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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 computationFri, 24 Dec 2010 14:38:51 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t1293201437zzdll02jsjiugw2.htm/, Retrieved Tue, 30 Apr 2024 02:30:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115015, Retrieved Tue, 30 Apr 2024 02:30:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

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]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-27 12:29:42] [ebd107afac1bd6180acb277edd05815b]
-    D            [(Partial) Autocorrelation Function] [] [2010-12-24 14:38:51] [817f44ab92560f82acbc5e6c80d9a294] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
19685.6
19601.7
16006.9
17681.2
19790.4
17014.2
17424.5
18908.9
15692.1
15160
15794.3
16032.1
16065
16236.8
12521
14762.1
15446.9
13635
14212.6
15021.7
14134.3
13721.4
14384.5
15638.6
19711.6
20359.8
16141.4
20056.9
20605.5
19325.8
20547.7
19211.2
19009.5
18746.8
16471.5
18957.2
20515.2
18374.4
16192.9
18147.5
19301.4
18344.7
17183.6
19630
17167.2
17428.5
16016.5
18466.5
18406.6
18174.1
14851.9
16260.7
18329.6
18003.8
15903.8
19554.2
16554.2
16198.9
16571.8
17535.2
16198.1

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=115015&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=115015&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115015&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
10.8399495.87960
20.7856995.49991e-06
30.7301865.11133e-06
40.5441293.80890.000195
50.4227572.95930.002369
60.2695111.88660.032575
70.0668240.46780.321012
8-0.052303-0.36610.357926
9-0.192835-1.34980.091634
10-0.320989-2.24690.014592
11-0.400943-2.80660.003582
12-0.486334-3.40430.000665
13-0.513268-3.59290.000378
14-0.488822-3.42180.000632
15-0.471025-3.29720.000911
16-0.447318-3.13120.001467
17-0.392997-2.7510.004152
18-0.321416-2.24990.01449
19-0.263979-1.84790.035332
20-0.1954-1.36780.088807
21-0.159285-1.1150.135146
22-0.100374-0.70260.242809
23-0.040737-0.28520.388362
24-0.046153-0.32310.374007
250.0001198e-040.499669
260.0031190.02180.491335
27-0.012183-0.08530.466194
280.0203670.14260.443607
290.0280190.19610.422659
300.0166220.11640.453923
310.0182470.12770.449442
320.0375590.26290.396859
330.029530.20670.418548
340.0448840.31420.377357
350.0429620.30070.382444
360.0457120.320.375169

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.839949 & 5.8796 & 0 \tabularnewline
2 & 0.785699 & 5.4999 & 1e-06 \tabularnewline
3 & 0.730186 & 5.1113 & 3e-06 \tabularnewline
4 & 0.544129 & 3.8089 & 0.000195 \tabularnewline
5 & 0.422757 & 2.9593 & 0.002369 \tabularnewline
6 & 0.269511 & 1.8866 & 0.032575 \tabularnewline
7 & 0.066824 & 0.4678 & 0.321012 \tabularnewline
8 & -0.052303 & -0.3661 & 0.357926 \tabularnewline
9 & -0.192835 & -1.3498 & 0.091634 \tabularnewline
10 & -0.320989 & -2.2469 & 0.014592 \tabularnewline
11 & -0.400943 & -2.8066 & 0.003582 \tabularnewline
12 & -0.486334 & -3.4043 & 0.000665 \tabularnewline
13 & -0.513268 & -3.5929 & 0.000378 \tabularnewline
14 & -0.488822 & -3.4218 & 0.000632 \tabularnewline
15 & -0.471025 & -3.2972 & 0.000911 \tabularnewline
16 & -0.447318 & -3.1312 & 0.001467 \tabularnewline
17 & -0.392997 & -2.751 & 0.004152 \tabularnewline
18 & -0.321416 & -2.2499 & 0.01449 \tabularnewline
19 & -0.263979 & -1.8479 & 0.035332 \tabularnewline
20 & -0.1954 & -1.3678 & 0.088807 \tabularnewline
21 & -0.159285 & -1.115 & 0.135146 \tabularnewline
22 & -0.100374 & -0.7026 & 0.242809 \tabularnewline
23 & -0.040737 & -0.2852 & 0.388362 \tabularnewline
24 & -0.046153 & -0.3231 & 0.374007 \tabularnewline
25 & 0.000119 & 8e-04 & 0.499669 \tabularnewline
26 & 0.003119 & 0.0218 & 0.491335 \tabularnewline
27 & -0.012183 & -0.0853 & 0.466194 \tabularnewline
28 & 0.020367 & 0.1426 & 0.443607 \tabularnewline
29 & 0.028019 & 0.1961 & 0.422659 \tabularnewline
30 & 0.016622 & 0.1164 & 0.453923 \tabularnewline
31 & 0.018247 & 0.1277 & 0.449442 \tabularnewline
32 & 0.037559 & 0.2629 & 0.396859 \tabularnewline
33 & 0.02953 & 0.2067 & 0.418548 \tabularnewline
34 & 0.044884 & 0.3142 & 0.377357 \tabularnewline
35 & 0.042962 & 0.3007 & 0.382444 \tabularnewline
36 & 0.045712 & 0.32 & 0.375169 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115015&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]0.839949[/C][C]5.8796[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.785699[/C][C]5.4999[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.730186[/C][C]5.1113[/C][C]3e-06[/C][/ROW]
[ROW][C]4[/C][C]0.544129[/C][C]3.8089[/C][C]0.000195[/C][/ROW]
[ROW][C]5[/C][C]0.422757[/C][C]2.9593[/C][C]0.002369[/C][/ROW]
[ROW][C]6[/C][C]0.269511[/C][C]1.8866[/C][C]0.032575[/C][/ROW]
[ROW][C]7[/C][C]0.066824[/C][C]0.4678[/C][C]0.321012[/C][/ROW]
[ROW][C]8[/C][C]-0.052303[/C][C]-0.3661[/C][C]0.357926[/C][/ROW]
[ROW][C]9[/C][C]-0.192835[/C][C]-1.3498[/C][C]0.091634[/C][/ROW]
[ROW][C]10[/C][C]-0.320989[/C][C]-2.2469[/C][C]0.014592[/C][/ROW]
[ROW][C]11[/C][C]-0.400943[/C][C]-2.8066[/C][C]0.003582[/C][/ROW]
[ROW][C]12[/C][C]-0.486334[/C][C]-3.4043[/C][C]0.000665[/C][/ROW]
[ROW][C]13[/C][C]-0.513268[/C][C]-3.5929[/C][C]0.000378[/C][/ROW]
[ROW][C]14[/C][C]-0.488822[/C][C]-3.4218[/C][C]0.000632[/C][/ROW]
[ROW][C]15[/C][C]-0.471025[/C][C]-3.2972[/C][C]0.000911[/C][/ROW]
[ROW][C]16[/C][C]-0.447318[/C][C]-3.1312[/C][C]0.001467[/C][/ROW]
[ROW][C]17[/C][C]-0.392997[/C][C]-2.751[/C][C]0.004152[/C][/ROW]
[ROW][C]18[/C][C]-0.321416[/C][C]-2.2499[/C][C]0.01449[/C][/ROW]
[ROW][C]19[/C][C]-0.263979[/C][C]-1.8479[/C][C]0.035332[/C][/ROW]
[ROW][C]20[/C][C]-0.1954[/C][C]-1.3678[/C][C]0.088807[/C][/ROW]
[ROW][C]21[/C][C]-0.159285[/C][C]-1.115[/C][C]0.135146[/C][/ROW]
[ROW][C]22[/C][C]-0.100374[/C][C]-0.7026[/C][C]0.242809[/C][/ROW]
[ROW][C]23[/C][C]-0.040737[/C][C]-0.2852[/C][C]0.388362[/C][/ROW]
[ROW][C]24[/C][C]-0.046153[/C][C]-0.3231[/C][C]0.374007[/C][/ROW]
[ROW][C]25[/C][C]0.000119[/C][C]8e-04[/C][C]0.499669[/C][/ROW]
[ROW][C]26[/C][C]0.003119[/C][C]0.0218[/C][C]0.491335[/C][/ROW]
[ROW][C]27[/C][C]-0.012183[/C][C]-0.0853[/C][C]0.466194[/C][/ROW]
[ROW][C]28[/C][C]0.020367[/C][C]0.1426[/C][C]0.443607[/C][/ROW]
[ROW][C]29[/C][C]0.028019[/C][C]0.1961[/C][C]0.422659[/C][/ROW]
[ROW][C]30[/C][C]0.016622[/C][C]0.1164[/C][C]0.453923[/C][/ROW]
[ROW][C]31[/C][C]0.018247[/C][C]0.1277[/C][C]0.449442[/C][/ROW]
[ROW][C]32[/C][C]0.037559[/C][C]0.2629[/C][C]0.396859[/C][/ROW]
[ROW][C]33[/C][C]0.02953[/C][C]0.2067[/C][C]0.418548[/C][/ROW]
[ROW][C]34[/C][C]0.044884[/C][C]0.3142[/C][C]0.377357[/C][/ROW]
[ROW][C]35[/C][C]0.042962[/C][C]0.3007[/C][C]0.382444[/C][/ROW]
[ROW][C]36[/C][C]0.045712[/C][C]0.32[/C][C]0.375169[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115015&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115015&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
10.8399495.87960
20.7856995.49991e-06
30.7301865.11133e-06
40.5441293.80890.000195
50.4227572.95930.002369
60.2695111.88660.032575
70.0668240.46780.321012
8-0.052303-0.36610.357926
9-0.192835-1.34980.091634
10-0.320989-2.24690.014592
11-0.400943-2.80660.003582
12-0.486334-3.40430.000665
13-0.513268-3.59290.000378
14-0.488822-3.42180.000632
15-0.471025-3.29720.000911
16-0.447318-3.13120.001467
17-0.392997-2.7510.004152
18-0.321416-2.24990.01449
19-0.263979-1.84790.035332
20-0.1954-1.36780.088807
21-0.159285-1.1150.135146
22-0.100374-0.70260.242809
23-0.040737-0.28520.388362
24-0.046153-0.32310.374007
250.0001198e-040.499669
260.0031190.02180.491335
27-0.012183-0.08530.466194
280.0203670.14260.443607
290.0280190.19610.422659
300.0166220.11640.453923
310.0182470.12770.449442
320.0375590.26290.396859
330.029530.20670.418548
340.0448840.31420.377357
350.0429620.30070.382444
360.0457120.320.375169






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8399495.87960
20.2722861.9060.031262
30.0778510.5450.294129
4-0.474727-3.32310.000845
5-0.204264-1.42980.079553
6-0.206423-1.4450.077417
7-0.232429-1.6270.055075
80.0143020.10010.460332
90.0393960.27580.391941
100.0649990.4550.325562
11-0.039338-0.27540.392096
12-0.091524-0.64070.262361
130.031310.21920.413715
140.1623611.13650.130631
150.1089550.76270.224653
16-0.192255-1.34580.092282
17-0.242167-1.69520.048195
18-0.072565-0.5080.306883
19-0.050456-0.35320.362731
200.0124560.08720.465438
21-0.13711-0.95980.170942
220.0487860.34150.367094
230.0641380.4490.327718
24-0.204829-1.43380.078989
250.0228670.16010.436743
26-4.6e-05-3e-040.499871
270.0690850.48360.315413
28-0.035118-0.24580.403422
290.0309640.21670.414652
30-0.007133-0.04990.480189
31-0.191689-1.34180.092919
320.028120.19680.422384
33-0.141077-0.98750.164114
340.0454240.3180.375931
35-0.042876-0.30010.382672
36-0.009053-0.06340.474865

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.839949 & 5.8796 & 0 \tabularnewline
2 & 0.272286 & 1.906 & 0.031262 \tabularnewline
3 & 0.077851 & 0.545 & 0.294129 \tabularnewline
4 & -0.474727 & -3.3231 & 0.000845 \tabularnewline
5 & -0.204264 & -1.4298 & 0.079553 \tabularnewline
6 & -0.206423 & -1.445 & 0.077417 \tabularnewline
7 & -0.232429 & -1.627 & 0.055075 \tabularnewline
8 & 0.014302 & 0.1001 & 0.460332 \tabularnewline
9 & 0.039396 & 0.2758 & 0.391941 \tabularnewline
10 & 0.064999 & 0.455 & 0.325562 \tabularnewline
11 & -0.039338 & -0.2754 & 0.392096 \tabularnewline
12 & -0.091524 & -0.6407 & 0.262361 \tabularnewline
13 & 0.03131 & 0.2192 & 0.413715 \tabularnewline
14 & 0.162361 & 1.1365 & 0.130631 \tabularnewline
15 & 0.108955 & 0.7627 & 0.224653 \tabularnewline
16 & -0.192255 & -1.3458 & 0.092282 \tabularnewline
17 & -0.242167 & -1.6952 & 0.048195 \tabularnewline
18 & -0.072565 & -0.508 & 0.306883 \tabularnewline
19 & -0.050456 & -0.3532 & 0.362731 \tabularnewline
20 & 0.012456 & 0.0872 & 0.465438 \tabularnewline
21 & -0.13711 & -0.9598 & 0.170942 \tabularnewline
22 & 0.048786 & 0.3415 & 0.367094 \tabularnewline
23 & 0.064138 & 0.449 & 0.327718 \tabularnewline
24 & -0.204829 & -1.4338 & 0.078989 \tabularnewline
25 & 0.022867 & 0.1601 & 0.436743 \tabularnewline
26 & -4.6e-05 & -3e-04 & 0.499871 \tabularnewline
27 & 0.069085 & 0.4836 & 0.315413 \tabularnewline
28 & -0.035118 & -0.2458 & 0.403422 \tabularnewline
29 & 0.030964 & 0.2167 & 0.414652 \tabularnewline
30 & -0.007133 & -0.0499 & 0.480189 \tabularnewline
31 & -0.191689 & -1.3418 & 0.092919 \tabularnewline
32 & 0.02812 & 0.1968 & 0.422384 \tabularnewline
33 & -0.141077 & -0.9875 & 0.164114 \tabularnewline
34 & 0.045424 & 0.318 & 0.375931 \tabularnewline
35 & -0.042876 & -0.3001 & 0.382672 \tabularnewline
36 & -0.009053 & -0.0634 & 0.474865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115015&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]0.839949[/C][C]5.8796[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.272286[/C][C]1.906[/C][C]0.031262[/C][/ROW]
[ROW][C]3[/C][C]0.077851[/C][C]0.545[/C][C]0.294129[/C][/ROW]
[ROW][C]4[/C][C]-0.474727[/C][C]-3.3231[/C][C]0.000845[/C][/ROW]
[ROW][C]5[/C][C]-0.204264[/C][C]-1.4298[/C][C]0.079553[/C][/ROW]
[ROW][C]6[/C][C]-0.206423[/C][C]-1.445[/C][C]0.077417[/C][/ROW]
[ROW][C]7[/C][C]-0.232429[/C][C]-1.627[/C][C]0.055075[/C][/ROW]
[ROW][C]8[/C][C]0.014302[/C][C]0.1001[/C][C]0.460332[/C][/ROW]
[ROW][C]9[/C][C]0.039396[/C][C]0.2758[/C][C]0.391941[/C][/ROW]
[ROW][C]10[/C][C]0.064999[/C][C]0.455[/C][C]0.325562[/C][/ROW]
[ROW][C]11[/C][C]-0.039338[/C][C]-0.2754[/C][C]0.392096[/C][/ROW]
[ROW][C]12[/C][C]-0.091524[/C][C]-0.6407[/C][C]0.262361[/C][/ROW]
[ROW][C]13[/C][C]0.03131[/C][C]0.2192[/C][C]0.413715[/C][/ROW]
[ROW][C]14[/C][C]0.162361[/C][C]1.1365[/C][C]0.130631[/C][/ROW]
[ROW][C]15[/C][C]0.108955[/C][C]0.7627[/C][C]0.224653[/C][/ROW]
[ROW][C]16[/C][C]-0.192255[/C][C]-1.3458[/C][C]0.092282[/C][/ROW]
[ROW][C]17[/C][C]-0.242167[/C][C]-1.6952[/C][C]0.048195[/C][/ROW]
[ROW][C]18[/C][C]-0.072565[/C][C]-0.508[/C][C]0.306883[/C][/ROW]
[ROW][C]19[/C][C]-0.050456[/C][C]-0.3532[/C][C]0.362731[/C][/ROW]
[ROW][C]20[/C][C]0.012456[/C][C]0.0872[/C][C]0.465438[/C][/ROW]
[ROW][C]21[/C][C]-0.13711[/C][C]-0.9598[/C][C]0.170942[/C][/ROW]
[ROW][C]22[/C][C]0.048786[/C][C]0.3415[/C][C]0.367094[/C][/ROW]
[ROW][C]23[/C][C]0.064138[/C][C]0.449[/C][C]0.327718[/C][/ROW]
[ROW][C]24[/C][C]-0.204829[/C][C]-1.4338[/C][C]0.078989[/C][/ROW]
[ROW][C]25[/C][C]0.022867[/C][C]0.1601[/C][C]0.436743[/C][/ROW]
[ROW][C]26[/C][C]-4.6e-05[/C][C]-3e-04[/C][C]0.499871[/C][/ROW]
[ROW][C]27[/C][C]0.069085[/C][C]0.4836[/C][C]0.315413[/C][/ROW]
[ROW][C]28[/C][C]-0.035118[/C][C]-0.2458[/C][C]0.403422[/C][/ROW]
[ROW][C]29[/C][C]0.030964[/C][C]0.2167[/C][C]0.414652[/C][/ROW]
[ROW][C]30[/C][C]-0.007133[/C][C]-0.0499[/C][C]0.480189[/C][/ROW]
[ROW][C]31[/C][C]-0.191689[/C][C]-1.3418[/C][C]0.092919[/C][/ROW]
[ROW][C]32[/C][C]0.02812[/C][C]0.1968[/C][C]0.422384[/C][/ROW]
[ROW][C]33[/C][C]-0.141077[/C][C]-0.9875[/C][C]0.164114[/C][/ROW]
[ROW][C]34[/C][C]0.045424[/C][C]0.318[/C][C]0.375931[/C][/ROW]
[ROW][C]35[/C][C]-0.042876[/C][C]-0.3001[/C][C]0.382672[/C][/ROW]
[ROW][C]36[/C][C]-0.009053[/C][C]-0.0634[/C][C]0.474865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115015&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115015&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
10.8399495.87960
20.2722861.9060.031262
30.0778510.5450.294129
4-0.474727-3.32310.000845
5-0.204264-1.42980.079553
6-0.206423-1.4450.077417
7-0.232429-1.6270.055075
80.0143020.10010.460332
90.0393960.27580.391941
100.0649990.4550.325562
11-0.039338-0.27540.392096
12-0.091524-0.64070.262361
130.031310.21920.413715
140.1623611.13650.130631
150.1089550.76270.224653
16-0.192255-1.34580.092282
17-0.242167-1.69520.048195
18-0.072565-0.5080.306883
19-0.050456-0.35320.362731
200.0124560.08720.465438
21-0.13711-0.95980.170942
220.0487860.34150.367094
230.0641380.4490.327718
24-0.204829-1.43380.078989
250.0228670.16010.436743
26-4.6e-05-3e-040.499871
270.0690850.48360.315413
28-0.035118-0.24580.403422
290.0309640.21670.414652
30-0.007133-0.04990.480189
31-0.191689-1.34180.092919
320.028120.19680.422384
33-0.141077-0.98750.164114
340.0454240.3180.375931
35-0.042876-0.30010.382672
36-0.009053-0.06340.474865


Figures (Output of Computation)

Input Parameters & R Code

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 ; par8 = ;
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')