159859[/C][/ROW]
[ROW][C]35[/C][C]-0.091291[/C][C]-0.6892[/C][C]0.246738[/C][/ROW]
[ROW][C]36[/C][C]-0.060071[/C][C]-0.4535[/C][C]0.325945[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60488&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
10.9362367.06840
20.8649646.53030
30.7843335.92160
40.6869755.18661e-06
50.5820774.39462.4e-05
60.4809523.63110.000303
70.3734472.81950.003302
80.2847252.14960.017921
90.2018021.52360.066573
100.131280.99110.162902
110.0726260.54830.292808
120.0099070.07480.470318
13-0.048216-0.3640.358594
14-0.098365-0.74260.230375
15-0.15828-1.1950.118521
16-0.228713-1.72670.044815
17-0.283873-2.14320.01819
18-0.34702-2.61990.005626
19-0.400865-3.02650.001855
20-0.454079-3.42820.000567
21-0.50084-3.78130.000188
22-0.53185-4.01548.8e-05
23-0.547708-4.13515.9e-05
24-0.549922-4.15185.6e-05
25-0.5298-3.99999.2e-05
26-0.515573-3.89250.000131
27-0.486367-3.6720.000266
28-0.438482-3.31050.00081
29-0.38676-2.920.002503
30-0.335231-2.53090.00708
31-0.282831-2.13530.018522
32-0.237188-1.79070.039323
33-0.18388-1.38830.08523
34-0.132956-1.00380.159859
35-0.091291-0.68920.246738
36-0.060071-0.45350.325945







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9362367.06840
2-0.093749-0.70780.240979
3-0.111339-0.84060.202044
4-0.17614-1.32980.094436
5-0.108018-0.81550.209086
6-0.017216-0.130.44852
7-0.105086-0.79340.215422
80.0942090.71130.23991
9-0.030841-0.23280.408358
100.0277560.20960.417381
11-0.002622-0.01980.492137
12-0.142159-1.07330.143834
13-0.046346-0.34990.363851
14-0.042128-0.31810.375802
15-0.131773-0.99490.162004
16-0.171495-1.29480.100312
170.0526010.39710.346377
18-0.114029-0.86090.196451
190.0025810.01950.492261
20-0.107565-0.81210.210057
21-0.049665-0.3750.354539
220.0186010.14040.444407
23-0.020306-0.15330.439349
240.0421670.31840.37569
250.0275630.20810.417947
26-0.132558-1.00080.16058
270.039580.29880.383081
280.0501980.3790.353052
290.0168920.12750.449483
30-0.014499-0.10950.45661
31-0.04091-0.30890.379276
32-0.045561-0.3440.366063
330.0669670.50560.307547
34-0.020444-0.15430.438941
35-0.034817-0.26290.396801
36-0.136334-1.02930.153844

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936236 & 7.0684 & 0 \tabularnewline
2 & -0.093749 & -0.7078 & 0.240979 \tabularnewline
3 & -0.111339 & -0.8406 & 0.202044 \tabularnewline
4 & -0.17614 & -1.3298 & 0.094436 \tabularnewline
5 & -0.108018 & -0.8155 & 0.209086 \tabularnewline
6 & -0.017216 & -0.13 & 0.44852 \tabularnewline
7 & -0.105086 & -0.7934 & 0.215422 \tabularnewline
8 & 0.094209 & 0.7113 & 0.23991 \tabularnewline
9 & -0.030841 & -0.2328 & 0.408358 \tabularnewline
10 & 0.027756 & 0.2096 & 0.417381 \tabularnewline
11 & -0.002622 & -0.0198 & 0.492137 \tabularnewline
12 & -0.142159 & -1.0733 & 0.143834 \tabularnewline
13 & -0.046346 & -0.3499 & 0.363851 \tabularnewline
14 & -0.042128 & -0.3181 & 0.375802 \tabularnewline
15 & -0.131773 & -0.9949 & 0.162004 \tabularnewline
16 & -0.171495 & -1.2948 & 0.100312 \tabularnewline
17 & 0.052601 & 0.3971 & 0.346377 \tabularnewline
18 & -0.114029 & -0.8609 & 0.196451 \tabularnewline
19 & 0.002581 & 0.0195 & 0.492261 \tabularnewline
20 & -0.107565 & -0.8121 & 0.210057 \tabularnewline
21 & -0.049665 & -0.375 & 0.354539 \tabularnewline
22 & 0.018601 & 0.1404 & 0.444407 \tabularnewline
23 & -0.020306 & -0.1533 & 0.439349 \tabularnewline
24 & 0.042167 & 0.3184 & 0.37569 \tabularnewline
25 & 0.027563 & 0.2081 & 0.417947 \tabularnewline
26 & -0.132558 & -1.0008 & 0.16058 \tabularnewline
27 & 0.03958 & 0.2988 & 0.383081 \tabularnewline
28 & 0.050198 & 0.379 & 0.353052 \tabularnewline
29 & 0.016892 & 0.1275 & 0.449483 \tabularnewline
30 & -0.014499 & -0.1095 & 0.45661 \tabularnewline
31 & -0.04091 & -0.3089 & 0.379276 \tabularnewline
32 & -0.045561 & -0.344 & 0.366063 \tabularnewline
33 & 0.066967 & 0.5056 & 0.307547 \tabularnewline
34 & -0.020444 & -0.1543 & 0.438941 \tabularnewline
35 & -0.034817 & -0.2629 & 0.396801 \tabularnewline
36 & -0.136334 & -1.0293 & 0.153844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60488&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]0.936236[/C][C]7.0684[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.093749[/C][C]-0.7078[/C][C]0.240979[/C][/ROW]
[ROW][C]3[/C][C]-0.111339[/C][C]-0.8406[/C][C]0.202044[/C][/ROW]
[ROW][C]4[/C][C]-0.17614[/C][C]-1.3298[/C][C]0.094436[/C][/ROW]
[ROW][C]5[/C][C]-0.108018[/C][C]-0.8155[/C][C]0.209086[/C][/ROW]
[ROW][C]6[/C][C]-0.017216[/C][C]-0.13[/C][C]0.44852[/C][/ROW]
[ROW][C]7[/C][C]-0.105086[/C][C]-0.7934[/C][C]0.215422[/C][/ROW]
[ROW][C]8[/C][C]0.094209[/C][C]0.7113[/C][C]0.23991[/C][/ROW]
[ROW][C]9[/C][C]-0.030841[/C][C]-0.2328[/C][C]0.408358[/C][/ROW]
[ROW][C]10[/C][C]0.027756[/C][C]0.2096[/C][C]0.417381[/C][/ROW]
[ROW][C]11[/C][C]-0.002622[/C][C]-0.0198[/C][C]0.492137[/C][/ROW]
[ROW][C]12[/C][C]-0.142159[/C][C]-1.0733[/C][C]0.143834[/C][/ROW]
[ROW][C]13[/C][C]-0.046346[/C][C]-0.3499[/C][C]0.363851[/C][/ROW]
[ROW][C]14[/C][C]-0.042128[/C][C]-0.3181[/C][C]0.375802[/C][/ROW]
[ROW][C]15[/C][C]-0.131773[/C][C]-0.9949[/C][C]0.162004[/C][/ROW]
[ROW][C]16[/C][C]-0.171495[/C][C]-1.2948[/C][C]0.100312[/C][/ROW]
[ROW][C]17[/C][C]0.052601[/C][C]0.3971[/C][C]0.346377[/C][/ROW]
[ROW][C]18[/C][C]-0.114029[/C][C]-0.8609[/C][C]0.196451[/C][/ROW]
[ROW][C]19[/C][C]0.002581[/C][C]0.0195[/C][C]0.492261[/C][/ROW]
[ROW][C]20[/C][C]-0.107565[/C][C]-0.8121[/C][C]0.210057[/C][/ROW]
[ROW][C]21[/C][C]-0.049665[/C][C]-0.375[/C][C]0.354539[/C][/ROW]
[ROW][C]22[/C][C]0.018601[/C][C]0.1404[/C][C]0.444407[/C][/ROW]
[ROW][C]23[/C][C]-0.020306[/C][C]-0.1533[/C][C]0.439349[/C][/ROW]
[ROW][C]24[/C][C]0.042167[/C][C]0.3184[/C][C]0.37569[/C][/ROW]
[ROW][C]25[/C][C]0.027563[/C][C]0.2081[/C][C]0.417947[/C][/ROW]
[ROW][C]26[/C][C]-0.132558[/C][C]-1.0008[/C][C]0.16058[/C][/ROW]
[ROW][C]27[/C][C]0.03958[/C][C]0.2988[/C][C]0.383081[/C][/ROW]
[ROW][C]28[/C][C]0.050198[/C][C]0.379[/C][C]0.353052[/C][/ROW]
[ROW][C]29[/C][C]0.016892[/C][C]0.1275[/C][C]0.449483[/C][/ROW]
[ROW][C]30[/C][C]-0.014499[/C][C]-0.1095[/C][C]0.45661[/C][/ROW]
[ROW][C]31[/C][C]-0.04091[/C][C]-0.3089[/C][C]0.379276[/C][/ROW]
[ROW][C]32[/C][C]-0.045561[/C][C]-0.344[/C][C]0.366063[/C][/ROW]
[ROW][C]33[/C][C]0.066967[/C][C]0.5056[/C][C]0.307547[/C][/ROW]
[ROW][C]34[/C][C]-0.020444[/C][C]-0.1543[/C][C]0.438941[/C][/ROW]
[ROW][C]35[/C][C]-0.034817[/C][C]-0.2629[/C][C]0.396801[/C][/ROW]
[ROW][C]36[/C][C]-0.136334[/C][C]-1.0293[/C][C]0.153844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60488&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60488&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
10.9362367.06840
2-0.093749-0.70780.240979
3-0.111339-0.84060.202044
4-0.17614-1.32980.094436
5-0.108018-0.81550.209086
6-0.017216-0.130.44852
7-0.105086-0.79340.215422
80.0942090.71130.23991
9-0.030841-0.23280.408358
100.0277560.20960.417381
11-0.002622-0.01980.492137
12-0.142159-1.07330.143834
13-0.046346-0.34990.363851
14-0.042128-0.31810.375802
15-0.131773-0.99490.162004
16-0.171495-1.29480.100312
170.0526010.39710.346377
18-0.114029-0.86090.196451
190.0025810.01950.492261
20-0.107565-0.81210.210057
21-0.049665-0.3750.354539
220.0186010.14040.444407
23-0.020306-0.15330.439349
240.0421670.31840.37569
250.0275630.20810.417947
26-0.132558-1.00080.16058
270.039580.29880.383081
280.0501980.3790.353052
290.0168920.12750.449483
30-0.014499-0.10950.45661
31-0.04091-0.30890.379276
32-0.045561-0.3440.366063
330.0669670.50560.307547
34-0.020444-0.15430.438941
35-0.034817-0.26290.396801
36-0.136334-1.02930.153844



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')