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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 computationThu, 16 Dec 2010 15:06:34 +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/16/t12925118658clk9xbqeh2ibg4.htm/, Retrieved Fri, 03 May 2024 04:01:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110996, Retrieved Fri, 03 May 2024 04:01:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [] [2010-12-15 15:55:09] [c895532cb7349383dee5125244983cc8]
-             [(Partial) Autocorrelation Function] [TUM (ACF)] [2010-12-16 15:06:34] [a4848c79f7a98c5639a543e143e21e11] [Current]
-               [(Partial) Autocorrelation Function] [workshop 6] [2010-12-17 19:16:18] [916599f00c9c716123aa8433d9efa14f]
-   PD          [(Partial) Autocorrelation Function] [TUM] [2010-12-26 11:21:07] [c895532cb7349383dee5125244983cc8]
-                 [(Partial) Autocorrelation Function] [TUM (ACF)] [2010-12-28 08:54:31] [75b8170d590d2aca2c97c1862bb2167f]
-                 [(Partial) Autocorrelation Function] [berekening 10] [2010-12-28 14:01:16] [916599f00c9c716123aa8433d9efa14f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10
10
10
10
10
9,94
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
9,94
9,94
9,94
9,94
9,94
9,94
10,06
10,06
9,94
10,06
10,06
10,06
10,18
10,28
10,28
10,18
10,28
10,28
10,28
10,18
10,28
10,28
10,18
10,18
10,18
10,28
10,28
10,18
10,18
10,18
10,18
10,18
10,18
10,28
10,28
10,28
10,18
10,18
10,18
10,28
10,18
10,18
10,28
10,18
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,42
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,34
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,34
10,34
10,34
10,34
10,34
10,42
10,42
10,42
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,42
10,42
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,49
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,63
10,63
10,63
10,63
10,63
10,57
10,63
10,63
10,63
10,63
10,57
10,57
10,57
10,63
10,63
10,63
10,63
10,57
10,63
10,63
10,57
10,63
10,63
10,63
10,63
10,57
10,63
10,6
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,6
10,6
10,6
10,6
10,7
10,7
10,6
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,8
10,8
10,8
10,8
10,7
10,7
10,7
10,85
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,75
10,75
10,85
10,85
10,85
10,85
10,75
10,75
10,75
10,75
10,75

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110996&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110996&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110996&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97174818.17970
20.95185617.80760
30.93705517.53070
40.92421817.29050
50.91269517.0750
60.89520716.74780
70.88447916.54710
80.87025816.2810
90.85515215.99840
100.8417315.74730
110.83336615.59090
120.82540615.44190
130.81578915.2620
140.80664915.0910
150.79457114.86510
160.78275414.6440
170.77030214.4110
180.76093514.23580
190.75288414.08520
200.74082913.85960
210.72758313.61180
220.71276513.33460
230.70009213.09750
240.6894612.89860
250.6760612.64790

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.971748 & 18.1797 & 0 \tabularnewline
2 & 0.951856 & 17.8076 & 0 \tabularnewline
3 & 0.937055 & 17.5307 & 0 \tabularnewline
4 & 0.924218 & 17.2905 & 0 \tabularnewline
5 & 0.912695 & 17.075 & 0 \tabularnewline
6 & 0.895207 & 16.7478 & 0 \tabularnewline
7 & 0.884479 & 16.5471 & 0 \tabularnewline
8 & 0.870258 & 16.281 & 0 \tabularnewline
9 & 0.855152 & 15.9984 & 0 \tabularnewline
10 & 0.84173 & 15.7473 & 0 \tabularnewline
11 & 0.833366 & 15.5909 & 0 \tabularnewline
12 & 0.825406 & 15.4419 & 0 \tabularnewline
13 & 0.815789 & 15.262 & 0 \tabularnewline
14 & 0.806649 & 15.091 & 0 \tabularnewline
15 & 0.794571 & 14.8651 & 0 \tabularnewline
16 & 0.782754 & 14.644 & 0 \tabularnewline
17 & 0.770302 & 14.411 & 0 \tabularnewline
18 & 0.760935 & 14.2358 & 0 \tabularnewline
19 & 0.752884 & 14.0852 & 0 \tabularnewline
20 & 0.740829 & 13.8596 & 0 \tabularnewline
21 & 0.727583 & 13.6118 & 0 \tabularnewline
22 & 0.712765 & 13.3346 & 0 \tabularnewline
23 & 0.700092 & 13.0975 & 0 \tabularnewline
24 & 0.68946 & 12.8986 & 0 \tabularnewline
25 & 0.67606 & 12.6479 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110996&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]0.971748[/C][C]18.1797[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.951856[/C][C]17.8076[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.937055[/C][C]17.5307[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.924218[/C][C]17.2905[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.912695[/C][C]17.075[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.895207[/C][C]16.7478[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.884479[/C][C]16.5471[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.870258[/C][C]16.281[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.855152[/C][C]15.9984[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.84173[/C][C]15.7473[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.833366[/C][C]15.5909[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.825406[/C][C]15.4419[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.815789[/C][C]15.262[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.806649[/C][C]15.091[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.794571[/C][C]14.8651[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.782754[/C][C]14.644[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.770302[/C][C]14.411[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.760935[/C][C]14.2358[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.752884[/C][C]14.0852[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.740829[/C][C]13.8596[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.727583[/C][C]13.6118[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.712765[/C][C]13.3346[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.700092[/C][C]13.0975[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.68946[/C][C]12.8986[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.67606[/C][C]12.6479[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110996&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110996&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
10.97174818.17970
20.95185617.80760
30.93705517.53070
40.92421817.29050
50.91269517.0750
60.89520716.74780
70.88447916.54710
80.87025816.2810
90.85515215.99840
100.8417315.74730
110.83336615.59090
120.82540615.44190
130.81578915.2620
140.80664915.0910
150.79457114.86510
160.78275414.6440
170.77030214.4110
180.76093514.23580
190.75288414.08520
200.74082913.85960
210.72758313.61180
220.71276513.33460
230.70009213.09750
240.6894612.89860
250.6760612.64790






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97174818.17970
20.135732.53930.00577
30.1050021.96440.025137
40.0609011.13940.127666
50.0457460.85580.19634
6-0.093038-1.74060.041319
70.0951491.78010.037965
8-0.053252-0.99620.159909
9-0.025465-0.47640.317044
100.0108930.20380.41932
110.1028871.92480.02753
120.0146250.27360.392273
130.015590.29170.385359
140.008460.15830.437164
15-0.05663-1.05950.145063
16-0.028718-0.53730.295713
17-0.017172-0.32130.374104
180.0344250.6440.259991
190.0235670.44090.32978
20-0.043518-0.81410.208058
21-0.036278-0.67870.248886
22-0.046168-0.86370.194166
230.0008490.01590.493671
240.0291350.54510.293029
25-0.046575-0.87130.192083

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.971748 & 18.1797 & 0 \tabularnewline
2 & 0.13573 & 2.5393 & 0.00577 \tabularnewline
3 & 0.105002 & 1.9644 & 0.025137 \tabularnewline
4 & 0.060901 & 1.1394 & 0.127666 \tabularnewline
5 & 0.045746 & 0.8558 & 0.19634 \tabularnewline
6 & -0.093038 & -1.7406 & 0.041319 \tabularnewline
7 & 0.095149 & 1.7801 & 0.037965 \tabularnewline
8 & -0.053252 & -0.9962 & 0.159909 \tabularnewline
9 & -0.025465 & -0.4764 & 0.317044 \tabularnewline
10 & 0.010893 & 0.2038 & 0.41932 \tabularnewline
11 & 0.102887 & 1.9248 & 0.02753 \tabularnewline
12 & 0.014625 & 0.2736 & 0.392273 \tabularnewline
13 & 0.01559 & 0.2917 & 0.385359 \tabularnewline
14 & 0.00846 & 0.1583 & 0.437164 \tabularnewline
15 & -0.05663 & -1.0595 & 0.145063 \tabularnewline
16 & -0.028718 & -0.5373 & 0.295713 \tabularnewline
17 & -0.017172 & -0.3213 & 0.374104 \tabularnewline
18 & 0.034425 & 0.644 & 0.259991 \tabularnewline
19 & 0.023567 & 0.4409 & 0.32978 \tabularnewline
20 & -0.043518 & -0.8141 & 0.208058 \tabularnewline
21 & -0.036278 & -0.6787 & 0.248886 \tabularnewline
22 & -0.046168 & -0.8637 & 0.194166 \tabularnewline
23 & 0.000849 & 0.0159 & 0.493671 \tabularnewline
24 & 0.029135 & 0.5451 & 0.293029 \tabularnewline
25 & -0.046575 & -0.8713 & 0.192083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110996&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]0.971748[/C][C]18.1797[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.13573[/C][C]2.5393[/C][C]0.00577[/C][/ROW]
[ROW][C]3[/C][C]0.105002[/C][C]1.9644[/C][C]0.025137[/C][/ROW]
[ROW][C]4[/C][C]0.060901[/C][C]1.1394[/C][C]0.127666[/C][/ROW]
[ROW][C]5[/C][C]0.045746[/C][C]0.8558[/C][C]0.19634[/C][/ROW]
[ROW][C]6[/C][C]-0.093038[/C][C]-1.7406[/C][C]0.041319[/C][/ROW]
[ROW][C]7[/C][C]0.095149[/C][C]1.7801[/C][C]0.037965[/C][/ROW]
[ROW][C]8[/C][C]-0.053252[/C][C]-0.9962[/C][C]0.159909[/C][/ROW]
[ROW][C]9[/C][C]-0.025465[/C][C]-0.4764[/C][C]0.317044[/C][/ROW]
[ROW][C]10[/C][C]0.010893[/C][C]0.2038[/C][C]0.41932[/C][/ROW]
[ROW][C]11[/C][C]0.102887[/C][C]1.9248[/C][C]0.02753[/C][/ROW]
[ROW][C]12[/C][C]0.014625[/C][C]0.2736[/C][C]0.392273[/C][/ROW]
[ROW][C]13[/C][C]0.01559[/C][C]0.2917[/C][C]0.385359[/C][/ROW]
[ROW][C]14[/C][C]0.00846[/C][C]0.1583[/C][C]0.437164[/C][/ROW]
[ROW][C]15[/C][C]-0.05663[/C][C]-1.0595[/C][C]0.145063[/C][/ROW]
[ROW][C]16[/C][C]-0.028718[/C][C]-0.5373[/C][C]0.295713[/C][/ROW]
[ROW][C]17[/C][C]-0.017172[/C][C]-0.3213[/C][C]0.374104[/C][/ROW]
[ROW][C]18[/C][C]0.034425[/C][C]0.644[/C][C]0.259991[/C][/ROW]
[ROW][C]19[/C][C]0.023567[/C][C]0.4409[/C][C]0.32978[/C][/ROW]
[ROW][C]20[/C][C]-0.043518[/C][C]-0.8141[/C][C]0.208058[/C][/ROW]
[ROW][C]21[/C][C]-0.036278[/C][C]-0.6787[/C][C]0.248886[/C][/ROW]
[ROW][C]22[/C][C]-0.046168[/C][C]-0.8637[/C][C]0.194166[/C][/ROW]
[ROW][C]23[/C][C]0.000849[/C][C]0.0159[/C][C]0.493671[/C][/ROW]
[ROW][C]24[/C][C]0.029135[/C][C]0.5451[/C][C]0.293029[/C][/ROW]
[ROW][C]25[/C][C]-0.046575[/C][C]-0.8713[/C][C]0.192083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110996&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110996&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
10.97174818.17970
20.135732.53930.00577
30.1050021.96440.025137
40.0609011.13940.127666
50.0457460.85580.19634
6-0.093038-1.74060.041319
70.0951491.78010.037965
8-0.053252-0.99620.159909
9-0.025465-0.47640.317044
100.0108930.20380.41932
110.1028871.92480.02753
120.0146250.27360.392273
130.015590.29170.385359
140.008460.15830.437164
15-0.05663-1.05950.145063
16-0.028718-0.53730.295713
17-0.017172-0.32130.374104
180.0344250.6440.259991
190.0235670.44090.32978
20-0.043518-0.81410.208058
21-0.036278-0.67870.248886
22-0.046168-0.86370.194166
230.0008490.01590.493671
240.0291350.54510.293029
25-0.046575-0.87130.192083


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')