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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, 11 Dec 2014 15:33:31 +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/11/t1418312035lqkhcjxnp6c3db3.htm/, Retrieved Thu, 16 May 2024 08:54:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266124, Retrieved Thu, 16 May 2024 08:54:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact62

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [ezGGG] [2014-12-11 15:33:31] [7de4f24d5c21ad7c83693f758b02221d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9
12.2
12.8
7.4
6.7
12.6
14.8
13.3
11.1
8.2
11.4
6.4
10.6
12.0
6.3
11.3
11.9
9.3
9.6
10.0
6.4
13.8
10.8
13.8
11.7
10.9
16.1
13.4
9.9
11.5
8.3
11.7
9.0
9.7
10.8
10.3
10.4
12.7
9.3
11.8
5.9
11.4
13.0
10.8
12.3
11.3
11.8
7.9
12.7
12.3
11.6
6.7
10.9
12.1
13.3
10.1
5.7
14.3
8.0
13.3
9.3
12.5
7.6
15.9
9.2
9.1
11.1
13.0
14.5
12.2
12.3
11.4
8.8
14.6
12.6
13.0
12.6
13.2
9.9
7.7
10.5
13.4
10.9
4.3
10.3
11.8
11.2
11.4
8.6
13.2
12.6
5.6
9.9
8.8
7.7
9.0
7.3
11.4
13.6
7.9
10.7
10.3
8.3
9.6
14.2
8.5
13.5
4.9
6.4
9.6
11.6
11.1
4.35
12.7
18.1
17.85
16.6
12.6
17.1
19.1
16.1
13.35
18.4
14.7
10.6
12.6
16.2
13.6
18.9
14.1
14.5
16.15
14.75
14.8
12.45
12.65
17.35
8.6
18.4
16.1
11.6
17.75
15.25
17.65
16.35
17.65
13.6
14.35
14.75
18.25
9.9
16
18.25
16.85
14.6
13.85
18.95
15.6
14.85
11.75
18.45
15.9
17.1
16.1
19.9
10.95
18.45
15.1
15
11.35
15.95
18.1
14.6
15.4
15.4
17.6
13.35
19.1
15.35
7.6
13.4
13.9
19.1
15.25
12.9
16.1
17.35
13.15
12.15
12.6
10.35
15.4
9.6
18.2
13.6
14.85
14.75
14.1
14.9
16.25
19.25
13.6
13.6
15.65
12.75
14.6
9.85
12.65
19.2
16.6
11.2
15.25
11.9
13.2
16.35
12.4
15.85
18.15
11.15
15.65
17.75
7.65
12.35
15.6
19.3
15.2
17.1
15.6
18.4
19.05
18.55
19.1
13.1
12.85
9.5
4.5
11.85
13.6
11.7
12.4
13.35
11.4
14.9
19.9
11.2
14.6
17.6
14.05
16.1
13.35
11.85
11.95
14.75
15.15
13.2
16.85
7.85
7.7
12.6
7.85
10.95
12.35
9.95
14.9
16.65
13.4
13.95
15.7
16.85
10.95
15.35
12.2
15.1
17.75
15.2
14.6
16.65
8.1

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266124&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266124&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266124&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'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.475601-7.91560
2-0.043705-0.72740.233798
30.058360.97130.166121
4-0.029541-0.49170.311675
50.0322840.53730.295744
60.0136320.22690.410341
7-0.096844-1.61180.054072
80.041180.68540.246841
90.0409180.6810.248218
10-0.072795-1.21160.113358
110.06661.10840.134315
12-0.048136-0.80110.211866
130.0469320.78110.217705
14-0.061694-1.02680.152707
150.0312010.51930.301988
160.0133880.22280.411918
17-0.015635-0.26020.397445
180.0247750.41230.340204
19-0.031341-0.52160.301179
20-0.01807-0.30080.381914
210.0076470.12730.449411
220.0522060.86890.192833
23-0.023261-0.38710.349476
24-0.023867-0.39720.345753
250.043490.72380.234896
26-0.006773-0.11270.455168
27-0.019916-0.33150.370269
28-0.050995-0.84870.198382
290.0977461.62680.052457
30-0.013016-0.21660.414326
31-0.034866-0.58030.281097
32-0.013191-0.21950.413195
330.0327770.54550.292917
340.0094940.1580.437278
35-0.028322-0.47140.318876
36-0.026762-0.44540.328188
37-0.013344-0.22210.412201
380.1024891.70580.044587
39-0.058347-0.97110.166175
40-0.044347-0.73810.230546
41-0.00502-0.08360.466735
420.0500520.8330.202773
43-0.020917-0.34810.364001
440.0401510.66820.252266
45-0.027884-0.46410.321476
46-0.033643-0.55990.287991
470.1140611.89840.029344
48-0.038682-0.64380.260122
49-0.032996-0.54920.291669
50-0.017114-0.28480.387991
51-0.009287-0.15460.438638
520.054950.91460.18061
53-0.020278-0.33750.367998
54-0.044924-0.74770.227642
550.0081080.13490.446379
560.0949581.58040.057577
57-0.045293-0.75380.225795
58-0.038511-0.6410.261042
59-0.00535-0.0890.464554
600.0493290.8210.206176

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.475601 & -7.9156 & 0 \tabularnewline
2 & -0.043705 & -0.7274 & 0.233798 \tabularnewline
3 & 0.05836 & 0.9713 & 0.166121 \tabularnewline
4 & -0.029541 & -0.4917 & 0.311675 \tabularnewline
5 & 0.032284 & 0.5373 & 0.295744 \tabularnewline
6 & 0.013632 & 0.2269 & 0.410341 \tabularnewline
7 & -0.096844 & -1.6118 & 0.054072 \tabularnewline
8 & 0.04118 & 0.6854 & 0.246841 \tabularnewline
9 & 0.040918 & 0.681 & 0.248218 \tabularnewline
10 & -0.072795 & -1.2116 & 0.113358 \tabularnewline
11 & 0.0666 & 1.1084 & 0.134315 \tabularnewline
12 & -0.048136 & -0.8011 & 0.211866 \tabularnewline
13 & 0.046932 & 0.7811 & 0.217705 \tabularnewline
14 & -0.061694 & -1.0268 & 0.152707 \tabularnewline
15 & 0.031201 & 0.5193 & 0.301988 \tabularnewline
16 & 0.013388 & 0.2228 & 0.411918 \tabularnewline
17 & -0.015635 & -0.2602 & 0.397445 \tabularnewline
18 & 0.024775 & 0.4123 & 0.340204 \tabularnewline
19 & -0.031341 & -0.5216 & 0.301179 \tabularnewline
20 & -0.01807 & -0.3008 & 0.381914 \tabularnewline
21 & 0.007647 & 0.1273 & 0.449411 \tabularnewline
22 & 0.052206 & 0.8689 & 0.192833 \tabularnewline
23 & -0.023261 & -0.3871 & 0.349476 \tabularnewline
24 & -0.023867 & -0.3972 & 0.345753 \tabularnewline
25 & 0.04349 & 0.7238 & 0.234896 \tabularnewline
26 & -0.006773 & -0.1127 & 0.455168 \tabularnewline
27 & -0.019916 & -0.3315 & 0.370269 \tabularnewline
28 & -0.050995 & -0.8487 & 0.198382 \tabularnewline
29 & 0.097746 & 1.6268 & 0.052457 \tabularnewline
30 & -0.013016 & -0.2166 & 0.414326 \tabularnewline
31 & -0.034866 & -0.5803 & 0.281097 \tabularnewline
32 & -0.013191 & -0.2195 & 0.413195 \tabularnewline
33 & 0.032777 & 0.5455 & 0.292917 \tabularnewline
34 & 0.009494 & 0.158 & 0.437278 \tabularnewline
35 & -0.028322 & -0.4714 & 0.318876 \tabularnewline
36 & -0.026762 & -0.4454 & 0.328188 \tabularnewline
37 & -0.013344 & -0.2221 & 0.412201 \tabularnewline
38 & 0.102489 & 1.7058 & 0.044587 \tabularnewline
39 & -0.058347 & -0.9711 & 0.166175 \tabularnewline
40 & -0.044347 & -0.7381 & 0.230546 \tabularnewline
41 & -0.00502 & -0.0836 & 0.466735 \tabularnewline
42 & 0.050052 & 0.833 & 0.202773 \tabularnewline
43 & -0.020917 & -0.3481 & 0.364001 \tabularnewline
44 & 0.040151 & 0.6682 & 0.252266 \tabularnewline
45 & -0.027884 & -0.4641 & 0.321476 \tabularnewline
46 & -0.033643 & -0.5599 & 0.287991 \tabularnewline
47 & 0.114061 & 1.8984 & 0.029344 \tabularnewline
48 & -0.038682 & -0.6438 & 0.260122 \tabularnewline
49 & -0.032996 & -0.5492 & 0.291669 \tabularnewline
50 & -0.017114 & -0.2848 & 0.387991 \tabularnewline
51 & -0.009287 & -0.1546 & 0.438638 \tabularnewline
52 & 0.05495 & 0.9146 & 0.18061 \tabularnewline
53 & -0.020278 & -0.3375 & 0.367998 \tabularnewline
54 & -0.044924 & -0.7477 & 0.227642 \tabularnewline
55 & 0.008108 & 0.1349 & 0.446379 \tabularnewline
56 & 0.094958 & 1.5804 & 0.057577 \tabularnewline
57 & -0.045293 & -0.7538 & 0.225795 \tabularnewline
58 & -0.038511 & -0.641 & 0.261042 \tabularnewline
59 & -0.00535 & -0.089 & 0.464554 \tabularnewline
60 & 0.049329 & 0.821 & 0.206176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266124&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]-0.475601[/C][C]-7.9156[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.043705[/C][C]-0.7274[/C][C]0.233798[/C][/ROW]
[ROW][C]3[/C][C]0.05836[/C][C]0.9713[/C][C]0.166121[/C][/ROW]
[ROW][C]4[/C][C]-0.029541[/C][C]-0.4917[/C][C]0.311675[/C][/ROW]
[ROW][C]5[/C][C]0.032284[/C][C]0.5373[/C][C]0.295744[/C][/ROW]
[ROW][C]6[/C][C]0.013632[/C][C]0.2269[/C][C]0.410341[/C][/ROW]
[ROW][C]7[/C][C]-0.096844[/C][C]-1.6118[/C][C]0.054072[/C][/ROW]
[ROW][C]8[/C][C]0.04118[/C][C]0.6854[/C][C]0.246841[/C][/ROW]
[ROW][C]9[/C][C]0.040918[/C][C]0.681[/C][C]0.248218[/C][/ROW]
[ROW][C]10[/C][C]-0.072795[/C][C]-1.2116[/C][C]0.113358[/C][/ROW]
[ROW][C]11[/C][C]0.0666[/C][C]1.1084[/C][C]0.134315[/C][/ROW]
[ROW][C]12[/C][C]-0.048136[/C][C]-0.8011[/C][C]0.211866[/C][/ROW]
[ROW][C]13[/C][C]0.046932[/C][C]0.7811[/C][C]0.217705[/C][/ROW]
[ROW][C]14[/C][C]-0.061694[/C][C]-1.0268[/C][C]0.152707[/C][/ROW]
[ROW][C]15[/C][C]0.031201[/C][C]0.5193[/C][C]0.301988[/C][/ROW]
[ROW][C]16[/C][C]0.013388[/C][C]0.2228[/C][C]0.411918[/C][/ROW]
[ROW][C]17[/C][C]-0.015635[/C][C]-0.2602[/C][C]0.397445[/C][/ROW]
[ROW][C]18[/C][C]0.024775[/C][C]0.4123[/C][C]0.340204[/C][/ROW]
[ROW][C]19[/C][C]-0.031341[/C][C]-0.5216[/C][C]0.301179[/C][/ROW]
[ROW][C]20[/C][C]-0.01807[/C][C]-0.3008[/C][C]0.381914[/C][/ROW]
[ROW][C]21[/C][C]0.007647[/C][C]0.1273[/C][C]0.449411[/C][/ROW]
[ROW][C]22[/C][C]0.052206[/C][C]0.8689[/C][C]0.192833[/C][/ROW]
[ROW][C]23[/C][C]-0.023261[/C][C]-0.3871[/C][C]0.349476[/C][/ROW]
[ROW][C]24[/C][C]-0.023867[/C][C]-0.3972[/C][C]0.345753[/C][/ROW]
[ROW][C]25[/C][C]0.04349[/C][C]0.7238[/C][C]0.234896[/C][/ROW]
[ROW][C]26[/C][C]-0.006773[/C][C]-0.1127[/C][C]0.455168[/C][/ROW]
[ROW][C]27[/C][C]-0.019916[/C][C]-0.3315[/C][C]0.370269[/C][/ROW]
[ROW][C]28[/C][C]-0.050995[/C][C]-0.8487[/C][C]0.198382[/C][/ROW]
[ROW][C]29[/C][C]0.097746[/C][C]1.6268[/C][C]0.052457[/C][/ROW]
[ROW][C]30[/C][C]-0.013016[/C][C]-0.2166[/C][C]0.414326[/C][/ROW]
[ROW][C]31[/C][C]-0.034866[/C][C]-0.5803[/C][C]0.281097[/C][/ROW]
[ROW][C]32[/C][C]-0.013191[/C][C]-0.2195[/C][C]0.413195[/C][/ROW]
[ROW][C]33[/C][C]0.032777[/C][C]0.5455[/C][C]0.292917[/C][/ROW]
[ROW][C]34[/C][C]0.009494[/C][C]0.158[/C][C]0.437278[/C][/ROW]
[ROW][C]35[/C][C]-0.028322[/C][C]-0.4714[/C][C]0.318876[/C][/ROW]
[ROW][C]36[/C][C]-0.026762[/C][C]-0.4454[/C][C]0.328188[/C][/ROW]
[ROW][C]37[/C][C]-0.013344[/C][C]-0.2221[/C][C]0.412201[/C][/ROW]
[ROW][C]38[/C][C]0.102489[/C][C]1.7058[/C][C]0.044587[/C][/ROW]
[ROW][C]39[/C][C]-0.058347[/C][C]-0.9711[/C][C]0.166175[/C][/ROW]
[ROW][C]40[/C][C]-0.044347[/C][C]-0.7381[/C][C]0.230546[/C][/ROW]
[ROW][C]41[/C][C]-0.00502[/C][C]-0.0836[/C][C]0.466735[/C][/ROW]
[ROW][C]42[/C][C]0.050052[/C][C]0.833[/C][C]0.202773[/C][/ROW]
[ROW][C]43[/C][C]-0.020917[/C][C]-0.3481[/C][C]0.364001[/C][/ROW]
[ROW][C]44[/C][C]0.040151[/C][C]0.6682[/C][C]0.252266[/C][/ROW]
[ROW][C]45[/C][C]-0.027884[/C][C]-0.4641[/C][C]0.321476[/C][/ROW]
[ROW][C]46[/C][C]-0.033643[/C][C]-0.5599[/C][C]0.287991[/C][/ROW]
[ROW][C]47[/C][C]0.114061[/C][C]1.8984[/C][C]0.029344[/C][/ROW]
[ROW][C]48[/C][C]-0.038682[/C][C]-0.6438[/C][C]0.260122[/C][/ROW]
[ROW][C]49[/C][C]-0.032996[/C][C]-0.5492[/C][C]0.291669[/C][/ROW]
[ROW][C]50[/C][C]-0.017114[/C][C]-0.2848[/C][C]0.387991[/C][/ROW]
[ROW][C]51[/C][C]-0.009287[/C][C]-0.1546[/C][C]0.438638[/C][/ROW]
[ROW][C]52[/C][C]0.05495[/C][C]0.9146[/C][C]0.18061[/C][/ROW]
[ROW][C]53[/C][C]-0.020278[/C][C]-0.3375[/C][C]0.367998[/C][/ROW]
[ROW][C]54[/C][C]-0.044924[/C][C]-0.7477[/C][C]0.227642[/C][/ROW]
[ROW][C]55[/C][C]0.008108[/C][C]0.1349[/C][C]0.446379[/C][/ROW]
[ROW][C]56[/C][C]0.094958[/C][C]1.5804[/C][C]0.057577[/C][/ROW]
[ROW][C]57[/C][C]-0.045293[/C][C]-0.7538[/C][C]0.225795[/C][/ROW]
[ROW][C]58[/C][C]-0.038511[/C][C]-0.641[/C][C]0.261042[/C][/ROW]
[ROW][C]59[/C][C]-0.00535[/C][C]-0.089[/C][C]0.464554[/C][/ROW]
[ROW][C]60[/C][C]0.049329[/C][C]0.821[/C][C]0.206176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266124&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266124&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
1-0.475601-7.91560
2-0.043705-0.72740.233798
30.058360.97130.166121
4-0.029541-0.49170.311675
50.0322840.53730.295744
60.0136320.22690.410341
7-0.096844-1.61180.054072
80.041180.68540.246841
90.0409180.6810.248218
10-0.072795-1.21160.113358
110.06661.10840.134315
12-0.048136-0.80110.211866
130.0469320.78110.217705
14-0.061694-1.02680.152707
150.0312010.51930.301988
160.0133880.22280.411918
17-0.015635-0.26020.397445
180.0247750.41230.340204
19-0.031341-0.52160.301179
20-0.01807-0.30080.381914
210.0076470.12730.449411
220.0522060.86890.192833
23-0.023261-0.38710.349476
24-0.023867-0.39720.345753
250.043490.72380.234896
26-0.006773-0.11270.455168
27-0.019916-0.33150.370269
28-0.050995-0.84870.198382
290.0977461.62680.052457
30-0.013016-0.21660.414326
31-0.034866-0.58030.281097
32-0.013191-0.21950.413195
330.0327770.54550.292917
340.0094940.1580.437278
35-0.028322-0.47140.318876
36-0.026762-0.44540.328188
37-0.013344-0.22210.412201
380.1024891.70580.044587
39-0.058347-0.97110.166175
40-0.044347-0.73810.230546
41-0.00502-0.08360.466735
420.0500520.8330.202773
43-0.020917-0.34810.364001
440.0401510.66820.252266
45-0.027884-0.46410.321476
46-0.033643-0.55990.287991
470.1140611.89840.029344
48-0.038682-0.64380.260122
49-0.032996-0.54920.291669
50-0.017114-0.28480.387991
51-0.009287-0.15460.438638
520.054950.91460.18061
53-0.020278-0.33750.367998
54-0.044924-0.74770.227642
550.0081080.13490.446379
560.0949581.58040.057577
57-0.045293-0.75380.225795
58-0.038511-0.6410.261042
59-0.00535-0.0890.464554
600.0493290.8210.206176






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.475601-7.91560
2-0.348799-5.80520
3-0.19946-3.31970.000511
4-0.158963-2.64570.004309
5-0.07337-1.22110.111539
6-0.004162-0.06930.472415
7-0.11245-1.87150.031162
8-0.109547-1.82320.034674
9-0.044768-0.74510.228426
10-0.104834-1.74480.041065
11-0.030867-0.51370.303928
12-0.064043-1.06590.143703
130.0061290.1020.459412
14-0.083233-1.38530.083543
15-0.060758-1.01120.156397
16-0.031376-0.52220.300976
17-0.038726-0.64450.259881
180.008790.14630.441898
19-0.020424-0.33990.367089
20-0.065572-1.09130.138038
21-0.095727-1.59320.056127
22-0.018612-0.30980.378487
230.0150070.24980.401475
24-0.023184-0.38590.34995
250.0409090.68090.248263
260.0429030.71410.237897
270.0095880.15960.436663
28-0.098395-1.63760.051318
290.0211240.35160.362712
300.0716071.19180.117183
310.0412990.68740.246218
320.011070.18420.426977
330.0281830.46910.319698
340.0377240.62790.265308
350.0026940.04480.482134
36-0.025351-0.42190.336705
37-0.072072-1.19950.115678
380.0400460.66650.252824
390.0420610.70.242247
40-0.042704-0.71070.238921
41-0.111769-1.86020.031958
42-0.071945-1.19740.116086
43-0.063601-1.05850.145369
440.0090820.15120.439981
450.024260.40380.34335
46-0.041256-0.68660.246444
470.061921.03060.151825
480.0930851.54920.061232
490.0722611.20270.115065
500.0116130.19330.423439
51-0.056125-0.93410.17553
520.0198750.33080.370528
530.0270560.45030.32642
54-0.024909-0.41460.339391
55-0.083763-1.39410.082204
560.064931.08070.140395
570.1243442.06950.019713
580.0556210.92570.1777
59-0.024034-0.40.344727
60-0.005375-0.08950.464393

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.475601 & -7.9156 & 0 \tabularnewline
2 & -0.348799 & -5.8052 & 0 \tabularnewline
3 & -0.19946 & -3.3197 & 0.000511 \tabularnewline
4 & -0.158963 & -2.6457 & 0.004309 \tabularnewline
5 & -0.07337 & -1.2211 & 0.111539 \tabularnewline
6 & -0.004162 & -0.0693 & 0.472415 \tabularnewline
7 & -0.11245 & -1.8715 & 0.031162 \tabularnewline
8 & -0.109547 & -1.8232 & 0.034674 \tabularnewline
9 & -0.044768 & -0.7451 & 0.228426 \tabularnewline
10 & -0.104834 & -1.7448 & 0.041065 \tabularnewline
11 & -0.030867 & -0.5137 & 0.303928 \tabularnewline
12 & -0.064043 & -1.0659 & 0.143703 \tabularnewline
13 & 0.006129 & 0.102 & 0.459412 \tabularnewline
14 & -0.083233 & -1.3853 & 0.083543 \tabularnewline
15 & -0.060758 & -1.0112 & 0.156397 \tabularnewline
16 & -0.031376 & -0.5222 & 0.300976 \tabularnewline
17 & -0.038726 & -0.6445 & 0.259881 \tabularnewline
18 & 0.00879 & 0.1463 & 0.441898 \tabularnewline
19 & -0.020424 & -0.3399 & 0.367089 \tabularnewline
20 & -0.065572 & -1.0913 & 0.138038 \tabularnewline
21 & -0.095727 & -1.5932 & 0.056127 \tabularnewline
22 & -0.018612 & -0.3098 & 0.378487 \tabularnewline
23 & 0.015007 & 0.2498 & 0.401475 \tabularnewline
24 & -0.023184 & -0.3859 & 0.34995 \tabularnewline
25 & 0.040909 & 0.6809 & 0.248263 \tabularnewline
26 & 0.042903 & 0.7141 & 0.237897 \tabularnewline
27 & 0.009588 & 0.1596 & 0.436663 \tabularnewline
28 & -0.098395 & -1.6376 & 0.051318 \tabularnewline
29 & 0.021124 & 0.3516 & 0.362712 \tabularnewline
30 & 0.071607 & 1.1918 & 0.117183 \tabularnewline
31 & 0.041299 & 0.6874 & 0.246218 \tabularnewline
32 & 0.01107 & 0.1842 & 0.426977 \tabularnewline
33 & 0.028183 & 0.4691 & 0.319698 \tabularnewline
34 & 0.037724 & 0.6279 & 0.265308 \tabularnewline
35 & 0.002694 & 0.0448 & 0.482134 \tabularnewline
36 & -0.025351 & -0.4219 & 0.336705 \tabularnewline
37 & -0.072072 & -1.1995 & 0.115678 \tabularnewline
38 & 0.040046 & 0.6665 & 0.252824 \tabularnewline
39 & 0.042061 & 0.7 & 0.242247 \tabularnewline
40 & -0.042704 & -0.7107 & 0.238921 \tabularnewline
41 & -0.111769 & -1.8602 & 0.031958 \tabularnewline
42 & -0.071945 & -1.1974 & 0.116086 \tabularnewline
43 & -0.063601 & -1.0585 & 0.145369 \tabularnewline
44 & 0.009082 & 0.1512 & 0.439981 \tabularnewline
45 & 0.02426 & 0.4038 & 0.34335 \tabularnewline
46 & -0.041256 & -0.6866 & 0.246444 \tabularnewline
47 & 0.06192 & 1.0306 & 0.151825 \tabularnewline
48 & 0.093085 & 1.5492 & 0.061232 \tabularnewline
49 & 0.072261 & 1.2027 & 0.115065 \tabularnewline
50 & 0.011613 & 0.1933 & 0.423439 \tabularnewline
51 & -0.056125 & -0.9341 & 0.17553 \tabularnewline
52 & 0.019875 & 0.3308 & 0.370528 \tabularnewline
53 & 0.027056 & 0.4503 & 0.32642 \tabularnewline
54 & -0.024909 & -0.4146 & 0.339391 \tabularnewline
55 & -0.083763 & -1.3941 & 0.082204 \tabularnewline
56 & 0.06493 & 1.0807 & 0.140395 \tabularnewline
57 & 0.124344 & 2.0695 & 0.019713 \tabularnewline
58 & 0.055621 & 0.9257 & 0.1777 \tabularnewline
59 & -0.024034 & -0.4 & 0.344727 \tabularnewline
60 & -0.005375 & -0.0895 & 0.464393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266124&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]-0.475601[/C][C]-7.9156[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.348799[/C][C]-5.8052[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]-0.19946[/C][C]-3.3197[/C][C]0.000511[/C][/ROW]
[ROW][C]4[/C][C]-0.158963[/C][C]-2.6457[/C][C]0.004309[/C][/ROW]
[ROW][C]5[/C][C]-0.07337[/C][C]-1.2211[/C][C]0.111539[/C][/ROW]
[ROW][C]6[/C][C]-0.004162[/C][C]-0.0693[/C][C]0.472415[/C][/ROW]
[ROW][C]7[/C][C]-0.11245[/C][C]-1.8715[/C][C]0.031162[/C][/ROW]
[ROW][C]8[/C][C]-0.109547[/C][C]-1.8232[/C][C]0.034674[/C][/ROW]
[ROW][C]9[/C][C]-0.044768[/C][C]-0.7451[/C][C]0.228426[/C][/ROW]
[ROW][C]10[/C][C]-0.104834[/C][C]-1.7448[/C][C]0.041065[/C][/ROW]
[ROW][C]11[/C][C]-0.030867[/C][C]-0.5137[/C][C]0.303928[/C][/ROW]
[ROW][C]12[/C][C]-0.064043[/C][C]-1.0659[/C][C]0.143703[/C][/ROW]
[ROW][C]13[/C][C]0.006129[/C][C]0.102[/C][C]0.459412[/C][/ROW]
[ROW][C]14[/C][C]-0.083233[/C][C]-1.3853[/C][C]0.083543[/C][/ROW]
[ROW][C]15[/C][C]-0.060758[/C][C]-1.0112[/C][C]0.156397[/C][/ROW]
[ROW][C]16[/C][C]-0.031376[/C][C]-0.5222[/C][C]0.300976[/C][/ROW]
[ROW][C]17[/C][C]-0.038726[/C][C]-0.6445[/C][C]0.259881[/C][/ROW]
[ROW][C]18[/C][C]0.00879[/C][C]0.1463[/C][C]0.441898[/C][/ROW]
[ROW][C]19[/C][C]-0.020424[/C][C]-0.3399[/C][C]0.367089[/C][/ROW]
[ROW][C]20[/C][C]-0.065572[/C][C]-1.0913[/C][C]0.138038[/C][/ROW]
[ROW][C]21[/C][C]-0.095727[/C][C]-1.5932[/C][C]0.056127[/C][/ROW]
[ROW][C]22[/C][C]-0.018612[/C][C]-0.3098[/C][C]0.378487[/C][/ROW]
[ROW][C]23[/C][C]0.015007[/C][C]0.2498[/C][C]0.401475[/C][/ROW]
[ROW][C]24[/C][C]-0.023184[/C][C]-0.3859[/C][C]0.34995[/C][/ROW]
[ROW][C]25[/C][C]0.040909[/C][C]0.6809[/C][C]0.248263[/C][/ROW]
[ROW][C]26[/C][C]0.042903[/C][C]0.7141[/C][C]0.237897[/C][/ROW]
[ROW][C]27[/C][C]0.009588[/C][C]0.1596[/C][C]0.436663[/C][/ROW]
[ROW][C]28[/C][C]-0.098395[/C][C]-1.6376[/C][C]0.051318[/C][/ROW]
[ROW][C]29[/C][C]0.021124[/C][C]0.3516[/C][C]0.362712[/C][/ROW]
[ROW][C]30[/C][C]0.071607[/C][C]1.1918[/C][C]0.117183[/C][/ROW]
[ROW][C]31[/C][C]0.041299[/C][C]0.6874[/C][C]0.246218[/C][/ROW]
[ROW][C]32[/C][C]0.01107[/C][C]0.1842[/C][C]0.426977[/C][/ROW]
[ROW][C]33[/C][C]0.028183[/C][C]0.4691[/C][C]0.319698[/C][/ROW]
[ROW][C]34[/C][C]0.037724[/C][C]0.6279[/C][C]0.265308[/C][/ROW]
[ROW][C]35[/C][C]0.002694[/C][C]0.0448[/C][C]0.482134[/C][/ROW]
[ROW][C]36[/C][C]-0.025351[/C][C]-0.4219[/C][C]0.336705[/C][/ROW]
[ROW][C]37[/C][C]-0.072072[/C][C]-1.1995[/C][C]0.115678[/C][/ROW]
[ROW][C]38[/C][C]0.040046[/C][C]0.6665[/C][C]0.252824[/C][/ROW]
[ROW][C]39[/C][C]0.042061[/C][C]0.7[/C][C]0.242247[/C][/ROW]
[ROW][C]40[/C][C]-0.042704[/C][C]-0.7107[/C][C]0.238921[/C][/ROW]
[ROW][C]41[/C][C]-0.111769[/C][C]-1.8602[/C][C]0.031958[/C][/ROW]
[ROW][C]42[/C][C]-0.071945[/C][C]-1.1974[/C][C]0.116086[/C][/ROW]
[ROW][C]43[/C][C]-0.063601[/C][C]-1.0585[/C][C]0.145369[/C][/ROW]
[ROW][C]44[/C][C]0.009082[/C][C]0.1512[/C][C]0.439981[/C][/ROW]
[ROW][C]45[/C][C]0.02426[/C][C]0.4038[/C][C]0.34335[/C][/ROW]
[ROW][C]46[/C][C]-0.041256[/C][C]-0.6866[/C][C]0.246444[/C][/ROW]
[ROW][C]47[/C][C]0.06192[/C][C]1.0306[/C][C]0.151825[/C][/ROW]
[ROW][C]48[/C][C]0.093085[/C][C]1.5492[/C][C]0.061232[/C][/ROW]
[ROW][C]49[/C][C]0.072261[/C][C]1.2027[/C][C]0.115065[/C][/ROW]
[ROW][C]50[/C][C]0.011613[/C][C]0.1933[/C][C]0.423439[/C][/ROW]
[ROW][C]51[/C][C]-0.056125[/C][C]-0.9341[/C][C]0.17553[/C][/ROW]
[ROW][C]52[/C][C]0.019875[/C][C]0.3308[/C][C]0.370528[/C][/ROW]
[ROW][C]53[/C][C]0.027056[/C][C]0.4503[/C][C]0.32642[/C][/ROW]
[ROW][C]54[/C][C]-0.024909[/C][C]-0.4146[/C][C]0.339391[/C][/ROW]
[ROW][C]55[/C][C]-0.083763[/C][C]-1.3941[/C][C]0.082204[/C][/ROW]
[ROW][C]56[/C][C]0.06493[/C][C]1.0807[/C][C]0.140395[/C][/ROW]
[ROW][C]57[/C][C]0.124344[/C][C]2.0695[/C][C]0.019713[/C][/ROW]
[ROW][C]58[/C][C]0.055621[/C][C]0.9257[/C][C]0.1777[/C][/ROW]
[ROW][C]59[/C][C]-0.024034[/C][C]-0.4[/C][C]0.344727[/C][/ROW]
[ROW][C]60[/C][C]-0.005375[/C][C]-0.0895[/C][C]0.464393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266124&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266124&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
1-0.475601-7.91560
2-0.348799-5.80520
3-0.19946-3.31970.000511
4-0.158963-2.64570.004309
5-0.07337-1.22110.111539
6-0.004162-0.06930.472415
7-0.11245-1.87150.031162
8-0.109547-1.82320.034674
9-0.044768-0.74510.228426
10-0.104834-1.74480.041065
11-0.030867-0.51370.303928
12-0.064043-1.06590.143703
130.0061290.1020.459412
14-0.083233-1.38530.083543
15-0.060758-1.01120.156397
16-0.031376-0.52220.300976
17-0.038726-0.64450.259881
180.008790.14630.441898
19-0.020424-0.33990.367089
20-0.065572-1.09130.138038
21-0.095727-1.59320.056127
22-0.018612-0.30980.378487
230.0150070.24980.401475
24-0.023184-0.38590.34995
250.0409090.68090.248263
260.0429030.71410.237897
270.0095880.15960.436663
28-0.098395-1.63760.051318
290.0211240.35160.362712
300.0716071.19180.117183
310.0412990.68740.246218
320.011070.18420.426977
330.0281830.46910.319698
340.0377240.62790.265308
350.0026940.04480.482134
36-0.025351-0.42190.336705
37-0.072072-1.19950.115678
380.0400460.66650.252824
390.0420610.70.242247
40-0.042704-0.71070.238921
41-0.111769-1.86020.031958
42-0.071945-1.19740.116086
43-0.063601-1.05850.145369
440.0090820.15120.439981
450.024260.40380.34335
46-0.041256-0.68660.246444
470.061921.03060.151825
480.0930851.54920.061232
490.0722611.20270.115065
500.0116130.19330.423439
51-0.056125-0.93410.17553
520.0198750.33080.370528
530.0270560.45030.32642
54-0.024909-0.41460.339391
55-0.083763-1.39410.082204
560.064931.08070.140395
570.1243442.06950.019713
580.0556210.92570.1777
59-0.024034-0.40.344727
60-0.005375-0.08950.464393


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')