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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 18 Mar 2013 17:20:18 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Mar/18/t1363641629cclnpbtyivzxt7j.htm/, Retrieved Sat, 27 Apr 2024 12:15:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=207869, Retrieved Sat, 27 Apr 2024 12:15:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145

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] [gemiddelde consum...] [2013-03-18 21:20:18] [a5e81fc5b84eaf53b9dc73271fe36a59] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,26
1,26
1,28
1,34
1,39
1,47
1,57
1,63
1,72
1,43
1,35
1,41
1,44
1,43
1,43
1,42
1,45
1,51
1,48
1,48
1,45
1,38
1,46
1,45
1,41
1,45
1,47
1,47
1,53
1,56
1,66
1,79
1,78
1,46
1,41
1,43
1,43
1,45
1,35
1,35
1,29
1,29
1,26
1,3
1,3
1,16
1,24
1,15
1,21
1,22
1,17
1,13
1,15
1,2
1,23
1,25
1,38
1,28
1,26
1,25
1,26
1,28
1,31
1,22
1,23
1,36
1,54
1,58
1,44
1,29
1,28
1,23

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=207869&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=207869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207869&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
10.8288687.03320
20.6186385.24931e-06
30.4626443.92579.8e-05
40.3915973.32280.000701
50.379083.21660.000972
60.3505572.97460.001995
70.3010932.55490.006369
80.2640442.24050.014073
90.2693662.28560.01261
100.2512542.1320.018211
110.2238421.89940.030761
120.1961191.66410.050217
130.1053310.89380.187213
140.0338650.28730.387335
15-0.046792-0.3970.346255
16-0.086078-0.73040.233759
17-0.08647-0.73370.23275
18-0.087306-0.74080.230608
19-0.117283-0.99520.161492
20-0.147661-1.25290.107139
21-0.155362-1.31830.095792
22-0.125572-1.06550.145101
23-0.045556-0.38660.350111
240.015360.13030.448334
25-0.058788-0.49880.30971
26-0.134013-1.13710.129625
27-0.211739-1.79670.038291
28-0.248681-2.11010.019161
29-0.246525-2.09180.019991
30-0.254445-2.1590.01709
31-0.269907-2.29020.01247
32-0.292183-2.47930.007754
33-0.260907-2.21390.015003
34-0.20406-1.73150.043822
35-0.129006-1.09470.138658
36-0.100376-0.85170.198596
37-0.142437-1.20860.115382
38-0.174739-1.48270.071258
39-0.216344-1.83570.035263
40-0.201158-1.70690.046076
41-0.179978-1.52720.06555
42-0.164314-1.39430.083764
43-0.159508-1.35350.090069
44-0.144823-1.22890.111563
45-0.128285-1.08850.139995
46-0.117647-0.99830.160745
47-0.07411-0.62880.265721
48-0.019405-0.16470.434837

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.828868 & 7.0332 & 0 \tabularnewline
2 & 0.618638 & 5.2493 & 1e-06 \tabularnewline
3 & 0.462644 & 3.9257 & 9.8e-05 \tabularnewline
4 & 0.391597 & 3.3228 & 0.000701 \tabularnewline
5 & 0.37908 & 3.2166 & 0.000972 \tabularnewline
6 & 0.350557 & 2.9746 & 0.001995 \tabularnewline
7 & 0.301093 & 2.5549 & 0.006369 \tabularnewline
8 & 0.264044 & 2.2405 & 0.014073 \tabularnewline
9 & 0.269366 & 2.2856 & 0.01261 \tabularnewline
10 & 0.251254 & 2.132 & 0.018211 \tabularnewline
11 & 0.223842 & 1.8994 & 0.030761 \tabularnewline
12 & 0.196119 & 1.6641 & 0.050217 \tabularnewline
13 & 0.105331 & 0.8938 & 0.187213 \tabularnewline
14 & 0.033865 & 0.2873 & 0.387335 \tabularnewline
15 & -0.046792 & -0.397 & 0.346255 \tabularnewline
16 & -0.086078 & -0.7304 & 0.233759 \tabularnewline
17 & -0.08647 & -0.7337 & 0.23275 \tabularnewline
18 & -0.087306 & -0.7408 & 0.230608 \tabularnewline
19 & -0.117283 & -0.9952 & 0.161492 \tabularnewline
20 & -0.147661 & -1.2529 & 0.107139 \tabularnewline
21 & -0.155362 & -1.3183 & 0.095792 \tabularnewline
22 & -0.125572 & -1.0655 & 0.145101 \tabularnewline
23 & -0.045556 & -0.3866 & 0.350111 \tabularnewline
24 & 0.01536 & 0.1303 & 0.448334 \tabularnewline
25 & -0.058788 & -0.4988 & 0.30971 \tabularnewline
26 & -0.134013 & -1.1371 & 0.129625 \tabularnewline
27 & -0.211739 & -1.7967 & 0.038291 \tabularnewline
28 & -0.248681 & -2.1101 & 0.019161 \tabularnewline
29 & -0.246525 & -2.0918 & 0.019991 \tabularnewline
30 & -0.254445 & -2.159 & 0.01709 \tabularnewline
31 & -0.269907 & -2.2902 & 0.01247 \tabularnewline
32 & -0.292183 & -2.4793 & 0.007754 \tabularnewline
33 & -0.260907 & -2.2139 & 0.015003 \tabularnewline
34 & -0.20406 & -1.7315 & 0.043822 \tabularnewline
35 & -0.129006 & -1.0947 & 0.138658 \tabularnewline
36 & -0.100376 & -0.8517 & 0.198596 \tabularnewline
37 & -0.142437 & -1.2086 & 0.115382 \tabularnewline
38 & -0.174739 & -1.4827 & 0.071258 \tabularnewline
39 & -0.216344 & -1.8357 & 0.035263 \tabularnewline
40 & -0.201158 & -1.7069 & 0.046076 \tabularnewline
41 & -0.179978 & -1.5272 & 0.06555 \tabularnewline
42 & -0.164314 & -1.3943 & 0.083764 \tabularnewline
43 & -0.159508 & -1.3535 & 0.090069 \tabularnewline
44 & -0.144823 & -1.2289 & 0.111563 \tabularnewline
45 & -0.128285 & -1.0885 & 0.139995 \tabularnewline
46 & -0.117647 & -0.9983 & 0.160745 \tabularnewline
47 & -0.07411 & -0.6288 & 0.265721 \tabularnewline
48 & -0.019405 & -0.1647 & 0.434837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207869&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]0.828868[/C][C]7.0332[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.618638[/C][C]5.2493[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.462644[/C][C]3.9257[/C][C]9.8e-05[/C][/ROW]
[ROW][C]4[/C][C]0.391597[/C][C]3.3228[/C][C]0.000701[/C][/ROW]
[ROW][C]5[/C][C]0.37908[/C][C]3.2166[/C][C]0.000972[/C][/ROW]
[ROW][C]6[/C][C]0.350557[/C][C]2.9746[/C][C]0.001995[/C][/ROW]
[ROW][C]7[/C][C]0.301093[/C][C]2.5549[/C][C]0.006369[/C][/ROW]
[ROW][C]8[/C][C]0.264044[/C][C]2.2405[/C][C]0.014073[/C][/ROW]
[ROW][C]9[/C][C]0.269366[/C][C]2.2856[/C][C]0.01261[/C][/ROW]
[ROW][C]10[/C][C]0.251254[/C][C]2.132[/C][C]0.018211[/C][/ROW]
[ROW][C]11[/C][C]0.223842[/C][C]1.8994[/C][C]0.030761[/C][/ROW]
[ROW][C]12[/C][C]0.196119[/C][C]1.6641[/C][C]0.050217[/C][/ROW]
[ROW][C]13[/C][C]0.105331[/C][C]0.8938[/C][C]0.187213[/C][/ROW]
[ROW][C]14[/C][C]0.033865[/C][C]0.2873[/C][C]0.387335[/C][/ROW]
[ROW][C]15[/C][C]-0.046792[/C][C]-0.397[/C][C]0.346255[/C][/ROW]
[ROW][C]16[/C][C]-0.086078[/C][C]-0.7304[/C][C]0.233759[/C][/ROW]
[ROW][C]17[/C][C]-0.08647[/C][C]-0.7337[/C][C]0.23275[/C][/ROW]
[ROW][C]18[/C][C]-0.087306[/C][C]-0.7408[/C][C]0.230608[/C][/ROW]
[ROW][C]19[/C][C]-0.117283[/C][C]-0.9952[/C][C]0.161492[/C][/ROW]
[ROW][C]20[/C][C]-0.147661[/C][C]-1.2529[/C][C]0.107139[/C][/ROW]
[ROW][C]21[/C][C]-0.155362[/C][C]-1.3183[/C][C]0.095792[/C][/ROW]
[ROW][C]22[/C][C]-0.125572[/C][C]-1.0655[/C][C]0.145101[/C][/ROW]
[ROW][C]23[/C][C]-0.045556[/C][C]-0.3866[/C][C]0.350111[/C][/ROW]
[ROW][C]24[/C][C]0.01536[/C][C]0.1303[/C][C]0.448334[/C][/ROW]
[ROW][C]25[/C][C]-0.058788[/C][C]-0.4988[/C][C]0.30971[/C][/ROW]
[ROW][C]26[/C][C]-0.134013[/C][C]-1.1371[/C][C]0.129625[/C][/ROW]
[ROW][C]27[/C][C]-0.211739[/C][C]-1.7967[/C][C]0.038291[/C][/ROW]
[ROW][C]28[/C][C]-0.248681[/C][C]-2.1101[/C][C]0.019161[/C][/ROW]
[ROW][C]29[/C][C]-0.246525[/C][C]-2.0918[/C][C]0.019991[/C][/ROW]
[ROW][C]30[/C][C]-0.254445[/C][C]-2.159[/C][C]0.01709[/C][/ROW]
[ROW][C]31[/C][C]-0.269907[/C][C]-2.2902[/C][C]0.01247[/C][/ROW]
[ROW][C]32[/C][C]-0.292183[/C][C]-2.4793[/C][C]0.007754[/C][/ROW]
[ROW][C]33[/C][C]-0.260907[/C][C]-2.2139[/C][C]0.015003[/C][/ROW]
[ROW][C]34[/C][C]-0.20406[/C][C]-1.7315[/C][C]0.043822[/C][/ROW]
[ROW][C]35[/C][C]-0.129006[/C][C]-1.0947[/C][C]0.138658[/C][/ROW]
[ROW][C]36[/C][C]-0.100376[/C][C]-0.8517[/C][C]0.198596[/C][/ROW]
[ROW][C]37[/C][C]-0.142437[/C][C]-1.2086[/C][C]0.115382[/C][/ROW]
[ROW][C]38[/C][C]-0.174739[/C][C]-1.4827[/C][C]0.071258[/C][/ROW]
[ROW][C]39[/C][C]-0.216344[/C][C]-1.8357[/C][C]0.035263[/C][/ROW]
[ROW][C]40[/C][C]-0.201158[/C][C]-1.7069[/C][C]0.046076[/C][/ROW]
[ROW][C]41[/C][C]-0.179978[/C][C]-1.5272[/C][C]0.06555[/C][/ROW]
[ROW][C]42[/C][C]-0.164314[/C][C]-1.3943[/C][C]0.083764[/C][/ROW]
[ROW][C]43[/C][C]-0.159508[/C][C]-1.3535[/C][C]0.090069[/C][/ROW]
[ROW][C]44[/C][C]-0.144823[/C][C]-1.2289[/C][C]0.111563[/C][/ROW]
[ROW][C]45[/C][C]-0.128285[/C][C]-1.0885[/C][C]0.139995[/C][/ROW]
[ROW][C]46[/C][C]-0.117647[/C][C]-0.9983[/C][C]0.160745[/C][/ROW]
[ROW][C]47[/C][C]-0.07411[/C][C]-0.6288[/C][C]0.265721[/C][/ROW]
[ROW][C]48[/C][C]-0.019405[/C][C]-0.1647[/C][C]0.434837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207869&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
10.8288687.03320
20.6186385.24931e-06
30.4626443.92579.8e-05
40.3915973.32280.000701
50.379083.21660.000972
60.3505572.97460.001995
70.3010932.55490.006369
80.2640442.24050.014073
90.2693662.28560.01261
100.2512542.1320.018211
110.2238421.89940.030761
120.1961191.66410.050217
130.1053310.89380.187213
140.0338650.28730.387335
15-0.046792-0.3970.346255
16-0.086078-0.73040.233759
17-0.08647-0.73370.23275
18-0.087306-0.74080.230608
19-0.117283-0.99520.161492
20-0.147661-1.25290.107139
21-0.155362-1.31830.095792
22-0.125572-1.06550.145101
23-0.045556-0.38660.350111
240.015360.13030.448334
25-0.058788-0.49880.30971
26-0.134013-1.13710.129625
27-0.211739-1.79670.038291
28-0.248681-2.11010.019161
29-0.246525-2.09180.019991
30-0.254445-2.1590.01709
31-0.269907-2.29020.01247
32-0.292183-2.47930.007754
33-0.260907-2.21390.015003
34-0.20406-1.73150.043822
35-0.129006-1.09470.138658
36-0.100376-0.85170.198596
37-0.142437-1.20860.115382
38-0.174739-1.48270.071258
39-0.216344-1.83570.035263
40-0.201158-1.70690.046076
41-0.179978-1.52720.06555
42-0.164314-1.39430.083764
43-0.159508-1.35350.090069
44-0.144823-1.22890.111563
45-0.128285-1.08850.139995
46-0.117647-0.99830.160745
47-0.07411-0.62880.265721
48-0.019405-0.16470.434837






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8288687.03320
2-0.218494-1.8540.033919
30.0635490.53920.295694
40.1351521.14680.127629
50.0990870.84080.201626
6-0.057173-0.48510.314528
7-0.003839-0.03260.487052
80.0670570.5690.285565
90.1102240.93530.176385
10-0.114411-0.97080.167448
110.026240.22270.412217
120.033180.28150.38955
13-0.243992-2.07030.021004
140.0237190.20130.420529
15-0.143954-1.22150.112942
160.0507520.43060.334007
17-0.004177-0.03540.485912
18-0.05753-0.48820.31346
19-0.070045-0.59430.277071
200.0272280.2310.408972
21-0.017987-0.15260.439562
220.1271161.07860.142179
230.1449031.22950.111435
240.0299490.25410.400061
25-0.324362-2.75230.003742
260.094950.80570.21154
27-0.119441-1.01350.15711
28-0.084626-0.71810.237516
29-0.037009-0.3140.377204
30-0.050341-0.42720.33527
31-0.019587-0.16620.434231
32-0.159715-1.35520.089792
330.1344411.14080.128873
340.0991850.84160.201396
350.0361110.30640.380087
36-0.093948-0.79720.213986
370.0473090.40140.344647
380.0171430.14550.442375
39-0.050033-0.42450.336218
400.0026460.02240.491076
41-0.02288-0.19410.423304
42-0.013254-0.11250.455386
43-0.077709-0.65940.255875
440.0216270.18350.427456
45-0.058554-0.49680.310405
46-0.07666-0.65050.258725
47-0.040217-0.34130.366954
480.1820321.54460.063414

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.828868 & 7.0332 & 0 \tabularnewline
2 & -0.218494 & -1.854 & 0.033919 \tabularnewline
3 & 0.063549 & 0.5392 & 0.295694 \tabularnewline
4 & 0.135152 & 1.1468 & 0.127629 \tabularnewline
5 & 0.099087 & 0.8408 & 0.201626 \tabularnewline
6 & -0.057173 & -0.4851 & 0.314528 \tabularnewline
7 & -0.003839 & -0.0326 & 0.487052 \tabularnewline
8 & 0.067057 & 0.569 & 0.285565 \tabularnewline
9 & 0.110224 & 0.9353 & 0.176385 \tabularnewline
10 & -0.114411 & -0.9708 & 0.167448 \tabularnewline
11 & 0.02624 & 0.2227 & 0.412217 \tabularnewline
12 & 0.03318 & 0.2815 & 0.38955 \tabularnewline
13 & -0.243992 & -2.0703 & 0.021004 \tabularnewline
14 & 0.023719 & 0.2013 & 0.420529 \tabularnewline
15 & -0.143954 & -1.2215 & 0.112942 \tabularnewline
16 & 0.050752 & 0.4306 & 0.334007 \tabularnewline
17 & -0.004177 & -0.0354 & 0.485912 \tabularnewline
18 & -0.05753 & -0.4882 & 0.31346 \tabularnewline
19 & -0.070045 & -0.5943 & 0.277071 \tabularnewline
20 & 0.027228 & 0.231 & 0.408972 \tabularnewline
21 & -0.017987 & -0.1526 & 0.439562 \tabularnewline
22 & 0.127116 & 1.0786 & 0.142179 \tabularnewline
23 & 0.144903 & 1.2295 & 0.111435 \tabularnewline
24 & 0.029949 & 0.2541 & 0.400061 \tabularnewline
25 & -0.324362 & -2.7523 & 0.003742 \tabularnewline
26 & 0.09495 & 0.8057 & 0.21154 \tabularnewline
27 & -0.119441 & -1.0135 & 0.15711 \tabularnewline
28 & -0.084626 & -0.7181 & 0.237516 \tabularnewline
29 & -0.037009 & -0.314 & 0.377204 \tabularnewline
30 & -0.050341 & -0.4272 & 0.33527 \tabularnewline
31 & -0.019587 & -0.1662 & 0.434231 \tabularnewline
32 & -0.159715 & -1.3552 & 0.089792 \tabularnewline
33 & 0.134441 & 1.1408 & 0.128873 \tabularnewline
34 & 0.099185 & 0.8416 & 0.201396 \tabularnewline
35 & 0.036111 & 0.3064 & 0.380087 \tabularnewline
36 & -0.093948 & -0.7972 & 0.213986 \tabularnewline
37 & 0.047309 & 0.4014 & 0.344647 \tabularnewline
38 & 0.017143 & 0.1455 & 0.442375 \tabularnewline
39 & -0.050033 & -0.4245 & 0.336218 \tabularnewline
40 & 0.002646 & 0.0224 & 0.491076 \tabularnewline
41 & -0.02288 & -0.1941 & 0.423304 \tabularnewline
42 & -0.013254 & -0.1125 & 0.455386 \tabularnewline
43 & -0.077709 & -0.6594 & 0.255875 \tabularnewline
44 & 0.021627 & 0.1835 & 0.427456 \tabularnewline
45 & -0.058554 & -0.4968 & 0.310405 \tabularnewline
46 & -0.07666 & -0.6505 & 0.258725 \tabularnewline
47 & -0.040217 & -0.3413 & 0.366954 \tabularnewline
48 & 0.182032 & 1.5446 & 0.063414 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207869&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]0.828868[/C][C]7.0332[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.218494[/C][C]-1.854[/C][C]0.033919[/C][/ROW]
[ROW][C]3[/C][C]0.063549[/C][C]0.5392[/C][C]0.295694[/C][/ROW]
[ROW][C]4[/C][C]0.135152[/C][C]1.1468[/C][C]0.127629[/C][/ROW]
[ROW][C]5[/C][C]0.099087[/C][C]0.8408[/C][C]0.201626[/C][/ROW]
[ROW][C]6[/C][C]-0.057173[/C][C]-0.4851[/C][C]0.314528[/C][/ROW]
[ROW][C]7[/C][C]-0.003839[/C][C]-0.0326[/C][C]0.487052[/C][/ROW]
[ROW][C]8[/C][C]0.067057[/C][C]0.569[/C][C]0.285565[/C][/ROW]
[ROW][C]9[/C][C]0.110224[/C][C]0.9353[/C][C]0.176385[/C][/ROW]
[ROW][C]10[/C][C]-0.114411[/C][C]-0.9708[/C][C]0.167448[/C][/ROW]
[ROW][C]11[/C][C]0.02624[/C][C]0.2227[/C][C]0.412217[/C][/ROW]
[ROW][C]12[/C][C]0.03318[/C][C]0.2815[/C][C]0.38955[/C][/ROW]
[ROW][C]13[/C][C]-0.243992[/C][C]-2.0703[/C][C]0.021004[/C][/ROW]
[ROW][C]14[/C][C]0.023719[/C][C]0.2013[/C][C]0.420529[/C][/ROW]
[ROW][C]15[/C][C]-0.143954[/C][C]-1.2215[/C][C]0.112942[/C][/ROW]
[ROW][C]16[/C][C]0.050752[/C][C]0.4306[/C][C]0.334007[/C][/ROW]
[ROW][C]17[/C][C]-0.004177[/C][C]-0.0354[/C][C]0.485912[/C][/ROW]
[ROW][C]18[/C][C]-0.05753[/C][C]-0.4882[/C][C]0.31346[/C][/ROW]
[ROW][C]19[/C][C]-0.070045[/C][C]-0.5943[/C][C]0.277071[/C][/ROW]
[ROW][C]20[/C][C]0.027228[/C][C]0.231[/C][C]0.408972[/C][/ROW]
[ROW][C]21[/C][C]-0.017987[/C][C]-0.1526[/C][C]0.439562[/C][/ROW]
[ROW][C]22[/C][C]0.127116[/C][C]1.0786[/C][C]0.142179[/C][/ROW]
[ROW][C]23[/C][C]0.144903[/C][C]1.2295[/C][C]0.111435[/C][/ROW]
[ROW][C]24[/C][C]0.029949[/C][C]0.2541[/C][C]0.400061[/C][/ROW]
[ROW][C]25[/C][C]-0.324362[/C][C]-2.7523[/C][C]0.003742[/C][/ROW]
[ROW][C]26[/C][C]0.09495[/C][C]0.8057[/C][C]0.21154[/C][/ROW]
[ROW][C]27[/C][C]-0.119441[/C][C]-1.0135[/C][C]0.15711[/C][/ROW]
[ROW][C]28[/C][C]-0.084626[/C][C]-0.7181[/C][C]0.237516[/C][/ROW]
[ROW][C]29[/C][C]-0.037009[/C][C]-0.314[/C][C]0.377204[/C][/ROW]
[ROW][C]30[/C][C]-0.050341[/C][C]-0.4272[/C][C]0.33527[/C][/ROW]
[ROW][C]31[/C][C]-0.019587[/C][C]-0.1662[/C][C]0.434231[/C][/ROW]
[ROW][C]32[/C][C]-0.159715[/C][C]-1.3552[/C][C]0.089792[/C][/ROW]
[ROW][C]33[/C][C]0.134441[/C][C]1.1408[/C][C]0.128873[/C][/ROW]
[ROW][C]34[/C][C]0.099185[/C][C]0.8416[/C][C]0.201396[/C][/ROW]
[ROW][C]35[/C][C]0.036111[/C][C]0.3064[/C][C]0.380087[/C][/ROW]
[ROW][C]36[/C][C]-0.093948[/C][C]-0.7972[/C][C]0.213986[/C][/ROW]
[ROW][C]37[/C][C]0.047309[/C][C]0.4014[/C][C]0.344647[/C][/ROW]
[ROW][C]38[/C][C]0.017143[/C][C]0.1455[/C][C]0.442375[/C][/ROW]
[ROW][C]39[/C][C]-0.050033[/C][C]-0.4245[/C][C]0.336218[/C][/ROW]
[ROW][C]40[/C][C]0.002646[/C][C]0.0224[/C][C]0.491076[/C][/ROW]
[ROW][C]41[/C][C]-0.02288[/C][C]-0.1941[/C][C]0.423304[/C][/ROW]
[ROW][C]42[/C][C]-0.013254[/C][C]-0.1125[/C][C]0.455386[/C][/ROW]
[ROW][C]43[/C][C]-0.077709[/C][C]-0.6594[/C][C]0.255875[/C][/ROW]
[ROW][C]44[/C][C]0.021627[/C][C]0.1835[/C][C]0.427456[/C][/ROW]
[ROW][C]45[/C][C]-0.058554[/C][C]-0.4968[/C][C]0.310405[/C][/ROW]
[ROW][C]46[/C][C]-0.07666[/C][C]-0.6505[/C][C]0.258725[/C][/ROW]
[ROW][C]47[/C][C]-0.040217[/C][C]-0.3413[/C][C]0.366954[/C][/ROW]
[ROW][C]48[/C][C]0.182032[/C][C]1.5446[/C][C]0.063414[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207869&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207869&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
10.8288687.03320
2-0.218494-1.8540.033919
30.0635490.53920.295694
40.1351521.14680.127629
50.0990870.84080.201626
6-0.057173-0.48510.314528
7-0.003839-0.03260.487052
80.0670570.5690.285565
90.1102240.93530.176385
10-0.114411-0.97080.167448
110.026240.22270.412217
120.033180.28150.38955
13-0.243992-2.07030.021004
140.0237190.20130.420529
15-0.143954-1.22150.112942
160.0507520.43060.334007
17-0.004177-0.03540.485912
18-0.05753-0.48820.31346
19-0.070045-0.59430.277071
200.0272280.2310.408972
21-0.017987-0.15260.439562
220.1271161.07860.142179
230.1449031.22950.111435
240.0299490.25410.400061
25-0.324362-2.75230.003742
260.094950.80570.21154
27-0.119441-1.01350.15711
28-0.084626-0.71810.237516
29-0.037009-0.3140.377204
30-0.050341-0.42720.33527
31-0.019587-0.16620.434231
32-0.159715-1.35520.089792
330.1344411.14080.128873
340.0991850.84160.201396
350.0361110.30640.380087
36-0.093948-0.79720.213986
370.0473090.40140.344647
380.0171430.14550.442375
39-0.050033-0.42450.336218
400.0026460.02240.491076
41-0.02288-0.19410.423304
42-0.013254-0.11250.455386
43-0.077709-0.65940.255875
440.0216270.18350.427456
45-0.058554-0.49680.310405
46-0.07666-0.65050.258725
47-0.040217-0.34130.366954
480.1820321.54460.063414


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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')