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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, 23 Nov 2009 14:04:43 -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/23/t12590105427xjqvef6kglvvfb.htm/, Retrieved Sun, 28 Apr 2024 22:15:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58907, Retrieved Sun, 28 Apr 2024 22:15:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact227

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       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD          [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:04:43] [e339dd08bcbfc073ac7494f09a949034] [Current]
-   PD            [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:10:32] [0df1a6455bedfaf424729b1e006090d0]
-   PD            [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:12:39] [0df1a6455bedfaf424729b1e006090d0]
-   PD            [(Partial) Autocorrelation Function] [Autocorrelatie mo...] [2009-11-23 21:18:37] [0df1a6455bedfaf424729b1e006090d0]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25,6
23,7
22
21,3
20,7
20,4
20,3
20,4
19,8
19,5
23,1
23,5
23,5
22,9
21,9
21,5
20,5
20,2
19,4
19,2
18,8
18,8
22,6
23,3
23
21,4
19,9
18,8
18,6
18,4
18,6
19,9
19,2
18,4
21,1
20,5
19,1
18,1
17
17,1
17,4
16,8
15,3
14,3
13,4
15,3
22,1
23,7
22,2
19,5
16,6
17,3
19,8
21,2
21,5
20,6
19,1
19,6
23,5
24

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=58907&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=58907&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58907&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
10.7254955.61970
20.3339932.58710.00606
30.0923260.71520.238644
40.0252830.19580.422698
50.1058710.82010.207711
60.1765861.36780.088233
70.1392691.07880.142503
80.0478420.37060.356126
90.0564060.43690.33187
100.1819541.40940.081938
110.3171262.45640.008471
120.375172.90610.00256
130.1872771.45060.076044
14-0.033385-0.25860.398416
15-0.138561-1.07330.143719
16-0.188132-1.45730.075129
17-0.183913-1.42460.079729
18-0.187778-1.45450.075506
19-0.2095-1.62280.054939
20-0.201868-1.56370.061579
21-0.110291-0.85430.198167
220.0383950.29740.383591
230.1379961.06890.144696
240.1451881.12460.132615
25-0.027298-0.21150.416626
26-0.197141-1.52710.066002
27-0.261213-2.02330.023749
28-0.270777-2.09740.020089
29-0.239241-1.85320.03439
30-0.199435-1.54480.063825
31-0.182492-1.41360.081327
32-0.183723-1.42310.079941
33-0.128069-0.9920.162587
34-0.019271-0.14930.440921
350.039940.30940.379055
360.0326590.2530.400576

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.725495 & 5.6197 & 0 \tabularnewline
2 & 0.333993 & 2.5871 & 0.00606 \tabularnewline
3 & 0.092326 & 0.7152 & 0.238644 \tabularnewline
4 & 0.025283 & 0.1958 & 0.422698 \tabularnewline
5 & 0.105871 & 0.8201 & 0.207711 \tabularnewline
6 & 0.176586 & 1.3678 & 0.088233 \tabularnewline
7 & 0.139269 & 1.0788 & 0.142503 \tabularnewline
8 & 0.047842 & 0.3706 & 0.356126 \tabularnewline
9 & 0.056406 & 0.4369 & 0.33187 \tabularnewline
10 & 0.181954 & 1.4094 & 0.081938 \tabularnewline
11 & 0.317126 & 2.4564 & 0.008471 \tabularnewline
12 & 0.37517 & 2.9061 & 0.00256 \tabularnewline
13 & 0.187277 & 1.4506 & 0.076044 \tabularnewline
14 & -0.033385 & -0.2586 & 0.398416 \tabularnewline
15 & -0.138561 & -1.0733 & 0.143719 \tabularnewline
16 & -0.188132 & -1.4573 & 0.075129 \tabularnewline
17 & -0.183913 & -1.4246 & 0.079729 \tabularnewline
18 & -0.187778 & -1.4545 & 0.075506 \tabularnewline
19 & -0.2095 & -1.6228 & 0.054939 \tabularnewline
20 & -0.201868 & -1.5637 & 0.061579 \tabularnewline
21 & -0.110291 & -0.8543 & 0.198167 \tabularnewline
22 & 0.038395 & 0.2974 & 0.383591 \tabularnewline
23 & 0.137996 & 1.0689 & 0.144696 \tabularnewline
24 & 0.145188 & 1.1246 & 0.132615 \tabularnewline
25 & -0.027298 & -0.2115 & 0.416626 \tabularnewline
26 & -0.197141 & -1.5271 & 0.066002 \tabularnewline
27 & -0.261213 & -2.0233 & 0.023749 \tabularnewline
28 & -0.270777 & -2.0974 & 0.020089 \tabularnewline
29 & -0.239241 & -1.8532 & 0.03439 \tabularnewline
30 & -0.199435 & -1.5448 & 0.063825 \tabularnewline
31 & -0.182492 & -1.4136 & 0.081327 \tabularnewline
32 & -0.183723 & -1.4231 & 0.079941 \tabularnewline
33 & -0.128069 & -0.992 & 0.162587 \tabularnewline
34 & -0.019271 & -0.1493 & 0.440921 \tabularnewline
35 & 0.03994 & 0.3094 & 0.379055 \tabularnewline
36 & 0.032659 & 0.253 & 0.400576 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58907&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]0.725495[/C][C]5.6197[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.333993[/C][C]2.5871[/C][C]0.00606[/C][/ROW]
[ROW][C]3[/C][C]0.092326[/C][C]0.7152[/C][C]0.238644[/C][/ROW]
[ROW][C]4[/C][C]0.025283[/C][C]0.1958[/C][C]0.422698[/C][/ROW]
[ROW][C]5[/C][C]0.105871[/C][C]0.8201[/C][C]0.207711[/C][/ROW]
[ROW][C]6[/C][C]0.176586[/C][C]1.3678[/C][C]0.088233[/C][/ROW]
[ROW][C]7[/C][C]0.139269[/C][C]1.0788[/C][C]0.142503[/C][/ROW]
[ROW][C]8[/C][C]0.047842[/C][C]0.3706[/C][C]0.356126[/C][/ROW]
[ROW][C]9[/C][C]0.056406[/C][C]0.4369[/C][C]0.33187[/C][/ROW]
[ROW][C]10[/C][C]0.181954[/C][C]1.4094[/C][C]0.081938[/C][/ROW]
[ROW][C]11[/C][C]0.317126[/C][C]2.4564[/C][C]0.008471[/C][/ROW]
[ROW][C]12[/C][C]0.37517[/C][C]2.9061[/C][C]0.00256[/C][/ROW]
[ROW][C]13[/C][C]0.187277[/C][C]1.4506[/C][C]0.076044[/C][/ROW]
[ROW][C]14[/C][C]-0.033385[/C][C]-0.2586[/C][C]0.398416[/C][/ROW]
[ROW][C]15[/C][C]-0.138561[/C][C]-1.0733[/C][C]0.143719[/C][/ROW]
[ROW][C]16[/C][C]-0.188132[/C][C]-1.4573[/C][C]0.075129[/C][/ROW]
[ROW][C]17[/C][C]-0.183913[/C][C]-1.4246[/C][C]0.079729[/C][/ROW]
[ROW][C]18[/C][C]-0.187778[/C][C]-1.4545[/C][C]0.075506[/C][/ROW]
[ROW][C]19[/C][C]-0.2095[/C][C]-1.6228[/C][C]0.054939[/C][/ROW]
[ROW][C]20[/C][C]-0.201868[/C][C]-1.5637[/C][C]0.061579[/C][/ROW]
[ROW][C]21[/C][C]-0.110291[/C][C]-0.8543[/C][C]0.198167[/C][/ROW]
[ROW][C]22[/C][C]0.038395[/C][C]0.2974[/C][C]0.383591[/C][/ROW]
[ROW][C]23[/C][C]0.137996[/C][C]1.0689[/C][C]0.144696[/C][/ROW]
[ROW][C]24[/C][C]0.145188[/C][C]1.1246[/C][C]0.132615[/C][/ROW]
[ROW][C]25[/C][C]-0.027298[/C][C]-0.2115[/C][C]0.416626[/C][/ROW]
[ROW][C]26[/C][C]-0.197141[/C][C]-1.5271[/C][C]0.066002[/C][/ROW]
[ROW][C]27[/C][C]-0.261213[/C][C]-2.0233[/C][C]0.023749[/C][/ROW]
[ROW][C]28[/C][C]-0.270777[/C][C]-2.0974[/C][C]0.020089[/C][/ROW]
[ROW][C]29[/C][C]-0.239241[/C][C]-1.8532[/C][C]0.03439[/C][/ROW]
[ROW][C]30[/C][C]-0.199435[/C][C]-1.5448[/C][C]0.063825[/C][/ROW]
[ROW][C]31[/C][C]-0.182492[/C][C]-1.4136[/C][C]0.081327[/C][/ROW]
[ROW][C]32[/C][C]-0.183723[/C][C]-1.4231[/C][C]0.079941[/C][/ROW]
[ROW][C]33[/C][C]-0.128069[/C][C]-0.992[/C][C]0.162587[/C][/ROW]
[ROW][C]34[/C][C]-0.019271[/C][C]-0.1493[/C][C]0.440921[/C][/ROW]
[ROW][C]35[/C][C]0.03994[/C][C]0.3094[/C][C]0.379055[/C][/ROW]
[ROW][C]36[/C][C]0.032659[/C][C]0.253[/C][C]0.400576[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58907&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58907&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
10.7254955.61970
20.3339932.58710.00606
30.0923260.71520.238644
40.0252830.19580.422698
50.1058710.82010.207711
60.1765861.36780.088233
70.1392691.07880.142503
80.0478420.37060.356126
90.0564060.43690.33187
100.1819541.40940.081938
110.3171262.45640.008471
120.375172.90610.00256
130.1872771.45060.076044
14-0.033385-0.25860.398416
15-0.138561-1.07330.143719
16-0.188132-1.45730.075129
17-0.183913-1.42460.079729
18-0.187778-1.45450.075506
19-0.2095-1.62280.054939
20-0.201868-1.56370.061579
21-0.110291-0.85430.198167
220.0383950.29740.383591
230.1379961.06890.144696
240.1451881.12460.132615
25-0.027298-0.21150.416626
26-0.197141-1.52710.066002
27-0.261213-2.02330.023749
28-0.270777-2.09740.020089
29-0.239241-1.85320.03439
30-0.199435-1.54480.063825
31-0.182492-1.41360.081327
32-0.183723-1.42310.079941
33-0.128069-0.9920.162587
34-0.019271-0.14930.440921
350.039940.30940.379055
360.0326590.2530.400576






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7254955.61970
2-0.406096-3.14560.001289
30.116890.90540.184431
40.0445310.34490.365674
50.1794821.39030.084793
6-0.048188-0.37330.355133
7-0.062889-0.48710.313969
8-0.004286-0.03320.486812
90.2180651.68910.048193
100.1452281.12490.132549
110.0804290.6230.267823
120.0636370.49290.31193
13-0.348411-2.69880.004513
140.1407521.09030.13998
15-0.113292-0.87760.191842
16-0.19735-1.52870.065801
17-0.101108-0.78320.218301
18-0.118886-0.92090.1804
190.0068950.05340.478792
200.0003210.00250.499013
210.0334410.2590.398248
220.0665040.51510.304175
230.109230.84610.200432
240.0037520.02910.488456
25-0.157249-1.2180.113987
260.0711980.55150.291672
27-0.118876-0.92080.180418
280.0175110.13560.44628
29-0.092775-0.71860.237579
300.0178950.13860.445111
31-0.046295-0.35860.360578
32-0.117188-0.90770.183825
330.025130.19470.423159
34-0.044255-0.34280.366476
35-0.00768-0.05950.476379
36-0.062062-0.48070.316229

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.725495 & 5.6197 & 0 \tabularnewline
2 & -0.406096 & -3.1456 & 0.001289 \tabularnewline
3 & 0.11689 & 0.9054 & 0.184431 \tabularnewline
4 & 0.044531 & 0.3449 & 0.365674 \tabularnewline
5 & 0.179482 & 1.3903 & 0.084793 \tabularnewline
6 & -0.048188 & -0.3733 & 0.355133 \tabularnewline
7 & -0.062889 & -0.4871 & 0.313969 \tabularnewline
8 & -0.004286 & -0.0332 & 0.486812 \tabularnewline
9 & 0.218065 & 1.6891 & 0.048193 \tabularnewline
10 & 0.145228 & 1.1249 & 0.132549 \tabularnewline
11 & 0.080429 & 0.623 & 0.267823 \tabularnewline
12 & 0.063637 & 0.4929 & 0.31193 \tabularnewline
13 & -0.348411 & -2.6988 & 0.004513 \tabularnewline
14 & 0.140752 & 1.0903 & 0.13998 \tabularnewline
15 & -0.113292 & -0.8776 & 0.191842 \tabularnewline
16 & -0.19735 & -1.5287 & 0.065801 \tabularnewline
17 & -0.101108 & -0.7832 & 0.218301 \tabularnewline
18 & -0.118886 & -0.9209 & 0.1804 \tabularnewline
19 & 0.006895 & 0.0534 & 0.478792 \tabularnewline
20 & 0.000321 & 0.0025 & 0.499013 \tabularnewline
21 & 0.033441 & 0.259 & 0.398248 \tabularnewline
22 & 0.066504 & 0.5151 & 0.304175 \tabularnewline
23 & 0.10923 & 0.8461 & 0.200432 \tabularnewline
24 & 0.003752 & 0.0291 & 0.488456 \tabularnewline
25 & -0.157249 & -1.218 & 0.113987 \tabularnewline
26 & 0.071198 & 0.5515 & 0.291672 \tabularnewline
27 & -0.118876 & -0.9208 & 0.180418 \tabularnewline
28 & 0.017511 & 0.1356 & 0.44628 \tabularnewline
29 & -0.092775 & -0.7186 & 0.237579 \tabularnewline
30 & 0.017895 & 0.1386 & 0.445111 \tabularnewline
31 & -0.046295 & -0.3586 & 0.360578 \tabularnewline
32 & -0.117188 & -0.9077 & 0.183825 \tabularnewline
33 & 0.02513 & 0.1947 & 0.423159 \tabularnewline
34 & -0.044255 & -0.3428 & 0.366476 \tabularnewline
35 & -0.00768 & -0.0595 & 0.476379 \tabularnewline
36 & -0.062062 & -0.4807 & 0.316229 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58907&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]0.725495[/C][C]5.6197[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.406096[/C][C]-3.1456[/C][C]0.001289[/C][/ROW]
[ROW][C]3[/C][C]0.11689[/C][C]0.9054[/C][C]0.184431[/C][/ROW]
[ROW][C]4[/C][C]0.044531[/C][C]0.3449[/C][C]0.365674[/C][/ROW]
[ROW][C]5[/C][C]0.179482[/C][C]1.3903[/C][C]0.084793[/C][/ROW]
[ROW][C]6[/C][C]-0.048188[/C][C]-0.3733[/C][C]0.355133[/C][/ROW]
[ROW][C]7[/C][C]-0.062889[/C][C]-0.4871[/C][C]0.313969[/C][/ROW]
[ROW][C]8[/C][C]-0.004286[/C][C]-0.0332[/C][C]0.486812[/C][/ROW]
[ROW][C]9[/C][C]0.218065[/C][C]1.6891[/C][C]0.048193[/C][/ROW]
[ROW][C]10[/C][C]0.145228[/C][C]1.1249[/C][C]0.132549[/C][/ROW]
[ROW][C]11[/C][C]0.080429[/C][C]0.623[/C][C]0.267823[/C][/ROW]
[ROW][C]12[/C][C]0.063637[/C][C]0.4929[/C][C]0.31193[/C][/ROW]
[ROW][C]13[/C][C]-0.348411[/C][C]-2.6988[/C][C]0.004513[/C][/ROW]
[ROW][C]14[/C][C]0.140752[/C][C]1.0903[/C][C]0.13998[/C][/ROW]
[ROW][C]15[/C][C]-0.113292[/C][C]-0.8776[/C][C]0.191842[/C][/ROW]
[ROW][C]16[/C][C]-0.19735[/C][C]-1.5287[/C][C]0.065801[/C][/ROW]
[ROW][C]17[/C][C]-0.101108[/C][C]-0.7832[/C][C]0.218301[/C][/ROW]
[ROW][C]18[/C][C]-0.118886[/C][C]-0.9209[/C][C]0.1804[/C][/ROW]
[ROW][C]19[/C][C]0.006895[/C][C]0.0534[/C][C]0.478792[/C][/ROW]
[ROW][C]20[/C][C]0.000321[/C][C]0.0025[/C][C]0.499013[/C][/ROW]
[ROW][C]21[/C][C]0.033441[/C][C]0.259[/C][C]0.398248[/C][/ROW]
[ROW][C]22[/C][C]0.066504[/C][C]0.5151[/C][C]0.304175[/C][/ROW]
[ROW][C]23[/C][C]0.10923[/C][C]0.8461[/C][C]0.200432[/C][/ROW]
[ROW][C]24[/C][C]0.003752[/C][C]0.0291[/C][C]0.488456[/C][/ROW]
[ROW][C]25[/C][C]-0.157249[/C][C]-1.218[/C][C]0.113987[/C][/ROW]
[ROW][C]26[/C][C]0.071198[/C][C]0.5515[/C][C]0.291672[/C][/ROW]
[ROW][C]27[/C][C]-0.118876[/C][C]-0.9208[/C][C]0.180418[/C][/ROW]
[ROW][C]28[/C][C]0.017511[/C][C]0.1356[/C][C]0.44628[/C][/ROW]
[ROW][C]29[/C][C]-0.092775[/C][C]-0.7186[/C][C]0.237579[/C][/ROW]
[ROW][C]30[/C][C]0.017895[/C][C]0.1386[/C][C]0.445111[/C][/ROW]
[ROW][C]31[/C][C]-0.046295[/C][C]-0.3586[/C][C]0.360578[/C][/ROW]
[ROW][C]32[/C][C]-0.117188[/C][C]-0.9077[/C][C]0.183825[/C][/ROW]
[ROW][C]33[/C][C]0.02513[/C][C]0.1947[/C][C]0.423159[/C][/ROW]
[ROW][C]34[/C][C]-0.044255[/C][C]-0.3428[/C][C]0.366476[/C][/ROW]
[ROW][C]35[/C][C]-0.00768[/C][C]-0.0595[/C][C]0.476379[/C][/ROW]
[ROW][C]36[/C][C]-0.062062[/C][C]-0.4807[/C][C]0.316229[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58907&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58907&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
10.7254955.61970
2-0.406096-3.14560.001289
30.116890.90540.184431
40.0445310.34490.365674
50.1794821.39030.084793
6-0.048188-0.37330.355133
7-0.062889-0.48710.313969
8-0.004286-0.03320.486812
90.2180651.68910.048193
100.1452281.12490.132549
110.0804290.6230.267823
120.0636370.49290.31193
13-0.348411-2.69880.004513
140.1407521.09030.13998
15-0.113292-0.87760.191842
16-0.19735-1.52870.065801
17-0.101108-0.78320.218301
18-0.118886-0.92090.1804
190.0068950.05340.478792
200.0003210.00250.499013
210.0334410.2590.398248
220.0665040.51510.304175
230.109230.84610.200432
240.0037520.02910.488456
25-0.157249-1.2180.113987
260.0711980.55150.291672
27-0.118876-0.92080.180418
280.0175110.13560.44628
29-0.092775-0.71860.237579
300.0178950.13860.445111
31-0.046295-0.35860.360578
32-0.117188-0.90770.183825
330.025130.19470.423159
34-0.044255-0.34280.366476
35-0.00768-0.05950.476379
36-0.062062-0.48070.316229


Figures (Output of Computation)

Input Parameters & R Code

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