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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, 24 Nov 2009 15:56:18 -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/24/t1259103414quex2iqkx670wbm.htm/, Retrieved Thu, 30 May 2024 15:22:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59295, Retrieved Thu, 30 May 2024 15:22:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [Correlatie tussen...] [2007-11-03 21:44:17] [0b2d8ed757c467aee7199cdee05779c9]
- RMPD  [(Partial) Autocorrelation Function] [WS 8 01] [2009-11-21 08:59:55] [6e4e01d7eb22a9f33d58ebb35753a195]
-   PD    [(Partial) Autocorrelation Function] [WS 8 02] [2009-11-21 11:01:08] [6e4e01d7eb22a9f33d58ebb35753a195]
-   P       [(Partial) Autocorrelation Function] [WS 8 03] [2009-11-21 11:02:54] [6e4e01d7eb22a9f33d58ebb35753a195]
-   P         [(Partial) Autocorrelation Function] [WS 8 04] [2009-11-21 11:06:04] [6e4e01d7eb22a9f33d58ebb35753a195]
-   P             [(Partial) Autocorrelation Function] [ws 8 01b] [2009-11-24 22:56:18] [2e4ef2c1b76db9b31c0a03b96e94ad77] [Current]
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Dataseries X:
103.63
103.64
103.66
103.77
103.88
103.91
103.91
103.92
104.05
104.23
104.30
104.31
104.31
104.34
104.55
104.65
104.73
104.75
104.75
104.76
104.94
105.29
105.38
105.43
105.43
105.42
105.52
105.69
105.72
105.74
105.74
105.74
105.95
106.17
106.34
106.37
106.37
106.36
106.44
106.29
106.23
106.23
106.23
106.23
106.34
106.44
106.44
106.48
106.50
106.57
106.40
106.37
106.25
106.21
106.21
106.24
106.19
106.08
106.13
106.09




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59295&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]3 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=59295&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59295&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.416323.19780.001114
20.0766970.58910.279014
3-0.112083-0.86090.196383
4-0.00739-0.05680.477462
50.1725411.32530.095089
60.3148492.41840.009347
70.1706641.31090.097486
8-0.151973-1.16730.123888
9-0.11594-0.89060.188394
10-0.011391-0.08750.465286
110.384212.95120.002268
120.3748972.87960.00277
130.2713032.08390.020754
14-0.019703-0.15130.44011
15-0.095952-0.7370.232016
16-0.078996-0.60680.273164
170.1159670.89080.188338
180.0347860.26720.395126
19-0.11715-0.89980.185931
20-0.106703-0.81960.20787
21-0.123287-0.9470.173754
22-0.051185-0.39320.34781
23-0.001978-0.01520.493965
240.0436530.33530.369291
25-0.124832-0.95890.170772
26-0.103557-0.79540.214774
27-0.088949-0.68320.248567
280.0147420.11320.455113
29-0.081337-0.62480.267268
30-0.136832-1.0510.148766
31-0.165966-1.27480.103688
32-0.142771-1.09660.138627
33-0.053127-0.40810.342347
34-0.019919-0.1530.43946
35-0.061795-0.47470.318393
36-0.210326-1.61550.055764

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.41632 & 3.1978 & 0.001114 \tabularnewline
2 & 0.076697 & 0.5891 & 0.279014 \tabularnewline
3 & -0.112083 & -0.8609 & 0.196383 \tabularnewline
4 & -0.00739 & -0.0568 & 0.477462 \tabularnewline
5 & 0.172541 & 1.3253 & 0.095089 \tabularnewline
6 & 0.314849 & 2.4184 & 0.009347 \tabularnewline
7 & 0.170664 & 1.3109 & 0.097486 \tabularnewline
8 & -0.151973 & -1.1673 & 0.123888 \tabularnewline
9 & -0.11594 & -0.8906 & 0.188394 \tabularnewline
10 & -0.011391 & -0.0875 & 0.465286 \tabularnewline
11 & 0.38421 & 2.9512 & 0.002268 \tabularnewline
12 & 0.374897 & 2.8796 & 0.00277 \tabularnewline
13 & 0.271303 & 2.0839 & 0.020754 \tabularnewline
14 & -0.019703 & -0.1513 & 0.44011 \tabularnewline
15 & -0.095952 & -0.737 & 0.232016 \tabularnewline
16 & -0.078996 & -0.6068 & 0.273164 \tabularnewline
17 & 0.115967 & 0.8908 & 0.188338 \tabularnewline
18 & 0.034786 & 0.2672 & 0.395126 \tabularnewline
19 & -0.11715 & -0.8998 & 0.185931 \tabularnewline
20 & -0.106703 & -0.8196 & 0.20787 \tabularnewline
21 & -0.123287 & -0.947 & 0.173754 \tabularnewline
22 & -0.051185 & -0.3932 & 0.34781 \tabularnewline
23 & -0.001978 & -0.0152 & 0.493965 \tabularnewline
24 & 0.043653 & 0.3353 & 0.369291 \tabularnewline
25 & -0.124832 & -0.9589 & 0.170772 \tabularnewline
26 & -0.103557 & -0.7954 & 0.214774 \tabularnewline
27 & -0.088949 & -0.6832 & 0.248567 \tabularnewline
28 & 0.014742 & 0.1132 & 0.455113 \tabularnewline
29 & -0.081337 & -0.6248 & 0.267268 \tabularnewline
30 & -0.136832 & -1.051 & 0.148766 \tabularnewline
31 & -0.165966 & -1.2748 & 0.103688 \tabularnewline
32 & -0.142771 & -1.0966 & 0.138627 \tabularnewline
33 & -0.053127 & -0.4081 & 0.342347 \tabularnewline
34 & -0.019919 & -0.153 & 0.43946 \tabularnewline
35 & -0.061795 & -0.4747 & 0.318393 \tabularnewline
36 & -0.210326 & -1.6155 & 0.055764 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59295&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]0.41632[/C][C]3.1978[/C][C]0.001114[/C][/ROW]
[ROW][C]2[/C][C]0.076697[/C][C]0.5891[/C][C]0.279014[/C][/ROW]
[ROW][C]3[/C][C]-0.112083[/C][C]-0.8609[/C][C]0.196383[/C][/ROW]
[ROW][C]4[/C][C]-0.00739[/C][C]-0.0568[/C][C]0.477462[/C][/ROW]
[ROW][C]5[/C][C]0.172541[/C][C]1.3253[/C][C]0.095089[/C][/ROW]
[ROW][C]6[/C][C]0.314849[/C][C]2.4184[/C][C]0.009347[/C][/ROW]
[ROW][C]7[/C][C]0.170664[/C][C]1.3109[/C][C]0.097486[/C][/ROW]
[ROW][C]8[/C][C]-0.151973[/C][C]-1.1673[/C][C]0.123888[/C][/ROW]
[ROW][C]9[/C][C]-0.11594[/C][C]-0.8906[/C][C]0.188394[/C][/ROW]
[ROW][C]10[/C][C]-0.011391[/C][C]-0.0875[/C][C]0.465286[/C][/ROW]
[ROW][C]11[/C][C]0.38421[/C][C]2.9512[/C][C]0.002268[/C][/ROW]
[ROW][C]12[/C][C]0.374897[/C][C]2.8796[/C][C]0.00277[/C][/ROW]
[ROW][C]13[/C][C]0.271303[/C][C]2.0839[/C][C]0.020754[/C][/ROW]
[ROW][C]14[/C][C]-0.019703[/C][C]-0.1513[/C][C]0.44011[/C][/ROW]
[ROW][C]15[/C][C]-0.095952[/C][C]-0.737[/C][C]0.232016[/C][/ROW]
[ROW][C]16[/C][C]-0.078996[/C][C]-0.6068[/C][C]0.273164[/C][/ROW]
[ROW][C]17[/C][C]0.115967[/C][C]0.8908[/C][C]0.188338[/C][/ROW]
[ROW][C]18[/C][C]0.034786[/C][C]0.2672[/C][C]0.395126[/C][/ROW]
[ROW][C]19[/C][C]-0.11715[/C][C]-0.8998[/C][C]0.185931[/C][/ROW]
[ROW][C]20[/C][C]-0.106703[/C][C]-0.8196[/C][C]0.20787[/C][/ROW]
[ROW][C]21[/C][C]-0.123287[/C][C]-0.947[/C][C]0.173754[/C][/ROW]
[ROW][C]22[/C][C]-0.051185[/C][C]-0.3932[/C][C]0.34781[/C][/ROW]
[ROW][C]23[/C][C]-0.001978[/C][C]-0.0152[/C][C]0.493965[/C][/ROW]
[ROW][C]24[/C][C]0.043653[/C][C]0.3353[/C][C]0.369291[/C][/ROW]
[ROW][C]25[/C][C]-0.124832[/C][C]-0.9589[/C][C]0.170772[/C][/ROW]
[ROW][C]26[/C][C]-0.103557[/C][C]-0.7954[/C][C]0.214774[/C][/ROW]
[ROW][C]27[/C][C]-0.088949[/C][C]-0.6832[/C][C]0.248567[/C][/ROW]
[ROW][C]28[/C][C]0.014742[/C][C]0.1132[/C][C]0.455113[/C][/ROW]
[ROW][C]29[/C][C]-0.081337[/C][C]-0.6248[/C][C]0.267268[/C][/ROW]
[ROW][C]30[/C][C]-0.136832[/C][C]-1.051[/C][C]0.148766[/C][/ROW]
[ROW][C]31[/C][C]-0.165966[/C][C]-1.2748[/C][C]0.103688[/C][/ROW]
[ROW][C]32[/C][C]-0.142771[/C][C]-1.0966[/C][C]0.138627[/C][/ROW]
[ROW][C]33[/C][C]-0.053127[/C][C]-0.4081[/C][C]0.342347[/C][/ROW]
[ROW][C]34[/C][C]-0.019919[/C][C]-0.153[/C][C]0.43946[/C][/ROW]
[ROW][C]35[/C][C]-0.061795[/C][C]-0.4747[/C][C]0.318393[/C][/ROW]
[ROW][C]36[/C][C]-0.210326[/C][C]-1.6155[/C][C]0.055764[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59295&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59295&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
10.416323.19780.001114
20.0766970.58910.279014
3-0.112083-0.86090.196383
4-0.00739-0.05680.477462
50.1725411.32530.095089
60.3148492.41840.009347
70.1706641.31090.097486
8-0.151973-1.16730.123888
9-0.11594-0.89060.188394
10-0.011391-0.08750.465286
110.384212.95120.002268
120.3748972.87960.00277
130.2713032.08390.020754
14-0.019703-0.15130.44011
15-0.095952-0.7370.232016
16-0.078996-0.60680.273164
170.1159670.89080.188338
180.0347860.26720.395126
19-0.11715-0.89980.185931
20-0.106703-0.81960.20787
21-0.123287-0.9470.173754
22-0.051185-0.39320.34781
23-0.001978-0.01520.493965
240.0436530.33530.369291
25-0.124832-0.95890.170772
26-0.103557-0.79540.214774
27-0.088949-0.68320.248567
280.0147420.11320.455113
29-0.081337-0.62480.267268
30-0.136832-1.0510.148766
31-0.165966-1.27480.103688
32-0.142771-1.09660.138627
33-0.053127-0.40810.342347
34-0.019919-0.1530.43946
35-0.061795-0.47470.318393
36-0.210326-1.61550.055764







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.416323.19780.001114
2-0.116884-0.89780.186471
3-0.121519-0.93340.177208
40.1224330.94040.175417
50.1676031.28740.101494
60.1896841.4570.075211
7-0.047036-0.36130.359587
8-0.242216-1.86050.0339
90.127860.98210.165027
100.0306220.23520.40743
110.3791012.91190.002532
120.0163690.12570.450185
130.1045650.80320.212548
14-0.044164-0.33920.36782
15-0.020599-0.15820.43741
16-0.148269-1.13890.129679
170.0169110.12990.448546
18-0.30509-2.34340.011248
19-0.004059-0.03120.487618
200.0656850.50450.307882
210.0602260.46260.322674
22-0.194641-1.49510.070114
23-0.092736-0.71230.239537
24-0.135252-1.03890.151547
25-0.074269-0.57050.285261
26-0.096898-0.74430.229829
270.0712590.54730.293102
280.0662540.50890.306358
29-0.004293-0.0330.486902
30-0.003117-0.02390.49049
310.0167050.12830.44917
32-0.061761-0.47440.318484
330.0150710.11580.454116
34-0.011424-0.08780.465185
350.0225940.17350.431407
36-0.006888-0.05290.478992

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.41632 & 3.1978 & 0.001114 \tabularnewline
2 & -0.116884 & -0.8978 & 0.186471 \tabularnewline
3 & -0.121519 & -0.9334 & 0.177208 \tabularnewline
4 & 0.122433 & 0.9404 & 0.175417 \tabularnewline
5 & 0.167603 & 1.2874 & 0.101494 \tabularnewline
6 & 0.189684 & 1.457 & 0.075211 \tabularnewline
7 & -0.047036 & -0.3613 & 0.359587 \tabularnewline
8 & -0.242216 & -1.8605 & 0.0339 \tabularnewline
9 & 0.12786 & 0.9821 & 0.165027 \tabularnewline
10 & 0.030622 & 0.2352 & 0.40743 \tabularnewline
11 & 0.379101 & 2.9119 & 0.002532 \tabularnewline
12 & 0.016369 & 0.1257 & 0.450185 \tabularnewline
13 & 0.104565 & 0.8032 & 0.212548 \tabularnewline
14 & -0.044164 & -0.3392 & 0.36782 \tabularnewline
15 & -0.020599 & -0.1582 & 0.43741 \tabularnewline
16 & -0.148269 & -1.1389 & 0.129679 \tabularnewline
17 & 0.016911 & 0.1299 & 0.448546 \tabularnewline
18 & -0.30509 & -2.3434 & 0.011248 \tabularnewline
19 & -0.004059 & -0.0312 & 0.487618 \tabularnewline
20 & 0.065685 & 0.5045 & 0.307882 \tabularnewline
21 & 0.060226 & 0.4626 & 0.322674 \tabularnewline
22 & -0.194641 & -1.4951 & 0.070114 \tabularnewline
23 & -0.092736 & -0.7123 & 0.239537 \tabularnewline
24 & -0.135252 & -1.0389 & 0.151547 \tabularnewline
25 & -0.074269 & -0.5705 & 0.285261 \tabularnewline
26 & -0.096898 & -0.7443 & 0.229829 \tabularnewline
27 & 0.071259 & 0.5473 & 0.293102 \tabularnewline
28 & 0.066254 & 0.5089 & 0.306358 \tabularnewline
29 & -0.004293 & -0.033 & 0.486902 \tabularnewline
30 & -0.003117 & -0.0239 & 0.49049 \tabularnewline
31 & 0.016705 & 0.1283 & 0.44917 \tabularnewline
32 & -0.061761 & -0.4744 & 0.318484 \tabularnewline
33 & 0.015071 & 0.1158 & 0.454116 \tabularnewline
34 & -0.011424 & -0.0878 & 0.465185 \tabularnewline
35 & 0.022594 & 0.1735 & 0.431407 \tabularnewline
36 & -0.006888 & -0.0529 & 0.478992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59295&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]0.41632[/C][C]3.1978[/C][C]0.001114[/C][/ROW]
[ROW][C]2[/C][C]-0.116884[/C][C]-0.8978[/C][C]0.186471[/C][/ROW]
[ROW][C]3[/C][C]-0.121519[/C][C]-0.9334[/C][C]0.177208[/C][/ROW]
[ROW][C]4[/C][C]0.122433[/C][C]0.9404[/C][C]0.175417[/C][/ROW]
[ROW][C]5[/C][C]0.167603[/C][C]1.2874[/C][C]0.101494[/C][/ROW]
[ROW][C]6[/C][C]0.189684[/C][C]1.457[/C][C]0.075211[/C][/ROW]
[ROW][C]7[/C][C]-0.047036[/C][C]-0.3613[/C][C]0.359587[/C][/ROW]
[ROW][C]8[/C][C]-0.242216[/C][C]-1.8605[/C][C]0.0339[/C][/ROW]
[ROW][C]9[/C][C]0.12786[/C][C]0.9821[/C][C]0.165027[/C][/ROW]
[ROW][C]10[/C][C]0.030622[/C][C]0.2352[/C][C]0.40743[/C][/ROW]
[ROW][C]11[/C][C]0.379101[/C][C]2.9119[/C][C]0.002532[/C][/ROW]
[ROW][C]12[/C][C]0.016369[/C][C]0.1257[/C][C]0.450185[/C][/ROW]
[ROW][C]13[/C][C]0.104565[/C][C]0.8032[/C][C]0.212548[/C][/ROW]
[ROW][C]14[/C][C]-0.044164[/C][C]-0.3392[/C][C]0.36782[/C][/ROW]
[ROW][C]15[/C][C]-0.020599[/C][C]-0.1582[/C][C]0.43741[/C][/ROW]
[ROW][C]16[/C][C]-0.148269[/C][C]-1.1389[/C][C]0.129679[/C][/ROW]
[ROW][C]17[/C][C]0.016911[/C][C]0.1299[/C][C]0.448546[/C][/ROW]
[ROW][C]18[/C][C]-0.30509[/C][C]-2.3434[/C][C]0.011248[/C][/ROW]
[ROW][C]19[/C][C]-0.004059[/C][C]-0.0312[/C][C]0.487618[/C][/ROW]
[ROW][C]20[/C][C]0.065685[/C][C]0.5045[/C][C]0.307882[/C][/ROW]
[ROW][C]21[/C][C]0.060226[/C][C]0.4626[/C][C]0.322674[/C][/ROW]
[ROW][C]22[/C][C]-0.194641[/C][C]-1.4951[/C][C]0.070114[/C][/ROW]
[ROW][C]23[/C][C]-0.092736[/C][C]-0.7123[/C][C]0.239537[/C][/ROW]
[ROW][C]24[/C][C]-0.135252[/C][C]-1.0389[/C][C]0.151547[/C][/ROW]
[ROW][C]25[/C][C]-0.074269[/C][C]-0.5705[/C][C]0.285261[/C][/ROW]
[ROW][C]26[/C][C]-0.096898[/C][C]-0.7443[/C][C]0.229829[/C][/ROW]
[ROW][C]27[/C][C]0.071259[/C][C]0.5473[/C][C]0.293102[/C][/ROW]
[ROW][C]28[/C][C]0.066254[/C][C]0.5089[/C][C]0.306358[/C][/ROW]
[ROW][C]29[/C][C]-0.004293[/C][C]-0.033[/C][C]0.486902[/C][/ROW]
[ROW][C]30[/C][C]-0.003117[/C][C]-0.0239[/C][C]0.49049[/C][/ROW]
[ROW][C]31[/C][C]0.016705[/C][C]0.1283[/C][C]0.44917[/C][/ROW]
[ROW][C]32[/C][C]-0.061761[/C][C]-0.4744[/C][C]0.318484[/C][/ROW]
[ROW][C]33[/C][C]0.015071[/C][C]0.1158[/C][C]0.454116[/C][/ROW]
[ROW][C]34[/C][C]-0.011424[/C][C]-0.0878[/C][C]0.465185[/C][/ROW]
[ROW][C]35[/C][C]0.022594[/C][C]0.1735[/C][C]0.431407[/C][/ROW]
[ROW][C]36[/C][C]-0.006888[/C][C]-0.0529[/C][C]0.478992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59295&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59295&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
10.416323.19780.001114
2-0.116884-0.89780.186471
3-0.121519-0.93340.177208
40.1224330.94040.175417
50.1676031.28740.101494
60.1896841.4570.075211
7-0.047036-0.36130.359587
8-0.242216-1.86050.0339
90.127860.98210.165027
100.0306220.23520.40743
110.3791012.91190.002532
120.0163690.12570.450185
130.1045650.80320.212548
14-0.044164-0.33920.36782
15-0.020599-0.15820.43741
16-0.148269-1.13890.129679
170.0169110.12990.448546
18-0.30509-2.34340.011248
19-0.004059-0.03120.487618
200.0656850.50450.307882
210.0602260.46260.322674
22-0.194641-1.49510.070114
23-0.092736-0.71230.239537
24-0.135252-1.03890.151547
25-0.074269-0.57050.285261
26-0.096898-0.74430.229829
270.0712590.54730.293102
280.0662540.50890.306358
29-0.004293-0.0330.486902
30-0.003117-0.02390.49049
310.0167050.12830.44917
32-0.061761-0.47440.318484
330.0150710.11580.454116
34-0.011424-0.08780.465185
350.0225940.17350.431407
36-0.006888-0.05290.478992



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')