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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 computationMon, 21 Dec 2009 07:20:57 -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/21/t1261405339ri6e91xowcx2ocm.htm/, Retrieved Sun, 05 May 2024 16:53:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70188, Retrieved Sun, 05 May 2024 16:53:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsShw; Paper; toepassing ACF d=D=0
Estimated Impact111

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Ws8.1 ACF1] [2009-11-25 19:12:20] [e0fc65a5811681d807296d590d5b45de]
-    D          [(Partial) Autocorrelation Function] [Paper stationair ...] [2009-12-19 17:48:37] [e0fc65a5811681d807296d590d5b45de]
-    D              [(Partial) Autocorrelation Function] [Paper; toepassing...] [2009-12-21 14:20:57] [51108381f3361ca8af49c4f74052c840] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.1
103.1
103.3
103.5
103.3
103.5
103.8
103.9
103.9
104.2
104.6
104.9
105.2
105.2
105.6
105.6
106.2
106.3
106.4
106.9
107.2
107.3
107.3
107.4
107.55
107.87
108.37
108.38
107.92
108.03
108.14
108.3
108.64
108.66
109.04
109.03
109.03
109.54
109.75
109.83
109.65
109.82
109.95
110.12
110.15
110.2
109.99
110.14
110.14
110.81
110.97
110.99
109.73
109.81
110.02
110.18
110.21
110.25
110.36
110.51
110.64
110.95
111.18
111.19
111.69
111.7
111.83
111.77
111.73
112.01
111.86
112.04

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=70188&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=70188&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70188&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
10.9544428.09870
20.9079237.7040
30.8608277.30440
40.8176666.93810
50.7696276.53050
60.7199316.10880
70.6710335.69390
80.6204215.26441e-06
90.5714114.84863e-06
100.5251684.45621.5e-05
110.4828734.09735.4e-05
120.443513.76330.00017
130.4062693.44730.000475
140.3677753.12070.001298
150.3334432.82940.003019
160.2978352.52720.006847
170.2667062.26310.013324
180.2359622.00220.024515
190.2060171.74810.042353
200.1810241.5360.064456
210.1489451.26380.105182
220.1174830.99690.161082
230.0858530.72850.234339
240.0577360.48990.312845
250.0278140.2360.407048
260.0007070.0060.497613
27-0.022534-0.19120.424452
28-0.04648-0.39440.347229
29-0.076289-0.64730.259738
30-0.1052-0.89270.187508
31-0.133649-1.1340.130268
32-0.160412-1.36110.088857
33-0.185927-1.57760.059516
34-0.210666-1.78760.039028
35-0.230703-1.95760.027078
36-0.248908-2.11210.019076

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.954442 & 8.0987 & 0 \tabularnewline
2 & 0.907923 & 7.704 & 0 \tabularnewline
3 & 0.860827 & 7.3044 & 0 \tabularnewline
4 & 0.817666 & 6.9381 & 0 \tabularnewline
5 & 0.769627 & 6.5305 & 0 \tabularnewline
6 & 0.719931 & 6.1088 & 0 \tabularnewline
7 & 0.671033 & 5.6939 & 0 \tabularnewline
8 & 0.620421 & 5.2644 & 1e-06 \tabularnewline
9 & 0.571411 & 4.8486 & 3e-06 \tabularnewline
10 & 0.525168 & 4.4562 & 1.5e-05 \tabularnewline
11 & 0.482873 & 4.0973 & 5.4e-05 \tabularnewline
12 & 0.44351 & 3.7633 & 0.00017 \tabularnewline
13 & 0.406269 & 3.4473 & 0.000475 \tabularnewline
14 & 0.367775 & 3.1207 & 0.001298 \tabularnewline
15 & 0.333443 & 2.8294 & 0.003019 \tabularnewline
16 & 0.297835 & 2.5272 & 0.006847 \tabularnewline
17 & 0.266706 & 2.2631 & 0.013324 \tabularnewline
18 & 0.235962 & 2.0022 & 0.024515 \tabularnewline
19 & 0.206017 & 1.7481 & 0.042353 \tabularnewline
20 & 0.181024 & 1.536 & 0.064456 \tabularnewline
21 & 0.148945 & 1.2638 & 0.105182 \tabularnewline
22 & 0.117483 & 0.9969 & 0.161082 \tabularnewline
23 & 0.085853 & 0.7285 & 0.234339 \tabularnewline
24 & 0.057736 & 0.4899 & 0.312845 \tabularnewline
25 & 0.027814 & 0.236 & 0.407048 \tabularnewline
26 & 0.000707 & 0.006 & 0.497613 \tabularnewline
27 & -0.022534 & -0.1912 & 0.424452 \tabularnewline
28 & -0.04648 & -0.3944 & 0.347229 \tabularnewline
29 & -0.076289 & -0.6473 & 0.259738 \tabularnewline
30 & -0.1052 & -0.8927 & 0.187508 \tabularnewline
31 & -0.133649 & -1.134 & 0.130268 \tabularnewline
32 & -0.160412 & -1.3611 & 0.088857 \tabularnewline
33 & -0.185927 & -1.5776 & 0.059516 \tabularnewline
34 & -0.210666 & -1.7876 & 0.039028 \tabularnewline
35 & -0.230703 & -1.9576 & 0.027078 \tabularnewline
36 & -0.248908 & -2.1121 & 0.019076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70188&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]0.954442[/C][C]8.0987[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.907923[/C][C]7.704[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.860827[/C][C]7.3044[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.817666[/C][C]6.9381[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.769627[/C][C]6.5305[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.719931[/C][C]6.1088[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.671033[/C][C]5.6939[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.620421[/C][C]5.2644[/C][C]1e-06[/C][/ROW]
[ROW][C]9[/C][C]0.571411[/C][C]4.8486[/C][C]3e-06[/C][/ROW]
[ROW][C]10[/C][C]0.525168[/C][C]4.4562[/C][C]1.5e-05[/C][/ROW]
[ROW][C]11[/C][C]0.482873[/C][C]4.0973[/C][C]5.4e-05[/C][/ROW]
[ROW][C]12[/C][C]0.44351[/C][C]3.7633[/C][C]0.00017[/C][/ROW]
[ROW][C]13[/C][C]0.406269[/C][C]3.4473[/C][C]0.000475[/C][/ROW]
[ROW][C]14[/C][C]0.367775[/C][C]3.1207[/C][C]0.001298[/C][/ROW]
[ROW][C]15[/C][C]0.333443[/C][C]2.8294[/C][C]0.003019[/C][/ROW]
[ROW][C]16[/C][C]0.297835[/C][C]2.5272[/C][C]0.006847[/C][/ROW]
[ROW][C]17[/C][C]0.266706[/C][C]2.2631[/C][C]0.013324[/C][/ROW]
[ROW][C]18[/C][C]0.235962[/C][C]2.0022[/C][C]0.024515[/C][/ROW]
[ROW][C]19[/C][C]0.206017[/C][C]1.7481[/C][C]0.042353[/C][/ROW]
[ROW][C]20[/C][C]0.181024[/C][C]1.536[/C][C]0.064456[/C][/ROW]
[ROW][C]21[/C][C]0.148945[/C][C]1.2638[/C][C]0.105182[/C][/ROW]
[ROW][C]22[/C][C]0.117483[/C][C]0.9969[/C][C]0.161082[/C][/ROW]
[ROW][C]23[/C][C]0.085853[/C][C]0.7285[/C][C]0.234339[/C][/ROW]
[ROW][C]24[/C][C]0.057736[/C][C]0.4899[/C][C]0.312845[/C][/ROW]
[ROW][C]25[/C][C]0.027814[/C][C]0.236[/C][C]0.407048[/C][/ROW]
[ROW][C]26[/C][C]0.000707[/C][C]0.006[/C][C]0.497613[/C][/ROW]
[ROW][C]27[/C][C]-0.022534[/C][C]-0.1912[/C][C]0.424452[/C][/ROW]
[ROW][C]28[/C][C]-0.04648[/C][C]-0.3944[/C][C]0.347229[/C][/ROW]
[ROW][C]29[/C][C]-0.076289[/C][C]-0.6473[/C][C]0.259738[/C][/ROW]
[ROW][C]30[/C][C]-0.1052[/C][C]-0.8927[/C][C]0.187508[/C][/ROW]
[ROW][C]31[/C][C]-0.133649[/C][C]-1.134[/C][C]0.130268[/C][/ROW]
[ROW][C]32[/C][C]-0.160412[/C][C]-1.3611[/C][C]0.088857[/C][/ROW]
[ROW][C]33[/C][C]-0.185927[/C][C]-1.5776[/C][C]0.059516[/C][/ROW]
[ROW][C]34[/C][C]-0.210666[/C][C]-1.7876[/C][C]0.039028[/C][/ROW]
[ROW][C]35[/C][C]-0.230703[/C][C]-1.9576[/C][C]0.027078[/C][/ROW]
[ROW][C]36[/C][C]-0.248908[/C][C]-2.1121[/C][C]0.019076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70188&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70188&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
10.9544428.09870
20.9079237.7040
30.8608277.30440
40.8176666.93810
50.7696276.53050
60.7199316.10880
70.6710335.69390
80.6204215.26441e-06
90.5714114.84863e-06
100.5251684.45621.5e-05
110.4828734.09735.4e-05
120.443513.76330.00017
130.4062693.44730.000475
140.3677753.12070.001298
150.3334432.82940.003019
160.2978352.52720.006847
170.2667062.26310.013324
180.2359622.00220.024515
190.2060171.74810.042353
200.1810241.5360.064456
210.1489451.26380.105182
220.1174830.99690.161082
230.0858530.72850.234339
240.0577360.48990.312845
250.0278140.2360.407048
260.0007070.0060.497613
27-0.022534-0.19120.424452
28-0.04648-0.39440.347229
29-0.076289-0.64730.259738
30-0.1052-0.89270.187508
31-0.133649-1.1340.130268
32-0.160412-1.36110.088857
33-0.185927-1.57760.059516
34-0.210666-1.78760.039028
35-0.230703-1.95760.027078
36-0.248908-2.11210.019076






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9544428.09870
2-0.034093-0.28930.386597
3-0.030778-0.26120.397356
40.0191190.16220.435788
5-0.079594-0.67540.2508
6-0.045265-0.38410.351024
7-0.016811-0.14260.443483
8-0.053523-0.45420.325542
9-0.011497-0.09760.461277
100.0030010.02550.489878
110.0108860.09240.463332
120.0069890.05930.476437
13-0.002869-0.02430.490322
14-0.042993-0.36480.358161
150.0169370.14370.443065
16-0.045543-0.38640.350153
170.0168520.1430.443349
18-0.018282-0.15510.438576
19-0.023066-0.19570.42269
200.0360690.30610.380224
21-0.105324-0.89370.187228
22-0.021602-0.18330.427541
23-0.021789-0.18490.42692
24-0.004701-0.03990.484146
25-0.040159-0.34080.367137
260.0085380.07240.471225
270.0175450.14890.441036
28-0.035473-0.3010.382141
29-0.087791-0.74490.229368
30-0.023059-0.19570.422712
31-0.034711-0.29450.384598
32-0.024427-0.20730.418191
33-0.014017-0.11890.452827
34-0.016917-0.14350.44313
350.0153620.13030.448328
360.0035540.03020.488013

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.954442 & 8.0987 & 0 \tabularnewline
2 & -0.034093 & -0.2893 & 0.386597 \tabularnewline
3 & -0.030778 & -0.2612 & 0.397356 \tabularnewline
4 & 0.019119 & 0.1622 & 0.435788 \tabularnewline
5 & -0.079594 & -0.6754 & 0.2508 \tabularnewline
6 & -0.045265 & -0.3841 & 0.351024 \tabularnewline
7 & -0.016811 & -0.1426 & 0.443483 \tabularnewline
8 & -0.053523 & -0.4542 & 0.325542 \tabularnewline
9 & -0.011497 & -0.0976 & 0.461277 \tabularnewline
10 & 0.003001 & 0.0255 & 0.489878 \tabularnewline
11 & 0.010886 & 0.0924 & 0.463332 \tabularnewline
12 & 0.006989 & 0.0593 & 0.476437 \tabularnewline
13 & -0.002869 & -0.0243 & 0.490322 \tabularnewline
14 & -0.042993 & -0.3648 & 0.358161 \tabularnewline
15 & 0.016937 & 0.1437 & 0.443065 \tabularnewline
16 & -0.045543 & -0.3864 & 0.350153 \tabularnewline
17 & 0.016852 & 0.143 & 0.443349 \tabularnewline
18 & -0.018282 & -0.1551 & 0.438576 \tabularnewline
19 & -0.023066 & -0.1957 & 0.42269 \tabularnewline
20 & 0.036069 & 0.3061 & 0.380224 \tabularnewline
21 & -0.105324 & -0.8937 & 0.187228 \tabularnewline
22 & -0.021602 & -0.1833 & 0.427541 \tabularnewline
23 & -0.021789 & -0.1849 & 0.42692 \tabularnewline
24 & -0.004701 & -0.0399 & 0.484146 \tabularnewline
25 & -0.040159 & -0.3408 & 0.367137 \tabularnewline
26 & 0.008538 & 0.0724 & 0.471225 \tabularnewline
27 & 0.017545 & 0.1489 & 0.441036 \tabularnewline
28 & -0.035473 & -0.301 & 0.382141 \tabularnewline
29 & -0.087791 & -0.7449 & 0.229368 \tabularnewline
30 & -0.023059 & -0.1957 & 0.422712 \tabularnewline
31 & -0.034711 & -0.2945 & 0.384598 \tabularnewline
32 & -0.024427 & -0.2073 & 0.418191 \tabularnewline
33 & -0.014017 & -0.1189 & 0.452827 \tabularnewline
34 & -0.016917 & -0.1435 & 0.44313 \tabularnewline
35 & 0.015362 & 0.1303 & 0.448328 \tabularnewline
36 & 0.003554 & 0.0302 & 0.488013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70188&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]0.954442[/C][C]8.0987[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.034093[/C][C]-0.2893[/C][C]0.386597[/C][/ROW]
[ROW][C]3[/C][C]-0.030778[/C][C]-0.2612[/C][C]0.397356[/C][/ROW]
[ROW][C]4[/C][C]0.019119[/C][C]0.1622[/C][C]0.435788[/C][/ROW]
[ROW][C]5[/C][C]-0.079594[/C][C]-0.6754[/C][C]0.2508[/C][/ROW]
[ROW][C]6[/C][C]-0.045265[/C][C]-0.3841[/C][C]0.351024[/C][/ROW]
[ROW][C]7[/C][C]-0.016811[/C][C]-0.1426[/C][C]0.443483[/C][/ROW]
[ROW][C]8[/C][C]-0.053523[/C][C]-0.4542[/C][C]0.325542[/C][/ROW]
[ROW][C]9[/C][C]-0.011497[/C][C]-0.0976[/C][C]0.461277[/C][/ROW]
[ROW][C]10[/C][C]0.003001[/C][C]0.0255[/C][C]0.489878[/C][/ROW]
[ROW][C]11[/C][C]0.010886[/C][C]0.0924[/C][C]0.463332[/C][/ROW]
[ROW][C]12[/C][C]0.006989[/C][C]0.0593[/C][C]0.476437[/C][/ROW]
[ROW][C]13[/C][C]-0.002869[/C][C]-0.0243[/C][C]0.490322[/C][/ROW]
[ROW][C]14[/C][C]-0.042993[/C][C]-0.3648[/C][C]0.358161[/C][/ROW]
[ROW][C]15[/C][C]0.016937[/C][C]0.1437[/C][C]0.443065[/C][/ROW]
[ROW][C]16[/C][C]-0.045543[/C][C]-0.3864[/C][C]0.350153[/C][/ROW]
[ROW][C]17[/C][C]0.016852[/C][C]0.143[/C][C]0.443349[/C][/ROW]
[ROW][C]18[/C][C]-0.018282[/C][C]-0.1551[/C][C]0.438576[/C][/ROW]
[ROW][C]19[/C][C]-0.023066[/C][C]-0.1957[/C][C]0.42269[/C][/ROW]
[ROW][C]20[/C][C]0.036069[/C][C]0.3061[/C][C]0.380224[/C][/ROW]
[ROW][C]21[/C][C]-0.105324[/C][C]-0.8937[/C][C]0.187228[/C][/ROW]
[ROW][C]22[/C][C]-0.021602[/C][C]-0.1833[/C][C]0.427541[/C][/ROW]
[ROW][C]23[/C][C]-0.021789[/C][C]-0.1849[/C][C]0.42692[/C][/ROW]
[ROW][C]24[/C][C]-0.004701[/C][C]-0.0399[/C][C]0.484146[/C][/ROW]
[ROW][C]25[/C][C]-0.040159[/C][C]-0.3408[/C][C]0.367137[/C][/ROW]
[ROW][C]26[/C][C]0.008538[/C][C]0.0724[/C][C]0.471225[/C][/ROW]
[ROW][C]27[/C][C]0.017545[/C][C]0.1489[/C][C]0.441036[/C][/ROW]
[ROW][C]28[/C][C]-0.035473[/C][C]-0.301[/C][C]0.382141[/C][/ROW]
[ROW][C]29[/C][C]-0.087791[/C][C]-0.7449[/C][C]0.229368[/C][/ROW]
[ROW][C]30[/C][C]-0.023059[/C][C]-0.1957[/C][C]0.422712[/C][/ROW]
[ROW][C]31[/C][C]-0.034711[/C][C]-0.2945[/C][C]0.384598[/C][/ROW]
[ROW][C]32[/C][C]-0.024427[/C][C]-0.2073[/C][C]0.418191[/C][/ROW]
[ROW][C]33[/C][C]-0.014017[/C][C]-0.1189[/C][C]0.452827[/C][/ROW]
[ROW][C]34[/C][C]-0.016917[/C][C]-0.1435[/C][C]0.44313[/C][/ROW]
[ROW][C]35[/C][C]0.015362[/C][C]0.1303[/C][C]0.448328[/C][/ROW]
[ROW][C]36[/C][C]0.003554[/C][C]0.0302[/C][C]0.488013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70188&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70188&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
10.9544428.09870
2-0.034093-0.28930.386597
3-0.030778-0.26120.397356
40.0191190.16220.435788
5-0.079594-0.67540.2508
6-0.045265-0.38410.351024
7-0.016811-0.14260.443483
8-0.053523-0.45420.325542
9-0.011497-0.09760.461277
100.0030010.02550.489878
110.0108860.09240.463332
120.0069890.05930.476437
13-0.002869-0.02430.490322
14-0.042993-0.36480.358161
150.0169370.14370.443065
16-0.045543-0.38640.350153
170.0168520.1430.443349
18-0.018282-0.15510.438576
19-0.023066-0.19570.42269
200.0360690.30610.380224
21-0.105324-0.89370.187228
22-0.021602-0.18330.427541
23-0.021789-0.18490.42692
24-0.004701-0.03990.484146
25-0.040159-0.34080.367137
260.0085380.07240.471225
270.0175450.14890.441036
28-0.035473-0.3010.382141
29-0.087791-0.74490.229368
30-0.023059-0.19570.422712
31-0.034711-0.29450.384598
32-0.024427-0.20730.418191
33-0.014017-0.11890.452827
34-0.016917-0.14350.44313
350.0153620.13030.448328
360.0035540.03020.488013


Figures (Output of Computation)

Input Parameters & R Code

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