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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 computationWed, 17 Dec 2014 14:30:31 +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/2014/Dec/17/t1418826701dt6ol0tfj1bfvm9.htm/, Retrieved Thu, 16 May 2024 14:50:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270333, Retrieved Thu, 16 May 2024 14:50:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [(Partial) Autocorrelation Function] [] [2011-12-06 19:49:59] [b98453cac15ba1066b407e146608df68]
- RMP     [(Partial) Autocorrelation Function] [] [2014-11-26 15:01:01] [bcf5edf18529a33bd1494456d2c6cb9a]
- R PD        [(Partial) Autocorrelation Function] [] [2014-12-17 14:30:31] [6fc1b517ba5ef695988bbc0a377c4b82] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.90
7.40
12.20
12.80
7.40
6.70
12.60
14.80
13.30
11.10
8.20
11.40
6.40
10.60
12.00
6.30
11.30
11.90
9.30
9.60
10.00
6.40
13.80
10.80
13.80
11.70
10.90
16.10
13.40
9.90
11.50
8.30
11.70
6.10
9.00
9.70
10.80
10.30
10.40
12.70
9.30
11.80
5.90
11.40
13.00
10.80
12.30
11.30
11.80
7.90
12.70
12.30
11.60
6.70
10.90
12.10
13.30
10.10
5.70
14.30
8.00
13.30
9.30
12.50
7.60
15.90
9.20
9.10
11.10
13.00
14.50
12.20
12.30
11.40
8.80
14.60
7.30
12.60
13.00
12.60
13.20
9.90
7.70
10.50
13.40
10.90
4.30
10.30
11.80
11.20
11.40
8.60
13.20
12.60
5.60
9.90
8.80
7.70
9.00
7.30
11.40
13.60
7.90
10.70
10.30
8.30
9.60
14.20
8.50
13.50
4.90
6.40
9.60
11.60
11.10
4.35
12.70
18.10
17.85
16.60
12.60
17.10
19.10
16.10
13.35
18.40
14.70
10.60
12.60
16.20
13.60
18.90
14.10
14.50
16.15
14.75
14.80
12.45
12.65
17.35
8.60
18.40
16.10
11.60
17.75
15.25
17.65
15.60
16.35
17.65
13.60
11.70
14.35
14.75
18.25
9.90
16.00
18.25
16.85
14.60
13.85
18.95
15.60
14.85
11.75
18.45
15.90
17.10
16.10
19.90
10.95
18.45
15.10
15.00
11.35
15.95
18.10
14.60
15.40
15.40
17.60
13.35
19.10
15.35
7.60
13.40
13.90
19.10
15.25
12.90
16.10
17.35
13.15
12.15
12.60
10.35
15.40
9.60
18.20
13.60
14.85
14.75
14.10
14.90
16.25
19.25
13.60
13.60
15.65
12.75
14.60
9.85
12.65
11.90
19.20
16.60
11.20
15.25
11.90
13.20
16.35
12.40
15.85
14.35
18.15
11.15
15.65
17.75
7.65
12.35
15.60
19.30
15.20
17.10
15.60
18.40
19.05
18.55
19.10
13.10
12.85
9.50
4.50
11.85
13.60
11.70
12.40
13.35
11.40
14.90
19.90
17.75
11.20
14.60
17.60
14.05
16.10
13.35
11.85
11.95
14.75
15.15
13.20
16.85
7.85
7.70
12.60
7.85
10.95
12.35
9.95
14.90
16.65
13.40
13.95
15.70
16.85
10.95
15.35
12.20
15.10
17.75
15.20
14.60
16.65
8.10

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270333&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270333&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270333&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1136561.88130.030492
20.1244732.06040.020153
30.1300852.15330.016084
40.1094241.81130.035595
50.1284512.12620.017188
6-0.026533-0.43920.330432
7-0.092619-1.53310.0632
8-0.087125-1.44220.075199
9-0.035246-0.58340.280044
10-0.068726-1.13760.128138
11-0.072231-1.19560.116436
12-0.475379-7.86890
13-0.024252-0.40140.344207
14-0.032639-0.54030.294725
15-0.056862-0.94120.173709
160.0230350.38130.351637
17-0.033882-0.56080.287681
180.0771341.27680.101378
190.1189941.96970.02494
200.0280380.46410.321467
21-0.025268-0.41830.338043
220.0910971.50790.066363
230.1096491.8150.035307
240.0753161.24670.106786
250.0185880.30770.379275
26-0.008603-0.14240.443434
270.0137690.22790.409943
28-0.00751-0.12430.450581
29-0.001299-0.02150.491428
30-0.01052-0.17410.430941
31-0.114876-1.90150.02914
32-0.050491-0.83580.202004
330.0035060.0580.476883
34-0.105627-1.74840.040753
35-0.121227-2.00670.022883
36-0.122377-2.02570.021882

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.113656 & 1.8813 & 0.030492 \tabularnewline
2 & 0.124473 & 2.0604 & 0.020153 \tabularnewline
3 & 0.130085 & 2.1533 & 0.016084 \tabularnewline
4 & 0.109424 & 1.8113 & 0.035595 \tabularnewline
5 & 0.128451 & 2.1262 & 0.017188 \tabularnewline
6 & -0.026533 & -0.4392 & 0.330432 \tabularnewline
7 & -0.092619 & -1.5331 & 0.0632 \tabularnewline
8 & -0.087125 & -1.4422 & 0.075199 \tabularnewline
9 & -0.035246 & -0.5834 & 0.280044 \tabularnewline
10 & -0.068726 & -1.1376 & 0.128138 \tabularnewline
11 & -0.072231 & -1.1956 & 0.116436 \tabularnewline
12 & -0.475379 & -7.8689 & 0 \tabularnewline
13 & -0.024252 & -0.4014 & 0.344207 \tabularnewline
14 & -0.032639 & -0.5403 & 0.294725 \tabularnewline
15 & -0.056862 & -0.9412 & 0.173709 \tabularnewline
16 & 0.023035 & 0.3813 & 0.351637 \tabularnewline
17 & -0.033882 & -0.5608 & 0.287681 \tabularnewline
18 & 0.077134 & 1.2768 & 0.101378 \tabularnewline
19 & 0.118994 & 1.9697 & 0.02494 \tabularnewline
20 & 0.028038 & 0.4641 & 0.321467 \tabularnewline
21 & -0.025268 & -0.4183 & 0.338043 \tabularnewline
22 & 0.091097 & 1.5079 & 0.066363 \tabularnewline
23 & 0.109649 & 1.815 & 0.035307 \tabularnewline
24 & 0.075316 & 1.2467 & 0.106786 \tabularnewline
25 & 0.018588 & 0.3077 & 0.379275 \tabularnewline
26 & -0.008603 & -0.1424 & 0.443434 \tabularnewline
27 & 0.013769 & 0.2279 & 0.409943 \tabularnewline
28 & -0.00751 & -0.1243 & 0.450581 \tabularnewline
29 & -0.001299 & -0.0215 & 0.491428 \tabularnewline
30 & -0.01052 & -0.1741 & 0.430941 \tabularnewline
31 & -0.114876 & -1.9015 & 0.02914 \tabularnewline
32 & -0.050491 & -0.8358 & 0.202004 \tabularnewline
33 & 0.003506 & 0.058 & 0.476883 \tabularnewline
34 & -0.105627 & -1.7484 & 0.040753 \tabularnewline
35 & -0.121227 & -2.0067 & 0.022883 \tabularnewline
36 & -0.122377 & -2.0257 & 0.021882 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270333&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]0.113656[/C][C]1.8813[/C][C]0.030492[/C][/ROW]
[ROW][C]2[/C][C]0.124473[/C][C]2.0604[/C][C]0.020153[/C][/ROW]
[ROW][C]3[/C][C]0.130085[/C][C]2.1533[/C][C]0.016084[/C][/ROW]
[ROW][C]4[/C][C]0.109424[/C][C]1.8113[/C][C]0.035595[/C][/ROW]
[ROW][C]5[/C][C]0.128451[/C][C]2.1262[/C][C]0.017188[/C][/ROW]
[ROW][C]6[/C][C]-0.026533[/C][C]-0.4392[/C][C]0.330432[/C][/ROW]
[ROW][C]7[/C][C]-0.092619[/C][C]-1.5331[/C][C]0.0632[/C][/ROW]
[ROW][C]8[/C][C]-0.087125[/C][C]-1.4422[/C][C]0.075199[/C][/ROW]
[ROW][C]9[/C][C]-0.035246[/C][C]-0.5834[/C][C]0.280044[/C][/ROW]
[ROW][C]10[/C][C]-0.068726[/C][C]-1.1376[/C][C]0.128138[/C][/ROW]
[ROW][C]11[/C][C]-0.072231[/C][C]-1.1956[/C][C]0.116436[/C][/ROW]
[ROW][C]12[/C][C]-0.475379[/C][C]-7.8689[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.024252[/C][C]-0.4014[/C][C]0.344207[/C][/ROW]
[ROW][C]14[/C][C]-0.032639[/C][C]-0.5403[/C][C]0.294725[/C][/ROW]
[ROW][C]15[/C][C]-0.056862[/C][C]-0.9412[/C][C]0.173709[/C][/ROW]
[ROW][C]16[/C][C]0.023035[/C][C]0.3813[/C][C]0.351637[/C][/ROW]
[ROW][C]17[/C][C]-0.033882[/C][C]-0.5608[/C][C]0.287681[/C][/ROW]
[ROW][C]18[/C][C]0.077134[/C][C]1.2768[/C][C]0.101378[/C][/ROW]
[ROW][C]19[/C][C]0.118994[/C][C]1.9697[/C][C]0.02494[/C][/ROW]
[ROW][C]20[/C][C]0.028038[/C][C]0.4641[/C][C]0.321467[/C][/ROW]
[ROW][C]21[/C][C]-0.025268[/C][C]-0.4183[/C][C]0.338043[/C][/ROW]
[ROW][C]22[/C][C]0.091097[/C][C]1.5079[/C][C]0.066363[/C][/ROW]
[ROW][C]23[/C][C]0.109649[/C][C]1.815[/C][C]0.035307[/C][/ROW]
[ROW][C]24[/C][C]0.075316[/C][C]1.2467[/C][C]0.106786[/C][/ROW]
[ROW][C]25[/C][C]0.018588[/C][C]0.3077[/C][C]0.379275[/C][/ROW]
[ROW][C]26[/C][C]-0.008603[/C][C]-0.1424[/C][C]0.443434[/C][/ROW]
[ROW][C]27[/C][C]0.013769[/C][C]0.2279[/C][C]0.409943[/C][/ROW]
[ROW][C]28[/C][C]-0.00751[/C][C]-0.1243[/C][C]0.450581[/C][/ROW]
[ROW][C]29[/C][C]-0.001299[/C][C]-0.0215[/C][C]0.491428[/C][/ROW]
[ROW][C]30[/C][C]-0.01052[/C][C]-0.1741[/C][C]0.430941[/C][/ROW]
[ROW][C]31[/C][C]-0.114876[/C][C]-1.9015[/C][C]0.02914[/C][/ROW]
[ROW][C]32[/C][C]-0.050491[/C][C]-0.8358[/C][C]0.202004[/C][/ROW]
[ROW][C]33[/C][C]0.003506[/C][C]0.058[/C][C]0.476883[/C][/ROW]
[ROW][C]34[/C][C]-0.105627[/C][C]-1.7484[/C][C]0.040753[/C][/ROW]
[ROW][C]35[/C][C]-0.121227[/C][C]-2.0067[/C][C]0.022883[/C][/ROW]
[ROW][C]36[/C][C]-0.122377[/C][C]-2.0257[/C][C]0.021882[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270333&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270333&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
10.1136561.88130.030492
20.1244732.06040.020153
30.1300852.15330.016084
40.1094241.81130.035595
50.1284512.12620.017188
6-0.026533-0.43920.330432
7-0.092619-1.53310.0632
8-0.087125-1.44220.075199
9-0.035246-0.58340.280044
10-0.068726-1.13760.128138
11-0.072231-1.19560.116436
12-0.475379-7.86890
13-0.024252-0.40140.344207
14-0.032639-0.54030.294725
15-0.056862-0.94120.173709
160.0230350.38130.351637
17-0.033882-0.56080.287681
180.0771341.27680.101378
190.1189941.96970.02494
200.0280380.46410.321467
21-0.025268-0.41830.338043
220.0910971.50790.066363
230.1096491.8150.035307
240.0753161.24670.106786
250.0185880.30770.379275
26-0.008603-0.14240.443434
270.0137690.22790.409943
28-0.00751-0.12430.450581
29-0.001299-0.02150.491428
30-0.01052-0.17410.430941
31-0.114876-1.90150.02914
32-0.050491-0.83580.202004
330.0035060.0580.476883
34-0.105627-1.74840.040753
35-0.121227-2.00670.022883
36-0.122377-2.02570.021882






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1136561.88130.030492
20.1130151.87070.031224
30.1074341.77830.038228
40.0757451.25380.105491
50.0900161.490.068684
6-0.080107-1.3260.092972
7-0.133155-2.20410.014174
8-0.099161-1.64140.050931
9-0.009781-0.16190.435748
10-0.026258-0.43460.332079
11-0.006257-0.10360.458793
12-0.448748-7.42810
130.0842131.3940.082228
140.0652571.08020.140501
150.0547170.90570.182938
160.1143761.89330.029689
170.0457460.75720.224782
180.0037610.06230.475202
190.029060.4810.315439
20-0.088241-1.46070.072629
21-0.078655-1.3020.097008
220.0769751.27420.101841
230.105571.74750.040836
24-0.209235-3.46340.000309
250.0621191.02830.152368
26-0.000124-0.0020.499185
27-0.017263-0.28580.387642
280.0713381.18090.119341
290.0342880.56760.285395
300.0554260.91750.179854
31-0.057979-0.95970.169019
32-0.137987-2.28410.011566
33-0.053151-0.87980.189868
34-0.016826-0.27850.390414
35-0.015814-0.26180.396849
36-0.19594-3.24340.000664

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.113656 & 1.8813 & 0.030492 \tabularnewline
2 & 0.113015 & 1.8707 & 0.031224 \tabularnewline
3 & 0.107434 & 1.7783 & 0.038228 \tabularnewline
4 & 0.075745 & 1.2538 & 0.105491 \tabularnewline
5 & 0.090016 & 1.49 & 0.068684 \tabularnewline
6 & -0.080107 & -1.326 & 0.092972 \tabularnewline
7 & -0.133155 & -2.2041 & 0.014174 \tabularnewline
8 & -0.099161 & -1.6414 & 0.050931 \tabularnewline
9 & -0.009781 & -0.1619 & 0.435748 \tabularnewline
10 & -0.026258 & -0.4346 & 0.332079 \tabularnewline
11 & -0.006257 & -0.1036 & 0.458793 \tabularnewline
12 & -0.448748 & -7.4281 & 0 \tabularnewline
13 & 0.084213 & 1.394 & 0.082228 \tabularnewline
14 & 0.065257 & 1.0802 & 0.140501 \tabularnewline
15 & 0.054717 & 0.9057 & 0.182938 \tabularnewline
16 & 0.114376 & 1.8933 & 0.029689 \tabularnewline
17 & 0.045746 & 0.7572 & 0.224782 \tabularnewline
18 & 0.003761 & 0.0623 & 0.475202 \tabularnewline
19 & 0.02906 & 0.481 & 0.315439 \tabularnewline
20 & -0.088241 & -1.4607 & 0.072629 \tabularnewline
21 & -0.078655 & -1.302 & 0.097008 \tabularnewline
22 & 0.076975 & 1.2742 & 0.101841 \tabularnewline
23 & 0.10557 & 1.7475 & 0.040836 \tabularnewline
24 & -0.209235 & -3.4634 & 0.000309 \tabularnewline
25 & 0.062119 & 1.0283 & 0.152368 \tabularnewline
26 & -0.000124 & -0.002 & 0.499185 \tabularnewline
27 & -0.017263 & -0.2858 & 0.387642 \tabularnewline
28 & 0.071338 & 1.1809 & 0.119341 \tabularnewline
29 & 0.034288 & 0.5676 & 0.285395 \tabularnewline
30 & 0.055426 & 0.9175 & 0.179854 \tabularnewline
31 & -0.057979 & -0.9597 & 0.169019 \tabularnewline
32 & -0.137987 & -2.2841 & 0.011566 \tabularnewline
33 & -0.053151 & -0.8798 & 0.189868 \tabularnewline
34 & -0.016826 & -0.2785 & 0.390414 \tabularnewline
35 & -0.015814 & -0.2618 & 0.396849 \tabularnewline
36 & -0.19594 & -3.2434 & 0.000664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270333&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]0.113656[/C][C]1.8813[/C][C]0.030492[/C][/ROW]
[ROW][C]2[/C][C]0.113015[/C][C]1.8707[/C][C]0.031224[/C][/ROW]
[ROW][C]3[/C][C]0.107434[/C][C]1.7783[/C][C]0.038228[/C][/ROW]
[ROW][C]4[/C][C]0.075745[/C][C]1.2538[/C][C]0.105491[/C][/ROW]
[ROW][C]5[/C][C]0.090016[/C][C]1.49[/C][C]0.068684[/C][/ROW]
[ROW][C]6[/C][C]-0.080107[/C][C]-1.326[/C][C]0.092972[/C][/ROW]
[ROW][C]7[/C][C]-0.133155[/C][C]-2.2041[/C][C]0.014174[/C][/ROW]
[ROW][C]8[/C][C]-0.099161[/C][C]-1.6414[/C][C]0.050931[/C][/ROW]
[ROW][C]9[/C][C]-0.009781[/C][C]-0.1619[/C][C]0.435748[/C][/ROW]
[ROW][C]10[/C][C]-0.026258[/C][C]-0.4346[/C][C]0.332079[/C][/ROW]
[ROW][C]11[/C][C]-0.006257[/C][C]-0.1036[/C][C]0.458793[/C][/ROW]
[ROW][C]12[/C][C]-0.448748[/C][C]-7.4281[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.084213[/C][C]1.394[/C][C]0.082228[/C][/ROW]
[ROW][C]14[/C][C]0.065257[/C][C]1.0802[/C][C]0.140501[/C][/ROW]
[ROW][C]15[/C][C]0.054717[/C][C]0.9057[/C][C]0.182938[/C][/ROW]
[ROW][C]16[/C][C]0.114376[/C][C]1.8933[/C][C]0.029689[/C][/ROW]
[ROW][C]17[/C][C]0.045746[/C][C]0.7572[/C][C]0.224782[/C][/ROW]
[ROW][C]18[/C][C]0.003761[/C][C]0.0623[/C][C]0.475202[/C][/ROW]
[ROW][C]19[/C][C]0.02906[/C][C]0.481[/C][C]0.315439[/C][/ROW]
[ROW][C]20[/C][C]-0.088241[/C][C]-1.4607[/C][C]0.072629[/C][/ROW]
[ROW][C]21[/C][C]-0.078655[/C][C]-1.302[/C][C]0.097008[/C][/ROW]
[ROW][C]22[/C][C]0.076975[/C][C]1.2742[/C][C]0.101841[/C][/ROW]
[ROW][C]23[/C][C]0.10557[/C][C]1.7475[/C][C]0.040836[/C][/ROW]
[ROW][C]24[/C][C]-0.209235[/C][C]-3.4634[/C][C]0.000309[/C][/ROW]
[ROW][C]25[/C][C]0.062119[/C][C]1.0283[/C][C]0.152368[/C][/ROW]
[ROW][C]26[/C][C]-0.000124[/C][C]-0.002[/C][C]0.499185[/C][/ROW]
[ROW][C]27[/C][C]-0.017263[/C][C]-0.2858[/C][C]0.387642[/C][/ROW]
[ROW][C]28[/C][C]0.071338[/C][C]1.1809[/C][C]0.119341[/C][/ROW]
[ROW][C]29[/C][C]0.034288[/C][C]0.5676[/C][C]0.285395[/C][/ROW]
[ROW][C]30[/C][C]0.055426[/C][C]0.9175[/C][C]0.179854[/C][/ROW]
[ROW][C]31[/C][C]-0.057979[/C][C]-0.9597[/C][C]0.169019[/C][/ROW]
[ROW][C]32[/C][C]-0.137987[/C][C]-2.2841[/C][C]0.011566[/C][/ROW]
[ROW][C]33[/C][C]-0.053151[/C][C]-0.8798[/C][C]0.189868[/C][/ROW]
[ROW][C]34[/C][C]-0.016826[/C][C]-0.2785[/C][C]0.390414[/C][/ROW]
[ROW][C]35[/C][C]-0.015814[/C][C]-0.2618[/C][C]0.396849[/C][/ROW]
[ROW][C]36[/C][C]-0.19594[/C][C]-3.2434[/C][C]0.000664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270333&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270333&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
10.1136561.88130.030492
20.1130151.87070.031224
30.1074341.77830.038228
40.0757451.25380.105491
50.0900161.490.068684
6-0.080107-1.3260.092972
7-0.133155-2.20410.014174
8-0.099161-1.64140.050931
9-0.009781-0.16190.435748
10-0.026258-0.43460.332079
11-0.006257-0.10360.458793
12-0.448748-7.42810
130.0842131.3940.082228
140.0652571.08020.140501
150.0547170.90570.182938
160.1143761.89330.029689
170.0457460.75720.224782
180.0037610.06230.475202
190.029060.4810.315439
20-0.088241-1.46070.072629
21-0.078655-1.3020.097008
220.0769751.27420.101841
230.105571.74750.040836
24-0.209235-3.46340.000309
250.0621191.02830.152368
26-0.000124-0.0020.499185
27-0.017263-0.28580.387642
280.0713381.18090.119341
290.0342880.56760.285395
300.0554260.91750.179854
31-0.057979-0.95970.169019
32-0.137987-2.28410.011566
33-0.053151-0.87980.189868
34-0.016826-0.27850.390414
35-0.015814-0.26180.396849
36-0.19594-3.24340.000664


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')