FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationFri, 18 Dec 2009 04:26:25 -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/18/t1261135643m3ib3f6ipguvh19.htm/, Retrieved Sat, 27 Apr 2024 23:35:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69242, Retrieved Sat, 27 Apr 2024 23:35:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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 15:43:41] [e149fd9094b67af26551857fa83a9d9d]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-18 11:26:25] [27b6e36591879260e4dc6bb7e89a38fd] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69242&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]2 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=69242&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69242&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2416781.8720.03304
2-0.253626-1.96460.027049
3-0.271106-2.10.019972
4-0.173703-1.34550.091764
50.084840.65720.256794
60.2255921.74740.04284
70.0883560.68440.248177
8-0.221791-1.7180.045478
9-0.279503-2.1650.017187
10-0.219943-1.70370.046809
110.2428541.88110.032404
120.7335115.68180
130.1258120.97450.166852
14-0.249632-1.93360.028939
15-0.244737-1.89570.031408
16-0.166839-1.29230.100599
170.03960.30670.380051
180.1488611.15310.126727
190.0398730.30890.379252
20-0.232537-1.80120.038346
21-0.253486-1.96350.027114
22-0.168124-1.30230.098898
230.1937661.50090.069312
240.5138613.98039.4e-05
250.0516340.40.345305
26-0.22278-1.72560.044779
27-0.15347-1.18880.119606
28-0.105001-0.81330.209622
290.0346870.26870.394546
300.0984320.76250.224389
310.0277820.21520.415171
32-0.192384-1.49020.070705
33-0.16908-1.30970.097647
34-0.065107-0.50430.307943
350.1432231.10940.135843
360.2952942.28730.012859

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.241678 & 1.872 & 0.03304 \tabularnewline
2 & -0.253626 & -1.9646 & 0.027049 \tabularnewline
3 & -0.271106 & -2.1 & 0.019972 \tabularnewline
4 & -0.173703 & -1.3455 & 0.091764 \tabularnewline
5 & 0.08484 & 0.6572 & 0.256794 \tabularnewline
6 & 0.225592 & 1.7474 & 0.04284 \tabularnewline
7 & 0.088356 & 0.6844 & 0.248177 \tabularnewline
8 & -0.221791 & -1.718 & 0.045478 \tabularnewline
9 & -0.279503 & -2.165 & 0.017187 \tabularnewline
10 & -0.219943 & -1.7037 & 0.046809 \tabularnewline
11 & 0.242854 & 1.8811 & 0.032404 \tabularnewline
12 & 0.733511 & 5.6818 & 0 \tabularnewline
13 & 0.125812 & 0.9745 & 0.166852 \tabularnewline
14 & -0.249632 & -1.9336 & 0.028939 \tabularnewline
15 & -0.244737 & -1.8957 & 0.031408 \tabularnewline
16 & -0.166839 & -1.2923 & 0.100599 \tabularnewline
17 & 0.0396 & 0.3067 & 0.380051 \tabularnewline
18 & 0.148861 & 1.1531 & 0.126727 \tabularnewline
19 & 0.039873 & 0.3089 & 0.379252 \tabularnewline
20 & -0.232537 & -1.8012 & 0.038346 \tabularnewline
21 & -0.253486 & -1.9635 & 0.027114 \tabularnewline
22 & -0.168124 & -1.3023 & 0.098898 \tabularnewline
23 & 0.193766 & 1.5009 & 0.069312 \tabularnewline
24 & 0.513861 & 3.9803 & 9.4e-05 \tabularnewline
25 & 0.051634 & 0.4 & 0.345305 \tabularnewline
26 & -0.22278 & -1.7256 & 0.044779 \tabularnewline
27 & -0.15347 & -1.1888 & 0.119606 \tabularnewline
28 & -0.105001 & -0.8133 & 0.209622 \tabularnewline
29 & 0.034687 & 0.2687 & 0.394546 \tabularnewline
30 & 0.098432 & 0.7625 & 0.224389 \tabularnewline
31 & 0.027782 & 0.2152 & 0.415171 \tabularnewline
32 & -0.192384 & -1.4902 & 0.070705 \tabularnewline
33 & -0.16908 & -1.3097 & 0.097647 \tabularnewline
34 & -0.065107 & -0.5043 & 0.307943 \tabularnewline
35 & 0.143223 & 1.1094 & 0.135843 \tabularnewline
36 & 0.295294 & 2.2873 & 0.012859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69242&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]0.241678[/C][C]1.872[/C][C]0.03304[/C][/ROW]
[ROW][C]2[/C][C]-0.253626[/C][C]-1.9646[/C][C]0.027049[/C][/ROW]
[ROW][C]3[/C][C]-0.271106[/C][C]-2.1[/C][C]0.019972[/C][/ROW]
[ROW][C]4[/C][C]-0.173703[/C][C]-1.3455[/C][C]0.091764[/C][/ROW]
[ROW][C]5[/C][C]0.08484[/C][C]0.6572[/C][C]0.256794[/C][/ROW]
[ROW][C]6[/C][C]0.225592[/C][C]1.7474[/C][C]0.04284[/C][/ROW]
[ROW][C]7[/C][C]0.088356[/C][C]0.6844[/C][C]0.248177[/C][/ROW]
[ROW][C]8[/C][C]-0.221791[/C][C]-1.718[/C][C]0.045478[/C][/ROW]
[ROW][C]9[/C][C]-0.279503[/C][C]-2.165[/C][C]0.017187[/C][/ROW]
[ROW][C]10[/C][C]-0.219943[/C][C]-1.7037[/C][C]0.046809[/C][/ROW]
[ROW][C]11[/C][C]0.242854[/C][C]1.8811[/C][C]0.032404[/C][/ROW]
[ROW][C]12[/C][C]0.733511[/C][C]5.6818[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.125812[/C][C]0.9745[/C][C]0.166852[/C][/ROW]
[ROW][C]14[/C][C]-0.249632[/C][C]-1.9336[/C][C]0.028939[/C][/ROW]
[ROW][C]15[/C][C]-0.244737[/C][C]-1.8957[/C][C]0.031408[/C][/ROW]
[ROW][C]16[/C][C]-0.166839[/C][C]-1.2923[/C][C]0.100599[/C][/ROW]
[ROW][C]17[/C][C]0.0396[/C][C]0.3067[/C][C]0.380051[/C][/ROW]
[ROW][C]18[/C][C]0.148861[/C][C]1.1531[/C][C]0.126727[/C][/ROW]
[ROW][C]19[/C][C]0.039873[/C][C]0.3089[/C][C]0.379252[/C][/ROW]
[ROW][C]20[/C][C]-0.232537[/C][C]-1.8012[/C][C]0.038346[/C][/ROW]
[ROW][C]21[/C][C]-0.253486[/C][C]-1.9635[/C][C]0.027114[/C][/ROW]
[ROW][C]22[/C][C]-0.168124[/C][C]-1.3023[/C][C]0.098898[/C][/ROW]
[ROW][C]23[/C][C]0.193766[/C][C]1.5009[/C][C]0.069312[/C][/ROW]
[ROW][C]24[/C][C]0.513861[/C][C]3.9803[/C][C]9.4e-05[/C][/ROW]
[ROW][C]25[/C][C]0.051634[/C][C]0.4[/C][C]0.345305[/C][/ROW]
[ROW][C]26[/C][C]-0.22278[/C][C]-1.7256[/C][C]0.044779[/C][/ROW]
[ROW][C]27[/C][C]-0.15347[/C][C]-1.1888[/C][C]0.119606[/C][/ROW]
[ROW][C]28[/C][C]-0.105001[/C][C]-0.8133[/C][C]0.209622[/C][/ROW]
[ROW][C]29[/C][C]0.034687[/C][C]0.2687[/C][C]0.394546[/C][/ROW]
[ROW][C]30[/C][C]0.098432[/C][C]0.7625[/C][C]0.224389[/C][/ROW]
[ROW][C]31[/C][C]0.027782[/C][C]0.2152[/C][C]0.415171[/C][/ROW]
[ROW][C]32[/C][C]-0.192384[/C][C]-1.4902[/C][C]0.070705[/C][/ROW]
[ROW][C]33[/C][C]-0.16908[/C][C]-1.3097[/C][C]0.097647[/C][/ROW]
[ROW][C]34[/C][C]-0.065107[/C][C]-0.5043[/C][C]0.307943[/C][/ROW]
[ROW][C]35[/C][C]0.143223[/C][C]1.1094[/C][C]0.135843[/C][/ROW]
[ROW][C]36[/C][C]0.295294[/C][C]2.2873[/C][C]0.012859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69242&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69242&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
10.2416781.8720.03304
2-0.253626-1.96460.027049
3-0.271106-2.10.019972
4-0.173703-1.34550.091764
50.084840.65720.256794
60.2255921.74740.04284
70.0883560.68440.248177
8-0.221791-1.7180.045478
9-0.279503-2.1650.017187
10-0.219943-1.70370.046809
110.2428541.88110.032404
120.7335115.68180
130.1258120.97450.166852
14-0.249632-1.93360.028939
15-0.244737-1.89570.031408
16-0.166839-1.29230.100599
170.03960.30670.380051
180.1488611.15310.126727
190.0398730.30890.379252
20-0.232537-1.80120.038346
21-0.253486-1.96350.027114
22-0.168124-1.30230.098898
230.1937661.50090.069312
240.5138613.98039.4e-05
250.0516340.40.345305
26-0.22278-1.72560.044779
27-0.15347-1.18880.119606
28-0.105001-0.81330.209622
290.0346870.26870.394546
300.0984320.76250.224389
310.0277820.21520.415171
32-0.192384-1.49020.070705
33-0.16908-1.30970.097647
34-0.065107-0.50430.307943
350.1432231.10940.135843
360.2952942.28730.012859






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2416781.8720.03304
2-0.33139-2.56690.006386
3-0.130529-1.01110.158021
4-0.169981-1.31670.096479
50.0719340.55720.289732
60.0802960.6220.26816
7-0.004881-0.03780.484984
8-0.204669-1.58540.059071
9-0.12563-0.97310.167199
10-0.243725-1.88790.03194
110.2522971.95430.027666
120.5989314.63931e-05
13-0.193654-1.50.069424
140.0584680.45290.326129
15-0.023664-0.18330.427589
16-0.101129-0.78330.218253
17-0.089341-0.6920.245793
18-0.17392-1.34720.091494
19-0.053345-0.41320.340462
20-0.032052-0.24830.402385
21-0.022062-0.17090.432442
22-0.012292-0.09520.46223
23-0.105422-0.81660.208695
24-0.041117-0.31850.37561
25-0.044783-0.34690.364943
26-0.070103-0.5430.294566
270.1009820.78220.218585
28-0.016947-0.13130.448001
290.0279540.21650.414654
30-0.035039-0.27140.393504
310.006140.04760.481112
32-0.009169-0.0710.471807
330.0215870.16720.433881
340.0395280.30620.380263
35-0.08669-0.67150.252239
36-0.163316-1.2650.105374

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.241678 & 1.872 & 0.03304 \tabularnewline
2 & -0.33139 & -2.5669 & 0.006386 \tabularnewline
3 & -0.130529 & -1.0111 & 0.158021 \tabularnewline
4 & -0.169981 & -1.3167 & 0.096479 \tabularnewline
5 & 0.071934 & 0.5572 & 0.289732 \tabularnewline
6 & 0.080296 & 0.622 & 0.26816 \tabularnewline
7 & -0.004881 & -0.0378 & 0.484984 \tabularnewline
8 & -0.204669 & -1.5854 & 0.059071 \tabularnewline
9 & -0.12563 & -0.9731 & 0.167199 \tabularnewline
10 & -0.243725 & -1.8879 & 0.03194 \tabularnewline
11 & 0.252297 & 1.9543 & 0.027666 \tabularnewline
12 & 0.598931 & 4.6393 & 1e-05 \tabularnewline
13 & -0.193654 & -1.5 & 0.069424 \tabularnewline
14 & 0.058468 & 0.4529 & 0.326129 \tabularnewline
15 & -0.023664 & -0.1833 & 0.427589 \tabularnewline
16 & -0.101129 & -0.7833 & 0.218253 \tabularnewline
17 & -0.089341 & -0.692 & 0.245793 \tabularnewline
18 & -0.17392 & -1.3472 & 0.091494 \tabularnewline
19 & -0.053345 & -0.4132 & 0.340462 \tabularnewline
20 & -0.032052 & -0.2483 & 0.402385 \tabularnewline
21 & -0.022062 & -0.1709 & 0.432442 \tabularnewline
22 & -0.012292 & -0.0952 & 0.46223 \tabularnewline
23 & -0.105422 & -0.8166 & 0.208695 \tabularnewline
24 & -0.041117 & -0.3185 & 0.37561 \tabularnewline
25 & -0.044783 & -0.3469 & 0.364943 \tabularnewline
26 & -0.070103 & -0.543 & 0.294566 \tabularnewline
27 & 0.100982 & 0.7822 & 0.218585 \tabularnewline
28 & -0.016947 & -0.1313 & 0.448001 \tabularnewline
29 & 0.027954 & 0.2165 & 0.414654 \tabularnewline
30 & -0.035039 & -0.2714 & 0.393504 \tabularnewline
31 & 0.00614 & 0.0476 & 0.481112 \tabularnewline
32 & -0.009169 & -0.071 & 0.471807 \tabularnewline
33 & 0.021587 & 0.1672 & 0.433881 \tabularnewline
34 & 0.039528 & 0.3062 & 0.380263 \tabularnewline
35 & -0.08669 & -0.6715 & 0.252239 \tabularnewline
36 & -0.163316 & -1.265 & 0.105374 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69242&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]0.241678[/C][C]1.872[/C][C]0.03304[/C][/ROW]
[ROW][C]2[/C][C]-0.33139[/C][C]-2.5669[/C][C]0.006386[/C][/ROW]
[ROW][C]3[/C][C]-0.130529[/C][C]-1.0111[/C][C]0.158021[/C][/ROW]
[ROW][C]4[/C][C]-0.169981[/C][C]-1.3167[/C][C]0.096479[/C][/ROW]
[ROW][C]5[/C][C]0.071934[/C][C]0.5572[/C][C]0.289732[/C][/ROW]
[ROW][C]6[/C][C]0.080296[/C][C]0.622[/C][C]0.26816[/C][/ROW]
[ROW][C]7[/C][C]-0.004881[/C][C]-0.0378[/C][C]0.484984[/C][/ROW]
[ROW][C]8[/C][C]-0.204669[/C][C]-1.5854[/C][C]0.059071[/C][/ROW]
[ROW][C]9[/C][C]-0.12563[/C][C]-0.9731[/C][C]0.167199[/C][/ROW]
[ROW][C]10[/C][C]-0.243725[/C][C]-1.8879[/C][C]0.03194[/C][/ROW]
[ROW][C]11[/C][C]0.252297[/C][C]1.9543[/C][C]0.027666[/C][/ROW]
[ROW][C]12[/C][C]0.598931[/C][C]4.6393[/C][C]1e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.193654[/C][C]-1.5[/C][C]0.069424[/C][/ROW]
[ROW][C]14[/C][C]0.058468[/C][C]0.4529[/C][C]0.326129[/C][/ROW]
[ROW][C]15[/C][C]-0.023664[/C][C]-0.1833[/C][C]0.427589[/C][/ROW]
[ROW][C]16[/C][C]-0.101129[/C][C]-0.7833[/C][C]0.218253[/C][/ROW]
[ROW][C]17[/C][C]-0.089341[/C][C]-0.692[/C][C]0.245793[/C][/ROW]
[ROW][C]18[/C][C]-0.17392[/C][C]-1.3472[/C][C]0.091494[/C][/ROW]
[ROW][C]19[/C][C]-0.053345[/C][C]-0.4132[/C][C]0.340462[/C][/ROW]
[ROW][C]20[/C][C]-0.032052[/C][C]-0.2483[/C][C]0.402385[/C][/ROW]
[ROW][C]21[/C][C]-0.022062[/C][C]-0.1709[/C][C]0.432442[/C][/ROW]
[ROW][C]22[/C][C]-0.012292[/C][C]-0.0952[/C][C]0.46223[/C][/ROW]
[ROW][C]23[/C][C]-0.105422[/C][C]-0.8166[/C][C]0.208695[/C][/ROW]
[ROW][C]24[/C][C]-0.041117[/C][C]-0.3185[/C][C]0.37561[/C][/ROW]
[ROW][C]25[/C][C]-0.044783[/C][C]-0.3469[/C][C]0.364943[/C][/ROW]
[ROW][C]26[/C][C]-0.070103[/C][C]-0.543[/C][C]0.294566[/C][/ROW]
[ROW][C]27[/C][C]0.100982[/C][C]0.7822[/C][C]0.218585[/C][/ROW]
[ROW][C]28[/C][C]-0.016947[/C][C]-0.1313[/C][C]0.448001[/C][/ROW]
[ROW][C]29[/C][C]0.027954[/C][C]0.2165[/C][C]0.414654[/C][/ROW]
[ROW][C]30[/C][C]-0.035039[/C][C]-0.2714[/C][C]0.393504[/C][/ROW]
[ROW][C]31[/C][C]0.00614[/C][C]0.0476[/C][C]0.481112[/C][/ROW]
[ROW][C]32[/C][C]-0.009169[/C][C]-0.071[/C][C]0.471807[/C][/ROW]
[ROW][C]33[/C][C]0.021587[/C][C]0.1672[/C][C]0.433881[/C][/ROW]
[ROW][C]34[/C][C]0.039528[/C][C]0.3062[/C][C]0.380263[/C][/ROW]
[ROW][C]35[/C][C]-0.08669[/C][C]-0.6715[/C][C]0.252239[/C][/ROW]
[ROW][C]36[/C][C]-0.163316[/C][C]-1.265[/C][C]0.105374[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69242&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69242&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
10.2416781.8720.03304
2-0.33139-2.56690.006386
3-0.130529-1.01110.158021
4-0.169981-1.31670.096479
50.0719340.55720.289732
60.0802960.6220.26816
7-0.004881-0.03780.484984
8-0.204669-1.58540.059071
9-0.12563-0.97310.167199
10-0.243725-1.88790.03194
110.2522971.95430.027666
120.5989314.63931e-05
13-0.193654-1.50.069424
140.0584680.45290.326129
15-0.023664-0.18330.427589
16-0.101129-0.78330.218253
17-0.089341-0.6920.245793
18-0.17392-1.34720.091494
19-0.053345-0.41320.340462
20-0.032052-0.24830.402385
21-0.022062-0.17090.432442
22-0.012292-0.09520.46223
23-0.105422-0.81660.208695
24-0.041117-0.31850.37561
25-0.044783-0.34690.364943
26-0.070103-0.5430.294566
270.1009820.78220.218585
28-0.016947-0.13130.448001
290.0279540.21650.414654
30-0.035039-0.27140.393504
310.006140.04760.481112
32-0.009169-0.0710.471807
330.0215870.16720.433881
340.0395280.30620.380263
35-0.08669-0.67150.252239
36-0.163316-1.2650.105374


Figures (Output of Computation)

Input Parameters & R Code

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