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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, 27 Nov 2009 05:29:42 -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/27/t1259325027a3v6o57x9od8tsu.htm/, Retrieved Mon, 29 Apr 2024 20:31:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60642, Retrieved Mon, 29 Apr 2024 20:31:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws8vr2
Estimated Impact162

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] [4407d6264e55b051ec65750e6dca2820] [Current]
-    D            [(Partial) Autocorrelation Function] [] [2010-12-24 14:38:51] [6e5489189f7de5cfbcc25dd35ae15009]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
20906,5
21164,1
21374,4
22952,3
21343,5
23899,3
22392,9
18274,1
22786,7
22321,5
17842,2
16373,5
15993,8
16446,1
17729
16643
16196,7
18252,1
17304

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=60642&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=60642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60642&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
10.7220655.05453e-06
20.6912524.83887e-06
30.6313544.41952.7e-05
40.3792812.6550.005334
50.3331812.33230.01192
60.1941071.35880.090224
7-0.025428-0.1780.429731
8-0.010975-0.07680.469539
9-0.158307-1.10810.136604
10-0.193681-1.35580.090694
11-0.13885-0.97190.167925
12-0.201244-1.40870.082618
13-0.164307-1.15010.127833
14-0.121343-0.84940.199895
15-0.132772-0.92940.178618
16-0.107369-0.75160.227948
17-0.081492-0.57040.285491
18-0.090375-0.63260.264961
19-0.066671-0.46670.321393
20-0.036854-0.2580.398752
21-0.084277-0.58990.278972
22-0.062272-0.43590.33241
230.0088930.06220.475309
24-0.07338-0.51370.304899
250.0059050.04130.483599
260.0016280.01140.495478
27-0.045604-0.31920.375456
28-0.004768-0.03340.486756
29-0.033436-0.23410.407959
30-0.067548-0.47280.319214
31-0.032504-0.22750.41048
32-0.103773-0.72640.23552
33-0.097921-0.68540.248146
34-0.08366-0.58560.280409
35-0.140872-0.98610.164462
36-0.123245-0.86270.196249

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.722065 & 5.0545 & 3e-06 \tabularnewline
2 & 0.691252 & 4.8388 & 7e-06 \tabularnewline
3 & 0.631354 & 4.4195 & 2.7e-05 \tabularnewline
4 & 0.379281 & 2.655 & 0.005334 \tabularnewline
5 & 0.333181 & 2.3323 & 0.01192 \tabularnewline
6 & 0.194107 & 1.3588 & 0.090224 \tabularnewline
7 & -0.025428 & -0.178 & 0.429731 \tabularnewline
8 & -0.010975 & -0.0768 & 0.469539 \tabularnewline
9 & -0.158307 & -1.1081 & 0.136604 \tabularnewline
10 & -0.193681 & -1.3558 & 0.090694 \tabularnewline
11 & -0.13885 & -0.9719 & 0.167925 \tabularnewline
12 & -0.201244 & -1.4087 & 0.082618 \tabularnewline
13 & -0.164307 & -1.1501 & 0.127833 \tabularnewline
14 & -0.121343 & -0.8494 & 0.199895 \tabularnewline
15 & -0.132772 & -0.9294 & 0.178618 \tabularnewline
16 & -0.107369 & -0.7516 & 0.227948 \tabularnewline
17 & -0.081492 & -0.5704 & 0.285491 \tabularnewline
18 & -0.090375 & -0.6326 & 0.264961 \tabularnewline
19 & -0.066671 & -0.4667 & 0.321393 \tabularnewline
20 & -0.036854 & -0.258 & 0.398752 \tabularnewline
21 & -0.084277 & -0.5899 & 0.278972 \tabularnewline
22 & -0.062272 & -0.4359 & 0.33241 \tabularnewline
23 & 0.008893 & 0.0622 & 0.475309 \tabularnewline
24 & -0.07338 & -0.5137 & 0.304899 \tabularnewline
25 & 0.005905 & 0.0413 & 0.483599 \tabularnewline
26 & 0.001628 & 0.0114 & 0.495478 \tabularnewline
27 & -0.045604 & -0.3192 & 0.375456 \tabularnewline
28 & -0.004768 & -0.0334 & 0.486756 \tabularnewline
29 & -0.033436 & -0.2341 & 0.407959 \tabularnewline
30 & -0.067548 & -0.4728 & 0.319214 \tabularnewline
31 & -0.032504 & -0.2275 & 0.41048 \tabularnewline
32 & -0.103773 & -0.7264 & 0.23552 \tabularnewline
33 & -0.097921 & -0.6854 & 0.248146 \tabularnewline
34 & -0.08366 & -0.5856 & 0.280409 \tabularnewline
35 & -0.140872 & -0.9861 & 0.164462 \tabularnewline
36 & -0.123245 & -0.8627 & 0.196249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60642&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]0.722065[/C][C]5.0545[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.691252[/C][C]4.8388[/C][C]7e-06[/C][/ROW]
[ROW][C]3[/C][C]0.631354[/C][C]4.4195[/C][C]2.7e-05[/C][/ROW]
[ROW][C]4[/C][C]0.379281[/C][C]2.655[/C][C]0.005334[/C][/ROW]
[ROW][C]5[/C][C]0.333181[/C][C]2.3323[/C][C]0.01192[/C][/ROW]
[ROW][C]6[/C][C]0.194107[/C][C]1.3588[/C][C]0.090224[/C][/ROW]
[ROW][C]7[/C][C]-0.025428[/C][C]-0.178[/C][C]0.429731[/C][/ROW]
[ROW][C]8[/C][C]-0.010975[/C][C]-0.0768[/C][C]0.469539[/C][/ROW]
[ROW][C]9[/C][C]-0.158307[/C][C]-1.1081[/C][C]0.136604[/C][/ROW]
[ROW][C]10[/C][C]-0.193681[/C][C]-1.3558[/C][C]0.090694[/C][/ROW]
[ROW][C]11[/C][C]-0.13885[/C][C]-0.9719[/C][C]0.167925[/C][/ROW]
[ROW][C]12[/C][C]-0.201244[/C][C]-1.4087[/C][C]0.082618[/C][/ROW]
[ROW][C]13[/C][C]-0.164307[/C][C]-1.1501[/C][C]0.127833[/C][/ROW]
[ROW][C]14[/C][C]-0.121343[/C][C]-0.8494[/C][C]0.199895[/C][/ROW]
[ROW][C]15[/C][C]-0.132772[/C][C]-0.9294[/C][C]0.178618[/C][/ROW]
[ROW][C]16[/C][C]-0.107369[/C][C]-0.7516[/C][C]0.227948[/C][/ROW]
[ROW][C]17[/C][C]-0.081492[/C][C]-0.5704[/C][C]0.285491[/C][/ROW]
[ROW][C]18[/C][C]-0.090375[/C][C]-0.6326[/C][C]0.264961[/C][/ROW]
[ROW][C]19[/C][C]-0.066671[/C][C]-0.4667[/C][C]0.321393[/C][/ROW]
[ROW][C]20[/C][C]-0.036854[/C][C]-0.258[/C][C]0.398752[/C][/ROW]
[ROW][C]21[/C][C]-0.084277[/C][C]-0.5899[/C][C]0.278972[/C][/ROW]
[ROW][C]22[/C][C]-0.062272[/C][C]-0.4359[/C][C]0.33241[/C][/ROW]
[ROW][C]23[/C][C]0.008893[/C][C]0.0622[/C][C]0.475309[/C][/ROW]
[ROW][C]24[/C][C]-0.07338[/C][C]-0.5137[/C][C]0.304899[/C][/ROW]
[ROW][C]25[/C][C]0.005905[/C][C]0.0413[/C][C]0.483599[/C][/ROW]
[ROW][C]26[/C][C]0.001628[/C][C]0.0114[/C][C]0.495478[/C][/ROW]
[ROW][C]27[/C][C]-0.045604[/C][C]-0.3192[/C][C]0.375456[/C][/ROW]
[ROW][C]28[/C][C]-0.004768[/C][C]-0.0334[/C][C]0.486756[/C][/ROW]
[ROW][C]29[/C][C]-0.033436[/C][C]-0.2341[/C][C]0.407959[/C][/ROW]
[ROW][C]30[/C][C]-0.067548[/C][C]-0.4728[/C][C]0.319214[/C][/ROW]
[ROW][C]31[/C][C]-0.032504[/C][C]-0.2275[/C][C]0.41048[/C][/ROW]
[ROW][C]32[/C][C]-0.103773[/C][C]-0.7264[/C][C]0.23552[/C][/ROW]
[ROW][C]33[/C][C]-0.097921[/C][C]-0.6854[/C][C]0.248146[/C][/ROW]
[ROW][C]34[/C][C]-0.08366[/C][C]-0.5856[/C][C]0.280409[/C][/ROW]
[ROW][C]35[/C][C]-0.140872[/C][C]-0.9861[/C][C]0.164462[/C][/ROW]
[ROW][C]36[/C][C]-0.123245[/C][C]-0.8627[/C][C]0.196249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60642&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
10.7220655.05453e-06
20.6912524.83887e-06
30.6313544.41952.7e-05
40.3792812.6550.005334
50.3331812.33230.01192
60.1941071.35880.090224
7-0.025428-0.1780.429731
8-0.010975-0.07680.469539
9-0.158307-1.10810.136604
10-0.193681-1.35580.090694
11-0.13885-0.97190.167925
12-0.201244-1.40870.082618
13-0.164307-1.15010.127833
14-0.121343-0.84940.199895
15-0.132772-0.92940.178618
16-0.107369-0.75160.227948
17-0.081492-0.57040.285491
18-0.090375-0.63260.264961
19-0.066671-0.46670.321393
20-0.036854-0.2580.398752
21-0.084277-0.58990.278972
22-0.062272-0.43590.33241
230.0088930.06220.475309
24-0.07338-0.51370.304899
250.0059050.04130.483599
260.0016280.01140.495478
27-0.045604-0.31920.375456
28-0.004768-0.03340.486756
29-0.033436-0.23410.407959
30-0.067548-0.47280.319214
31-0.032504-0.22750.41048
32-0.103773-0.72640.23552
33-0.097921-0.68540.248146
34-0.08366-0.58560.280409
35-0.140872-0.98610.164462
36-0.123245-0.86270.196249






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7220655.05453e-06
20.3549232.48450.00822
30.1269350.88850.189295
4-0.44335-3.10350.001587
5-0.041879-0.29320.385322
6-0.035891-0.25120.40134
7-0.257976-1.80580.038545
80.1213240.84930.199931
9-0.01955-0.13680.445856
100.1079420.75560.226755
110.075140.5260.300637
120.0134930.09450.462567
13-0.091404-0.63980.262632
14-0.079057-0.55340.291253
150.0442220.30960.379107
16-0.175272-1.22690.112861
170.0293610.20550.419006
180.0447020.31290.377837
190.0245110.17160.43224
200.0925630.64790.260024
21-0.146382-1.02470.155274
22-0.018649-0.13050.448336
230.1965951.37620.087514
24-0.170759-1.19530.118859
250.0128370.08990.464383
26-0.047574-0.3330.370271
270.0415250.29070.386263
28-0.161245-1.12870.132257
290.0415630.29090.386161
300.0462960.32410.373632
31-0.108738-0.76120.225102
320.071270.49890.310043
33-0.055569-0.3890.349487
340.0105190.07360.4708
35-0.065185-0.45630.325097
36-0.059343-0.41540.339831

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.722065 & 5.0545 & 3e-06 \tabularnewline
2 & 0.354923 & 2.4845 & 0.00822 \tabularnewline
3 & 0.126935 & 0.8885 & 0.189295 \tabularnewline
4 & -0.44335 & -3.1035 & 0.001587 \tabularnewline
5 & -0.041879 & -0.2932 & 0.385322 \tabularnewline
6 & -0.035891 & -0.2512 & 0.40134 \tabularnewline
7 & -0.257976 & -1.8058 & 0.038545 \tabularnewline
8 & 0.121324 & 0.8493 & 0.199931 \tabularnewline
9 & -0.01955 & -0.1368 & 0.445856 \tabularnewline
10 & 0.107942 & 0.7556 & 0.226755 \tabularnewline
11 & 0.07514 & 0.526 & 0.300637 \tabularnewline
12 & 0.013493 & 0.0945 & 0.462567 \tabularnewline
13 & -0.091404 & -0.6398 & 0.262632 \tabularnewline
14 & -0.079057 & -0.5534 & 0.291253 \tabularnewline
15 & 0.044222 & 0.3096 & 0.379107 \tabularnewline
16 & -0.175272 & -1.2269 & 0.112861 \tabularnewline
17 & 0.029361 & 0.2055 & 0.419006 \tabularnewline
18 & 0.044702 & 0.3129 & 0.377837 \tabularnewline
19 & 0.024511 & 0.1716 & 0.43224 \tabularnewline
20 & 0.092563 & 0.6479 & 0.260024 \tabularnewline
21 & -0.146382 & -1.0247 & 0.155274 \tabularnewline
22 & -0.018649 & -0.1305 & 0.448336 \tabularnewline
23 & 0.196595 & 1.3762 & 0.087514 \tabularnewline
24 & -0.170759 & -1.1953 & 0.118859 \tabularnewline
25 & 0.012837 & 0.0899 & 0.464383 \tabularnewline
26 & -0.047574 & -0.333 & 0.370271 \tabularnewline
27 & 0.041525 & 0.2907 & 0.386263 \tabularnewline
28 & -0.161245 & -1.1287 & 0.132257 \tabularnewline
29 & 0.041563 & 0.2909 & 0.386161 \tabularnewline
30 & 0.046296 & 0.3241 & 0.373632 \tabularnewline
31 & -0.108738 & -0.7612 & 0.225102 \tabularnewline
32 & 0.07127 & 0.4989 & 0.310043 \tabularnewline
33 & -0.055569 & -0.389 & 0.349487 \tabularnewline
34 & 0.010519 & 0.0736 & 0.4708 \tabularnewline
35 & -0.065185 & -0.4563 & 0.325097 \tabularnewline
36 & -0.059343 & -0.4154 & 0.339831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60642&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]0.722065[/C][C]5.0545[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.354923[/C][C]2.4845[/C][C]0.00822[/C][/ROW]
[ROW][C]3[/C][C]0.126935[/C][C]0.8885[/C][C]0.189295[/C][/ROW]
[ROW][C]4[/C][C]-0.44335[/C][C]-3.1035[/C][C]0.001587[/C][/ROW]
[ROW][C]5[/C][C]-0.041879[/C][C]-0.2932[/C][C]0.385322[/C][/ROW]
[ROW][C]6[/C][C]-0.035891[/C][C]-0.2512[/C][C]0.40134[/C][/ROW]
[ROW][C]7[/C][C]-0.257976[/C][C]-1.8058[/C][C]0.038545[/C][/ROW]
[ROW][C]8[/C][C]0.121324[/C][C]0.8493[/C][C]0.199931[/C][/ROW]
[ROW][C]9[/C][C]-0.01955[/C][C]-0.1368[/C][C]0.445856[/C][/ROW]
[ROW][C]10[/C][C]0.107942[/C][C]0.7556[/C][C]0.226755[/C][/ROW]
[ROW][C]11[/C][C]0.07514[/C][C]0.526[/C][C]0.300637[/C][/ROW]
[ROW][C]12[/C][C]0.013493[/C][C]0.0945[/C][C]0.462567[/C][/ROW]
[ROW][C]13[/C][C]-0.091404[/C][C]-0.6398[/C][C]0.262632[/C][/ROW]
[ROW][C]14[/C][C]-0.079057[/C][C]-0.5534[/C][C]0.291253[/C][/ROW]
[ROW][C]15[/C][C]0.044222[/C][C]0.3096[/C][C]0.379107[/C][/ROW]
[ROW][C]16[/C][C]-0.175272[/C][C]-1.2269[/C][C]0.112861[/C][/ROW]
[ROW][C]17[/C][C]0.029361[/C][C]0.2055[/C][C]0.419006[/C][/ROW]
[ROW][C]18[/C][C]0.044702[/C][C]0.3129[/C][C]0.377837[/C][/ROW]
[ROW][C]19[/C][C]0.024511[/C][C]0.1716[/C][C]0.43224[/C][/ROW]
[ROW][C]20[/C][C]0.092563[/C][C]0.6479[/C][C]0.260024[/C][/ROW]
[ROW][C]21[/C][C]-0.146382[/C][C]-1.0247[/C][C]0.155274[/C][/ROW]
[ROW][C]22[/C][C]-0.018649[/C][C]-0.1305[/C][C]0.448336[/C][/ROW]
[ROW][C]23[/C][C]0.196595[/C][C]1.3762[/C][C]0.087514[/C][/ROW]
[ROW][C]24[/C][C]-0.170759[/C][C]-1.1953[/C][C]0.118859[/C][/ROW]
[ROW][C]25[/C][C]0.012837[/C][C]0.0899[/C][C]0.464383[/C][/ROW]
[ROW][C]26[/C][C]-0.047574[/C][C]-0.333[/C][C]0.370271[/C][/ROW]
[ROW][C]27[/C][C]0.041525[/C][C]0.2907[/C][C]0.386263[/C][/ROW]
[ROW][C]28[/C][C]-0.161245[/C][C]-1.1287[/C][C]0.132257[/C][/ROW]
[ROW][C]29[/C][C]0.041563[/C][C]0.2909[/C][C]0.386161[/C][/ROW]
[ROW][C]30[/C][C]0.046296[/C][C]0.3241[/C][C]0.373632[/C][/ROW]
[ROW][C]31[/C][C]-0.108738[/C][C]-0.7612[/C][C]0.225102[/C][/ROW]
[ROW][C]32[/C][C]0.07127[/C][C]0.4989[/C][C]0.310043[/C][/ROW]
[ROW][C]33[/C][C]-0.055569[/C][C]-0.389[/C][C]0.349487[/C][/ROW]
[ROW][C]34[/C][C]0.010519[/C][C]0.0736[/C][C]0.4708[/C][/ROW]
[ROW][C]35[/C][C]-0.065185[/C][C]-0.4563[/C][C]0.325097[/C][/ROW]
[ROW][C]36[/C][C]-0.059343[/C][C]-0.4154[/C][C]0.339831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60642&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
10.7220655.05453e-06
20.3549232.48450.00822
30.1269350.88850.189295
4-0.44335-3.10350.001587
5-0.041879-0.29320.385322
6-0.035891-0.25120.40134
7-0.257976-1.80580.038545
80.1213240.84930.199931
9-0.01955-0.13680.445856
100.1079420.75560.226755
110.075140.5260.300637
120.0134930.09450.462567
13-0.091404-0.63980.262632
14-0.079057-0.55340.291253
150.0442220.30960.379107
16-0.175272-1.22690.112861
170.0293610.20550.419006
180.0447020.31290.377837
190.0245110.17160.43224
200.0925630.64790.260024
21-0.146382-1.02470.155274
22-0.018649-0.13050.448336
230.1965951.37620.087514
24-0.170759-1.19530.118859
250.0128370.08990.464383
26-0.047574-0.3330.370271
270.0415250.29070.386263
28-0.161245-1.12870.132257
290.0415630.29090.386161
300.0462960.32410.373632
31-0.108738-0.76120.225102
320.071270.49890.310043
33-0.055569-0.3890.349487
340.0105190.07360.4708
35-0.065185-0.45630.325097
36-0.059343-0.41540.339831


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 ;
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')