FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 04 Dec 2009 13:48:20 -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/04/t1259959745ci5oriko0xpc2sm.htm/, Retrieved Sun, 28 Apr 2024 07:40:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64149, Retrieved Sun, 28 Apr 2024 07:40:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Shw8: Method 1 AC...] [2009-11-27 11:38:48] [3c8b83428ce260cd44df892bb7619588]
-   P           [(Partial) Autocorrelation Function] [SHWWS8reviw3] [2009-11-29 15:06:16] [a66d3a79ef9e5308cd94a469bc5ca464]
-   PD              [(Partial) Autocorrelation Function] [SHWREviewws8] [2009-12-04 20:48:20] [db49399df1e4a3dbe31268849cebfd7f] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.75
3.75
3.55
3.5
3.5
3.1
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3.21
3.25
3.25
3.45
3.5
3.5
3.64
3.75
3.93
4
4.17
4.25
4.39
4.5
4.5
4.65
4.75
4.75
4.9
5
5
5
5
5
5
5
5
5
5
5
5
5.18
5.25
5.25
4.49
3.92
3.25

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=64149&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=64149&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64149&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
1-0.313496-2.62290.005346
2-0.026368-0.22060.41302
30.0860830.72020.236894
4-0.042849-0.35850.360523
5-0.03791-0.31720.376026
60.0072640.06080.475857
70.0060140.05030.480007
80.0033510.0280.488857
9-0.009678-0.0810.467848
100.0298270.24950.401834
11-0.078452-0.65640.256867
120.0636050.53220.29815
130.0300030.2510.401264
14-0.044667-0.37370.354875
150.075090.62820.265944
16-0.05494-0.45970.323591
170.0091090.07620.469735
180.034540.2890.386723
19-0.06827-0.57120.284852
200.058520.48960.312968
210.007940.06640.473611
22-0.052467-0.4390.331019
230.0780890.65330.257838
24-0.082732-0.69220.245554
250.1049680.87820.191413
26-0.084143-0.7040.241887
270.0109910.0920.463498
28-0.03372-0.28210.389341
290.073260.61290.270951
30-0.070757-0.5920.27788
31-0.025552-0.21380.415669
320.1207291.01010.157965
33-0.089289-0.7470.228768
34-0.075403-0.63090.265091
350.1124420.94080.175032
36-0.114087-0.95450.171553

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.313496 & -2.6229 & 0.005346 \tabularnewline
2 & -0.026368 & -0.2206 & 0.41302 \tabularnewline
3 & 0.086083 & 0.7202 & 0.236894 \tabularnewline
4 & -0.042849 & -0.3585 & 0.360523 \tabularnewline
5 & -0.03791 & -0.3172 & 0.376026 \tabularnewline
6 & 0.007264 & 0.0608 & 0.475857 \tabularnewline
7 & 0.006014 & 0.0503 & 0.480007 \tabularnewline
8 & 0.003351 & 0.028 & 0.488857 \tabularnewline
9 & -0.009678 & -0.081 & 0.467848 \tabularnewline
10 & 0.029827 & 0.2495 & 0.401834 \tabularnewline
11 & -0.078452 & -0.6564 & 0.256867 \tabularnewline
12 & 0.063605 & 0.5322 & 0.29815 \tabularnewline
13 & 0.030003 & 0.251 & 0.401264 \tabularnewline
14 & -0.044667 & -0.3737 & 0.354875 \tabularnewline
15 & 0.07509 & 0.6282 & 0.265944 \tabularnewline
16 & -0.05494 & -0.4597 & 0.323591 \tabularnewline
17 & 0.009109 & 0.0762 & 0.469735 \tabularnewline
18 & 0.03454 & 0.289 & 0.386723 \tabularnewline
19 & -0.06827 & -0.5712 & 0.284852 \tabularnewline
20 & 0.05852 & 0.4896 & 0.312968 \tabularnewline
21 & 0.00794 & 0.0664 & 0.473611 \tabularnewline
22 & -0.052467 & -0.439 & 0.331019 \tabularnewline
23 & 0.078089 & 0.6533 & 0.257838 \tabularnewline
24 & -0.082732 & -0.6922 & 0.245554 \tabularnewline
25 & 0.104968 & 0.8782 & 0.191413 \tabularnewline
26 & -0.084143 & -0.704 & 0.241887 \tabularnewline
27 & 0.010991 & 0.092 & 0.463498 \tabularnewline
28 & -0.03372 & -0.2821 & 0.389341 \tabularnewline
29 & 0.07326 & 0.6129 & 0.270951 \tabularnewline
30 & -0.070757 & -0.592 & 0.27788 \tabularnewline
31 & -0.025552 & -0.2138 & 0.415669 \tabularnewline
32 & 0.120729 & 1.0101 & 0.157965 \tabularnewline
33 & -0.089289 & -0.747 & 0.228768 \tabularnewline
34 & -0.075403 & -0.6309 & 0.265091 \tabularnewline
35 & 0.112442 & 0.9408 & 0.175032 \tabularnewline
36 & -0.114087 & -0.9545 & 0.171553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64149&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]-0.313496[/C][C]-2.6229[/C][C]0.005346[/C][/ROW]
[ROW][C]2[/C][C]-0.026368[/C][C]-0.2206[/C][C]0.41302[/C][/ROW]
[ROW][C]3[/C][C]0.086083[/C][C]0.7202[/C][C]0.236894[/C][/ROW]
[ROW][C]4[/C][C]-0.042849[/C][C]-0.3585[/C][C]0.360523[/C][/ROW]
[ROW][C]5[/C][C]-0.03791[/C][C]-0.3172[/C][C]0.376026[/C][/ROW]
[ROW][C]6[/C][C]0.007264[/C][C]0.0608[/C][C]0.475857[/C][/ROW]
[ROW][C]7[/C][C]0.006014[/C][C]0.0503[/C][C]0.480007[/C][/ROW]
[ROW][C]8[/C][C]0.003351[/C][C]0.028[/C][C]0.488857[/C][/ROW]
[ROW][C]9[/C][C]-0.009678[/C][C]-0.081[/C][C]0.467848[/C][/ROW]
[ROW][C]10[/C][C]0.029827[/C][C]0.2495[/C][C]0.401834[/C][/ROW]
[ROW][C]11[/C][C]-0.078452[/C][C]-0.6564[/C][C]0.256867[/C][/ROW]
[ROW][C]12[/C][C]0.063605[/C][C]0.5322[/C][C]0.29815[/C][/ROW]
[ROW][C]13[/C][C]0.030003[/C][C]0.251[/C][C]0.401264[/C][/ROW]
[ROW][C]14[/C][C]-0.044667[/C][C]-0.3737[/C][C]0.354875[/C][/ROW]
[ROW][C]15[/C][C]0.07509[/C][C]0.6282[/C][C]0.265944[/C][/ROW]
[ROW][C]16[/C][C]-0.05494[/C][C]-0.4597[/C][C]0.323591[/C][/ROW]
[ROW][C]17[/C][C]0.009109[/C][C]0.0762[/C][C]0.469735[/C][/ROW]
[ROW][C]18[/C][C]0.03454[/C][C]0.289[/C][C]0.386723[/C][/ROW]
[ROW][C]19[/C][C]-0.06827[/C][C]-0.5712[/C][C]0.284852[/C][/ROW]
[ROW][C]20[/C][C]0.05852[/C][C]0.4896[/C][C]0.312968[/C][/ROW]
[ROW][C]21[/C][C]0.00794[/C][C]0.0664[/C][C]0.473611[/C][/ROW]
[ROW][C]22[/C][C]-0.052467[/C][C]-0.439[/C][C]0.331019[/C][/ROW]
[ROW][C]23[/C][C]0.078089[/C][C]0.6533[/C][C]0.257838[/C][/ROW]
[ROW][C]24[/C][C]-0.082732[/C][C]-0.6922[/C][C]0.245554[/C][/ROW]
[ROW][C]25[/C][C]0.104968[/C][C]0.8782[/C][C]0.191413[/C][/ROW]
[ROW][C]26[/C][C]-0.084143[/C][C]-0.704[/C][C]0.241887[/C][/ROW]
[ROW][C]27[/C][C]0.010991[/C][C]0.092[/C][C]0.463498[/C][/ROW]
[ROW][C]28[/C][C]-0.03372[/C][C]-0.2821[/C][C]0.389341[/C][/ROW]
[ROW][C]29[/C][C]0.07326[/C][C]0.6129[/C][C]0.270951[/C][/ROW]
[ROW][C]30[/C][C]-0.070757[/C][C]-0.592[/C][C]0.27788[/C][/ROW]
[ROW][C]31[/C][C]-0.025552[/C][C]-0.2138[/C][C]0.415669[/C][/ROW]
[ROW][C]32[/C][C]0.120729[/C][C]1.0101[/C][C]0.157965[/C][/ROW]
[ROW][C]33[/C][C]-0.089289[/C][C]-0.747[/C][C]0.228768[/C][/ROW]
[ROW][C]34[/C][C]-0.075403[/C][C]-0.6309[/C][C]0.265091[/C][/ROW]
[ROW][C]35[/C][C]0.112442[/C][C]0.9408[/C][C]0.175032[/C][/ROW]
[ROW][C]36[/C][C]-0.114087[/C][C]-0.9545[/C][C]0.171553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64149&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64149&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
1-0.313496-2.62290.005346
2-0.026368-0.22060.41302
30.0860830.72020.236894
4-0.042849-0.35850.360523
5-0.03791-0.31720.376026
60.0072640.06080.475857
70.0060140.05030.480007
80.0033510.0280.488857
9-0.009678-0.0810.467848
100.0298270.24950.401834
11-0.078452-0.65640.256867
120.0636050.53220.29815
130.0300030.2510.401264
14-0.044667-0.37370.354875
150.075090.62820.265944
16-0.05494-0.45970.323591
170.0091090.07620.469735
180.034540.2890.386723
19-0.06827-0.57120.284852
200.058520.48960.312968
210.007940.06640.473611
22-0.052467-0.4390.331019
230.0780890.65330.257838
24-0.082732-0.69220.245554
250.1049680.87820.191413
26-0.084143-0.7040.241887
270.0109910.0920.463498
28-0.03372-0.28210.389341
290.073260.61290.270951
30-0.070757-0.5920.27788
31-0.025552-0.21380.415669
320.1207291.01010.157965
33-0.089289-0.7470.228768
34-0.075403-0.63090.265091
350.1124420.94080.175032
36-0.114087-0.95450.171553






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.313496-2.62290.005346
2-0.138233-1.15650.125696
30.0376920.31540.376715
4-0.004591-0.03840.484736
5-0.048308-0.40420.343659
6-0.033663-0.28160.389524
7-0.005372-0.04490.48214
80.0103070.08620.465764
9-0.006156-0.05150.479535
100.0244740.20480.419176
11-0.071946-0.60190.274577
120.0218840.18310.427627
130.0537310.44950.327213
14-0.001284-0.01070.495731
150.06370.5330.297877
16-0.02626-0.21970.413369
17-0.001288-0.01080.495715
180.0328540.27490.392109
19-0.042872-0.35870.360453
200.0303580.2540.400122
210.029310.24520.403499
22-0.03756-0.31420.377133
230.0577540.48320.315228
24-0.051344-0.42960.334414
250.0820320.68630.247386
26-0.03696-0.30920.379034
27-0.021798-0.18240.427909
28-0.065258-0.5460.293406
290.0688730.57620.283153
30-0.047004-0.39330.347659
31-0.048526-0.4060.342993
320.0925910.77470.220571
33-0.046242-0.38690.350005
34-0.086993-0.72780.23457
350.0198270.16590.434365
36-0.076561-0.64060.261951

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.313496 & -2.6229 & 0.005346 \tabularnewline
2 & -0.138233 & -1.1565 & 0.125696 \tabularnewline
3 & 0.037692 & 0.3154 & 0.376715 \tabularnewline
4 & -0.004591 & -0.0384 & 0.484736 \tabularnewline
5 & -0.048308 & -0.4042 & 0.343659 \tabularnewline
6 & -0.033663 & -0.2816 & 0.389524 \tabularnewline
7 & -0.005372 & -0.0449 & 0.48214 \tabularnewline
8 & 0.010307 & 0.0862 & 0.465764 \tabularnewline
9 & -0.006156 & -0.0515 & 0.479535 \tabularnewline
10 & 0.024474 & 0.2048 & 0.419176 \tabularnewline
11 & -0.071946 & -0.6019 & 0.274577 \tabularnewline
12 & 0.021884 & 0.1831 & 0.427627 \tabularnewline
13 & 0.053731 & 0.4495 & 0.327213 \tabularnewline
14 & -0.001284 & -0.0107 & 0.495731 \tabularnewline
15 & 0.0637 & 0.533 & 0.297877 \tabularnewline
16 & -0.02626 & -0.2197 & 0.413369 \tabularnewline
17 & -0.001288 & -0.0108 & 0.495715 \tabularnewline
18 & 0.032854 & 0.2749 & 0.392109 \tabularnewline
19 & -0.042872 & -0.3587 & 0.360453 \tabularnewline
20 & 0.030358 & 0.254 & 0.400122 \tabularnewline
21 & 0.02931 & 0.2452 & 0.403499 \tabularnewline
22 & -0.03756 & -0.3142 & 0.377133 \tabularnewline
23 & 0.057754 & 0.4832 & 0.315228 \tabularnewline
24 & -0.051344 & -0.4296 & 0.334414 \tabularnewline
25 & 0.082032 & 0.6863 & 0.247386 \tabularnewline
26 & -0.03696 & -0.3092 & 0.379034 \tabularnewline
27 & -0.021798 & -0.1824 & 0.427909 \tabularnewline
28 & -0.065258 & -0.546 & 0.293406 \tabularnewline
29 & 0.068873 & 0.5762 & 0.283153 \tabularnewline
30 & -0.047004 & -0.3933 & 0.347659 \tabularnewline
31 & -0.048526 & -0.406 & 0.342993 \tabularnewline
32 & 0.092591 & 0.7747 & 0.220571 \tabularnewline
33 & -0.046242 & -0.3869 & 0.350005 \tabularnewline
34 & -0.086993 & -0.7278 & 0.23457 \tabularnewline
35 & 0.019827 & 0.1659 & 0.434365 \tabularnewline
36 & -0.076561 & -0.6406 & 0.261951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64149&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]-0.313496[/C][C]-2.6229[/C][C]0.005346[/C][/ROW]
[ROW][C]2[/C][C]-0.138233[/C][C]-1.1565[/C][C]0.125696[/C][/ROW]
[ROW][C]3[/C][C]0.037692[/C][C]0.3154[/C][C]0.376715[/C][/ROW]
[ROW][C]4[/C][C]-0.004591[/C][C]-0.0384[/C][C]0.484736[/C][/ROW]
[ROW][C]5[/C][C]-0.048308[/C][C]-0.4042[/C][C]0.343659[/C][/ROW]
[ROW][C]6[/C][C]-0.033663[/C][C]-0.2816[/C][C]0.389524[/C][/ROW]
[ROW][C]7[/C][C]-0.005372[/C][C]-0.0449[/C][C]0.48214[/C][/ROW]
[ROW][C]8[/C][C]0.010307[/C][C]0.0862[/C][C]0.465764[/C][/ROW]
[ROW][C]9[/C][C]-0.006156[/C][C]-0.0515[/C][C]0.479535[/C][/ROW]
[ROW][C]10[/C][C]0.024474[/C][C]0.2048[/C][C]0.419176[/C][/ROW]
[ROW][C]11[/C][C]-0.071946[/C][C]-0.6019[/C][C]0.274577[/C][/ROW]
[ROW][C]12[/C][C]0.021884[/C][C]0.1831[/C][C]0.427627[/C][/ROW]
[ROW][C]13[/C][C]0.053731[/C][C]0.4495[/C][C]0.327213[/C][/ROW]
[ROW][C]14[/C][C]-0.001284[/C][C]-0.0107[/C][C]0.495731[/C][/ROW]
[ROW][C]15[/C][C]0.0637[/C][C]0.533[/C][C]0.297877[/C][/ROW]
[ROW][C]16[/C][C]-0.02626[/C][C]-0.2197[/C][C]0.413369[/C][/ROW]
[ROW][C]17[/C][C]-0.001288[/C][C]-0.0108[/C][C]0.495715[/C][/ROW]
[ROW][C]18[/C][C]0.032854[/C][C]0.2749[/C][C]0.392109[/C][/ROW]
[ROW][C]19[/C][C]-0.042872[/C][C]-0.3587[/C][C]0.360453[/C][/ROW]
[ROW][C]20[/C][C]0.030358[/C][C]0.254[/C][C]0.400122[/C][/ROW]
[ROW][C]21[/C][C]0.02931[/C][C]0.2452[/C][C]0.403499[/C][/ROW]
[ROW][C]22[/C][C]-0.03756[/C][C]-0.3142[/C][C]0.377133[/C][/ROW]
[ROW][C]23[/C][C]0.057754[/C][C]0.4832[/C][C]0.315228[/C][/ROW]
[ROW][C]24[/C][C]-0.051344[/C][C]-0.4296[/C][C]0.334414[/C][/ROW]
[ROW][C]25[/C][C]0.082032[/C][C]0.6863[/C][C]0.247386[/C][/ROW]
[ROW][C]26[/C][C]-0.03696[/C][C]-0.3092[/C][C]0.379034[/C][/ROW]
[ROW][C]27[/C][C]-0.021798[/C][C]-0.1824[/C][C]0.427909[/C][/ROW]
[ROW][C]28[/C][C]-0.065258[/C][C]-0.546[/C][C]0.293406[/C][/ROW]
[ROW][C]29[/C][C]0.068873[/C][C]0.5762[/C][C]0.283153[/C][/ROW]
[ROW][C]30[/C][C]-0.047004[/C][C]-0.3933[/C][C]0.347659[/C][/ROW]
[ROW][C]31[/C][C]-0.048526[/C][C]-0.406[/C][C]0.342993[/C][/ROW]
[ROW][C]32[/C][C]0.092591[/C][C]0.7747[/C][C]0.220571[/C][/ROW]
[ROW][C]33[/C][C]-0.046242[/C][C]-0.3869[/C][C]0.350005[/C][/ROW]
[ROW][C]34[/C][C]-0.086993[/C][C]-0.7278[/C][C]0.23457[/C][/ROW]
[ROW][C]35[/C][C]0.019827[/C][C]0.1659[/C][C]0.434365[/C][/ROW]
[ROW][C]36[/C][C]-0.076561[/C][C]-0.6406[/C][C]0.261951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64149&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64149&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
1-0.313496-2.62290.005346
2-0.138233-1.15650.125696
30.0376920.31540.376715
4-0.004591-0.03840.484736
5-0.048308-0.40420.343659
6-0.033663-0.28160.389524
7-0.005372-0.04490.48214
80.0103070.08620.465764
9-0.006156-0.05150.479535
100.0244740.20480.419176
11-0.071946-0.60190.274577
120.0218840.18310.427627
130.0537310.44950.327213
14-0.001284-0.01070.495731
150.06370.5330.297877
16-0.02626-0.21970.413369
17-0.001288-0.01080.495715
180.0328540.27490.392109
19-0.042872-0.35870.360453
200.0303580.2540.400122
210.029310.24520.403499
22-0.03756-0.31420.377133
230.0577540.48320.315228
24-0.051344-0.42960.334414
250.0820320.68630.247386
26-0.03696-0.30920.379034
27-0.021798-0.18240.427909
28-0.065258-0.5460.293406
290.0688730.57620.283153
30-0.047004-0.39330.347659
31-0.048526-0.4060.342993
320.0925910.77470.220571
33-0.046242-0.38690.350005
34-0.086993-0.72780.23457
350.0198270.16590.434365
36-0.076561-0.64060.261951


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')