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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 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, 25 Apr 2024 01:43:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59295, Retrieved Thu, 25 Apr 2024 01:43:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160

Tree of Dependent Computations

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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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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:  
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:  
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:  
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


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')