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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, 25 May 2015 21:55:02 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/May/25/t1432587321xzsss7uw5lyse8m.htm/, Retrieved Tue, 07 May 2024 10:31:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279358, Retrieved Tue, 07 May 2024 10:31:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

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] [seizoensinvloed] [2015-05-25 20:55:02] [b43493158838656c32486372ca9c54cf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,8
100,66
101,44
102,17
102,75
104,28
104,96
105,16
105,29
105,15
105,23
104,45
104,6
105,1
105,94
106,2
106,89
107,57
107,42
107,2
107,08
107,17
107,23
106,61
106,97
108,23
109,8
111,93
113,51
115,27
115,58
115,55
115,44
114,93
115,09
113,78
114,51
114,85
116,12
115,47
115,93
116,6
116,98
117,37
117,48
117,18
117,03
114,95
115,64
116,02
116,07
114,5
114,36
116
116,16
116,42
116,78
115,74
115,44
113,52
113,37
114,35
114,11
113,47
114,33
115,76
116,2
116,48
116,53
116,45
116,23
114,46
115,08
115,57
116,17
115,21
114,97
114,24
114,16
117,2
117,71
117,14
116,67
114,71
115,92
117,74
118,38
118,59
119,66
121,2
121,4
122,66
122,95
122,9
123,29
122,02

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'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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279358&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279358&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279358&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'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.945689.26570
20.8791048.61340
30.8150017.98530
40.7538157.38590
50.6966796.8260
60.6489426.35830
70.6072425.94970
80.5718315.60280
90.5412895.30350
100.5121225.01771e-06
110.4848244.75034e-06
120.4566474.47421.1e-05
130.4189984.10534.2e-05
140.3750083.67430.000196
150.3326683.25950.000772
160.2883422.82520.002874
170.2495692.44530.008149
180.2249692.20420.014949
190.2031771.99070.024677
200.1785761.74970.041685
210.1523331.49250.069417
220.1243241.21810.113082
230.0996010.97590.165787
240.0707480.69320.244934
250.0338750.33190.370344
26-0.00489-0.04790.480942
27-0.040773-0.39950.345211
28-0.06844-0.67060.252052
29-0.088273-0.86490.194626
30-0.097422-0.95450.171105
31-0.099107-0.9710.166983
32-0.095467-0.93540.175969
33-0.087519-0.85750.196649
34-0.080467-0.78840.216198
35-0.070618-0.69190.245331
36-0.064091-0.6280.26576
37-0.063494-0.62210.267671
38-0.067832-0.66460.253946
39-0.069868-0.68460.247635
40-0.07936-0.77760.219369
41-0.086143-0.8440.200377
42-0.089004-0.87210.192675
43-0.085873-0.84140.201113
44-0.075325-0.7380.231149
45-0.062801-0.61530.2699
46-0.054044-0.52950.298834
47-0.044523-0.43620.331823
48-0.0434-0.42520.335811

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.94568 & 9.2657 & 0 \tabularnewline
2 & 0.879104 & 8.6134 & 0 \tabularnewline
3 & 0.815001 & 7.9853 & 0 \tabularnewline
4 & 0.753815 & 7.3859 & 0 \tabularnewline
5 & 0.696679 & 6.826 & 0 \tabularnewline
6 & 0.648942 & 6.3583 & 0 \tabularnewline
7 & 0.607242 & 5.9497 & 0 \tabularnewline
8 & 0.571831 & 5.6028 & 0 \tabularnewline
9 & 0.541289 & 5.3035 & 0 \tabularnewline
10 & 0.512122 & 5.0177 & 1e-06 \tabularnewline
11 & 0.484824 & 4.7503 & 4e-06 \tabularnewline
12 & 0.456647 & 4.4742 & 1.1e-05 \tabularnewline
13 & 0.418998 & 4.1053 & 4.2e-05 \tabularnewline
14 & 0.375008 & 3.6743 & 0.000196 \tabularnewline
15 & 0.332668 & 3.2595 & 0.000772 \tabularnewline
16 & 0.288342 & 2.8252 & 0.002874 \tabularnewline
17 & 0.249569 & 2.4453 & 0.008149 \tabularnewline
18 & 0.224969 & 2.2042 & 0.014949 \tabularnewline
19 & 0.203177 & 1.9907 & 0.024677 \tabularnewline
20 & 0.178576 & 1.7497 & 0.041685 \tabularnewline
21 & 0.152333 & 1.4925 & 0.069417 \tabularnewline
22 & 0.124324 & 1.2181 & 0.113082 \tabularnewline
23 & 0.099601 & 0.9759 & 0.165787 \tabularnewline
24 & 0.070748 & 0.6932 & 0.244934 \tabularnewline
25 & 0.033875 & 0.3319 & 0.370344 \tabularnewline
26 & -0.00489 & -0.0479 & 0.480942 \tabularnewline
27 & -0.040773 & -0.3995 & 0.345211 \tabularnewline
28 & -0.06844 & -0.6706 & 0.252052 \tabularnewline
29 & -0.088273 & -0.8649 & 0.194626 \tabularnewline
30 & -0.097422 & -0.9545 & 0.171105 \tabularnewline
31 & -0.099107 & -0.971 & 0.166983 \tabularnewline
32 & -0.095467 & -0.9354 & 0.175969 \tabularnewline
33 & -0.087519 & -0.8575 & 0.196649 \tabularnewline
34 & -0.080467 & -0.7884 & 0.216198 \tabularnewline
35 & -0.070618 & -0.6919 & 0.245331 \tabularnewline
36 & -0.064091 & -0.628 & 0.26576 \tabularnewline
37 & -0.063494 & -0.6221 & 0.267671 \tabularnewline
38 & -0.067832 & -0.6646 & 0.253946 \tabularnewline
39 & -0.069868 & -0.6846 & 0.247635 \tabularnewline
40 & -0.07936 & -0.7776 & 0.219369 \tabularnewline
41 & -0.086143 & -0.844 & 0.200377 \tabularnewline
42 & -0.089004 & -0.8721 & 0.192675 \tabularnewline
43 & -0.085873 & -0.8414 & 0.201113 \tabularnewline
44 & -0.075325 & -0.738 & 0.231149 \tabularnewline
45 & -0.062801 & -0.6153 & 0.2699 \tabularnewline
46 & -0.054044 & -0.5295 & 0.298834 \tabularnewline
47 & -0.044523 & -0.4362 & 0.331823 \tabularnewline
48 & -0.0434 & -0.4252 & 0.335811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279358&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]0.94568[/C][C]9.2657[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.879104[/C][C]8.6134[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.815001[/C][C]7.9853[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.753815[/C][C]7.3859[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.696679[/C][C]6.826[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.648942[/C][C]6.3583[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.607242[/C][C]5.9497[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.571831[/C][C]5.6028[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.541289[/C][C]5.3035[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.512122[/C][C]5.0177[/C][C]1e-06[/C][/ROW]
[ROW][C]11[/C][C]0.484824[/C][C]4.7503[/C][C]4e-06[/C][/ROW]
[ROW][C]12[/C][C]0.456647[/C][C]4.4742[/C][C]1.1e-05[/C][/ROW]
[ROW][C]13[/C][C]0.418998[/C][C]4.1053[/C][C]4.2e-05[/C][/ROW]
[ROW][C]14[/C][C]0.375008[/C][C]3.6743[/C][C]0.000196[/C][/ROW]
[ROW][C]15[/C][C]0.332668[/C][C]3.2595[/C][C]0.000772[/C][/ROW]
[ROW][C]16[/C][C]0.288342[/C][C]2.8252[/C][C]0.002874[/C][/ROW]
[ROW][C]17[/C][C]0.249569[/C][C]2.4453[/C][C]0.008149[/C][/ROW]
[ROW][C]18[/C][C]0.224969[/C][C]2.2042[/C][C]0.014949[/C][/ROW]
[ROW][C]19[/C][C]0.203177[/C][C]1.9907[/C][C]0.024677[/C][/ROW]
[ROW][C]20[/C][C]0.178576[/C][C]1.7497[/C][C]0.041685[/C][/ROW]
[ROW][C]21[/C][C]0.152333[/C][C]1.4925[/C][C]0.069417[/C][/ROW]
[ROW][C]22[/C][C]0.124324[/C][C]1.2181[/C][C]0.113082[/C][/ROW]
[ROW][C]23[/C][C]0.099601[/C][C]0.9759[/C][C]0.165787[/C][/ROW]
[ROW][C]24[/C][C]0.070748[/C][C]0.6932[/C][C]0.244934[/C][/ROW]
[ROW][C]25[/C][C]0.033875[/C][C]0.3319[/C][C]0.370344[/C][/ROW]
[ROW][C]26[/C][C]-0.00489[/C][C]-0.0479[/C][C]0.480942[/C][/ROW]
[ROW][C]27[/C][C]-0.040773[/C][C]-0.3995[/C][C]0.345211[/C][/ROW]
[ROW][C]28[/C][C]-0.06844[/C][C]-0.6706[/C][C]0.252052[/C][/ROW]
[ROW][C]29[/C][C]-0.088273[/C][C]-0.8649[/C][C]0.194626[/C][/ROW]
[ROW][C]30[/C][C]-0.097422[/C][C]-0.9545[/C][C]0.171105[/C][/ROW]
[ROW][C]31[/C][C]-0.099107[/C][C]-0.971[/C][C]0.166983[/C][/ROW]
[ROW][C]32[/C][C]-0.095467[/C][C]-0.9354[/C][C]0.175969[/C][/ROW]
[ROW][C]33[/C][C]-0.087519[/C][C]-0.8575[/C][C]0.196649[/C][/ROW]
[ROW][C]34[/C][C]-0.080467[/C][C]-0.7884[/C][C]0.216198[/C][/ROW]
[ROW][C]35[/C][C]-0.070618[/C][C]-0.6919[/C][C]0.245331[/C][/ROW]
[ROW][C]36[/C][C]-0.064091[/C][C]-0.628[/C][C]0.26576[/C][/ROW]
[ROW][C]37[/C][C]-0.063494[/C][C]-0.6221[/C][C]0.267671[/C][/ROW]
[ROW][C]38[/C][C]-0.067832[/C][C]-0.6646[/C][C]0.253946[/C][/ROW]
[ROW][C]39[/C][C]-0.069868[/C][C]-0.6846[/C][C]0.247635[/C][/ROW]
[ROW][C]40[/C][C]-0.07936[/C][C]-0.7776[/C][C]0.219369[/C][/ROW]
[ROW][C]41[/C][C]-0.086143[/C][C]-0.844[/C][C]0.200377[/C][/ROW]
[ROW][C]42[/C][C]-0.089004[/C][C]-0.8721[/C][C]0.192675[/C][/ROW]
[ROW][C]43[/C][C]-0.085873[/C][C]-0.8414[/C][C]0.201113[/C][/ROW]
[ROW][C]44[/C][C]-0.075325[/C][C]-0.738[/C][C]0.231149[/C][/ROW]
[ROW][C]45[/C][C]-0.062801[/C][C]-0.6153[/C][C]0.2699[/C][/ROW]
[ROW][C]46[/C][C]-0.054044[/C][C]-0.5295[/C][C]0.298834[/C][/ROW]
[ROW][C]47[/C][C]-0.044523[/C][C]-0.4362[/C][C]0.331823[/C][/ROW]
[ROW][C]48[/C][C]-0.0434[/C][C]-0.4252[/C][C]0.335811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279358&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279358&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
10.945689.26570
20.8791048.61340
30.8150017.98530
40.7538157.38590
50.6966796.8260
60.6489426.35830
70.6072425.94970
80.5718315.60280
90.5412895.30350
100.5121225.01771e-06
110.4848244.75034e-06
120.4566474.47421.1e-05
130.4189984.10534.2e-05
140.3750083.67430.000196
150.3326683.25950.000772
160.2883422.82520.002874
170.2495692.44530.008149
180.2249692.20420.014949
190.2031771.99070.024677
200.1785761.74970.041685
210.1523331.49250.069417
220.1243241.21810.113082
230.0996010.97590.165787
240.0707480.69320.244934
250.0338750.33190.370344
26-0.00489-0.04790.480942
27-0.040773-0.39950.345211
28-0.06844-0.67060.252052
29-0.088273-0.86490.194626
30-0.097422-0.95450.171105
31-0.099107-0.9710.166983
32-0.095467-0.93540.175969
33-0.087519-0.85750.196649
34-0.080467-0.78840.216198
35-0.070618-0.69190.245331
36-0.064091-0.6280.26576
37-0.063494-0.62210.267671
38-0.067832-0.66460.253946
39-0.069868-0.68460.247635
40-0.07936-0.77760.219369
41-0.086143-0.8440.200377
42-0.089004-0.87210.192675
43-0.085873-0.84140.201113
44-0.075325-0.7380.231149
45-0.062801-0.61530.2699
46-0.054044-0.52950.298834
47-0.044523-0.43620.331823
48-0.0434-0.42520.335811






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.945689.26570
2-0.14388-1.40970.080926
30.0009540.00940.496279
4-0.013803-0.13520.446352
5-0.000478-0.00470.498137
60.0501750.49160.312059
70.011750.11510.454293
80.0285840.28010.390016
90.0169790.16640.434114
10-0.008833-0.08650.465605
110.0073380.07190.471416
12-0.021807-0.21370.415631
13-0.097574-0.9560.170731
14-0.057759-0.56590.286386
15-0.000169-0.00170.49934
16-0.05231-0.51250.304728
170.0261670.25640.399102
180.0856750.83940.201655
19-0.030735-0.30110.38198
20-0.051684-0.50640.306868
21-0.038473-0.3770.353518
22-0.034584-0.33890.367731
230.0226740.22220.412333
24-0.065938-0.64610.259891
25-0.081322-0.79680.213771
26-0.026498-0.25960.397853
27-0.010952-0.10730.457386
280.0464940.45560.324871
290.0225010.22050.41299
300.0365540.35820.360507
310.0258930.25370.400135
320.0341250.33440.36942
330.03610.35370.362167
340.0038060.03730.485164
350.0554250.54310.294175
36-0.022029-0.21580.414784
37-0.027921-0.27360.392501
38-0.028273-0.2770.391182
390.0307620.30140.381878
40-0.077913-0.76340.223552
410.0080490.07890.468653
42-0.014946-0.14640.441942
430.0244760.23980.405493
440.0588460.57660.28279
450.008710.08530.466083
46-0.029325-0.28730.38724
470.0173780.17030.432578
48-0.081366-0.79720.213646

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.94568 & 9.2657 & 0 \tabularnewline
2 & -0.14388 & -1.4097 & 0.080926 \tabularnewline
3 & 0.000954 & 0.0094 & 0.496279 \tabularnewline
4 & -0.013803 & -0.1352 & 0.446352 \tabularnewline
5 & -0.000478 & -0.0047 & 0.498137 \tabularnewline
6 & 0.050175 & 0.4916 & 0.312059 \tabularnewline
7 & 0.01175 & 0.1151 & 0.454293 \tabularnewline
8 & 0.028584 & 0.2801 & 0.390016 \tabularnewline
9 & 0.016979 & 0.1664 & 0.434114 \tabularnewline
10 & -0.008833 & -0.0865 & 0.465605 \tabularnewline
11 & 0.007338 & 0.0719 & 0.471416 \tabularnewline
12 & -0.021807 & -0.2137 & 0.415631 \tabularnewline
13 & -0.097574 & -0.956 & 0.170731 \tabularnewline
14 & -0.057759 & -0.5659 & 0.286386 \tabularnewline
15 & -0.000169 & -0.0017 & 0.49934 \tabularnewline
16 & -0.05231 & -0.5125 & 0.304728 \tabularnewline
17 & 0.026167 & 0.2564 & 0.399102 \tabularnewline
18 & 0.085675 & 0.8394 & 0.201655 \tabularnewline
19 & -0.030735 & -0.3011 & 0.38198 \tabularnewline
20 & -0.051684 & -0.5064 & 0.306868 \tabularnewline
21 & -0.038473 & -0.377 & 0.353518 \tabularnewline
22 & -0.034584 & -0.3389 & 0.367731 \tabularnewline
23 & 0.022674 & 0.2222 & 0.412333 \tabularnewline
24 & -0.065938 & -0.6461 & 0.259891 \tabularnewline
25 & -0.081322 & -0.7968 & 0.213771 \tabularnewline
26 & -0.026498 & -0.2596 & 0.397853 \tabularnewline
27 & -0.010952 & -0.1073 & 0.457386 \tabularnewline
28 & 0.046494 & 0.4556 & 0.324871 \tabularnewline
29 & 0.022501 & 0.2205 & 0.41299 \tabularnewline
30 & 0.036554 & 0.3582 & 0.360507 \tabularnewline
31 & 0.025893 & 0.2537 & 0.400135 \tabularnewline
32 & 0.034125 & 0.3344 & 0.36942 \tabularnewline
33 & 0.0361 & 0.3537 & 0.362167 \tabularnewline
34 & 0.003806 & 0.0373 & 0.485164 \tabularnewline
35 & 0.055425 & 0.5431 & 0.294175 \tabularnewline
36 & -0.022029 & -0.2158 & 0.414784 \tabularnewline
37 & -0.027921 & -0.2736 & 0.392501 \tabularnewline
38 & -0.028273 & -0.277 & 0.391182 \tabularnewline
39 & 0.030762 & 0.3014 & 0.381878 \tabularnewline
40 & -0.077913 & -0.7634 & 0.223552 \tabularnewline
41 & 0.008049 & 0.0789 & 0.468653 \tabularnewline
42 & -0.014946 & -0.1464 & 0.441942 \tabularnewline
43 & 0.024476 & 0.2398 & 0.405493 \tabularnewline
44 & 0.058846 & 0.5766 & 0.28279 \tabularnewline
45 & 0.00871 & 0.0853 & 0.466083 \tabularnewline
46 & -0.029325 & -0.2873 & 0.38724 \tabularnewline
47 & 0.017378 & 0.1703 & 0.432578 \tabularnewline
48 & -0.081366 & -0.7972 & 0.213646 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279358&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]0.94568[/C][C]9.2657[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.14388[/C][C]-1.4097[/C][C]0.080926[/C][/ROW]
[ROW][C]3[/C][C]0.000954[/C][C]0.0094[/C][C]0.496279[/C][/ROW]
[ROW][C]4[/C][C]-0.013803[/C][C]-0.1352[/C][C]0.446352[/C][/ROW]
[ROW][C]5[/C][C]-0.000478[/C][C]-0.0047[/C][C]0.498137[/C][/ROW]
[ROW][C]6[/C][C]0.050175[/C][C]0.4916[/C][C]0.312059[/C][/ROW]
[ROW][C]7[/C][C]0.01175[/C][C]0.1151[/C][C]0.454293[/C][/ROW]
[ROW][C]8[/C][C]0.028584[/C][C]0.2801[/C][C]0.390016[/C][/ROW]
[ROW][C]9[/C][C]0.016979[/C][C]0.1664[/C][C]0.434114[/C][/ROW]
[ROW][C]10[/C][C]-0.008833[/C][C]-0.0865[/C][C]0.465605[/C][/ROW]
[ROW][C]11[/C][C]0.007338[/C][C]0.0719[/C][C]0.471416[/C][/ROW]
[ROW][C]12[/C][C]-0.021807[/C][C]-0.2137[/C][C]0.415631[/C][/ROW]
[ROW][C]13[/C][C]-0.097574[/C][C]-0.956[/C][C]0.170731[/C][/ROW]
[ROW][C]14[/C][C]-0.057759[/C][C]-0.5659[/C][C]0.286386[/C][/ROW]
[ROW][C]15[/C][C]-0.000169[/C][C]-0.0017[/C][C]0.49934[/C][/ROW]
[ROW][C]16[/C][C]-0.05231[/C][C]-0.5125[/C][C]0.304728[/C][/ROW]
[ROW][C]17[/C][C]0.026167[/C][C]0.2564[/C][C]0.399102[/C][/ROW]
[ROW][C]18[/C][C]0.085675[/C][C]0.8394[/C][C]0.201655[/C][/ROW]
[ROW][C]19[/C][C]-0.030735[/C][C]-0.3011[/C][C]0.38198[/C][/ROW]
[ROW][C]20[/C][C]-0.051684[/C][C]-0.5064[/C][C]0.306868[/C][/ROW]
[ROW][C]21[/C][C]-0.038473[/C][C]-0.377[/C][C]0.353518[/C][/ROW]
[ROW][C]22[/C][C]-0.034584[/C][C]-0.3389[/C][C]0.367731[/C][/ROW]
[ROW][C]23[/C][C]0.022674[/C][C]0.2222[/C][C]0.412333[/C][/ROW]
[ROW][C]24[/C][C]-0.065938[/C][C]-0.6461[/C][C]0.259891[/C][/ROW]
[ROW][C]25[/C][C]-0.081322[/C][C]-0.7968[/C][C]0.213771[/C][/ROW]
[ROW][C]26[/C][C]-0.026498[/C][C]-0.2596[/C][C]0.397853[/C][/ROW]
[ROW][C]27[/C][C]-0.010952[/C][C]-0.1073[/C][C]0.457386[/C][/ROW]
[ROW][C]28[/C][C]0.046494[/C][C]0.4556[/C][C]0.324871[/C][/ROW]
[ROW][C]29[/C][C]0.022501[/C][C]0.2205[/C][C]0.41299[/C][/ROW]
[ROW][C]30[/C][C]0.036554[/C][C]0.3582[/C][C]0.360507[/C][/ROW]
[ROW][C]31[/C][C]0.025893[/C][C]0.2537[/C][C]0.400135[/C][/ROW]
[ROW][C]32[/C][C]0.034125[/C][C]0.3344[/C][C]0.36942[/C][/ROW]
[ROW][C]33[/C][C]0.0361[/C][C]0.3537[/C][C]0.362167[/C][/ROW]
[ROW][C]34[/C][C]0.003806[/C][C]0.0373[/C][C]0.485164[/C][/ROW]
[ROW][C]35[/C][C]0.055425[/C][C]0.5431[/C][C]0.294175[/C][/ROW]
[ROW][C]36[/C][C]-0.022029[/C][C]-0.2158[/C][C]0.414784[/C][/ROW]
[ROW][C]37[/C][C]-0.027921[/C][C]-0.2736[/C][C]0.392501[/C][/ROW]
[ROW][C]38[/C][C]-0.028273[/C][C]-0.277[/C][C]0.391182[/C][/ROW]
[ROW][C]39[/C][C]0.030762[/C][C]0.3014[/C][C]0.381878[/C][/ROW]
[ROW][C]40[/C][C]-0.077913[/C][C]-0.7634[/C][C]0.223552[/C][/ROW]
[ROW][C]41[/C][C]0.008049[/C][C]0.0789[/C][C]0.468653[/C][/ROW]
[ROW][C]42[/C][C]-0.014946[/C][C]-0.1464[/C][C]0.441942[/C][/ROW]
[ROW][C]43[/C][C]0.024476[/C][C]0.2398[/C][C]0.405493[/C][/ROW]
[ROW][C]44[/C][C]0.058846[/C][C]0.5766[/C][C]0.28279[/C][/ROW]
[ROW][C]45[/C][C]0.00871[/C][C]0.0853[/C][C]0.466083[/C][/ROW]
[ROW][C]46[/C][C]-0.029325[/C][C]-0.2873[/C][C]0.38724[/C][/ROW]
[ROW][C]47[/C][C]0.017378[/C][C]0.1703[/C][C]0.432578[/C][/ROW]
[ROW][C]48[/C][C]-0.081366[/C][C]-0.7972[/C][C]0.213646[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279358&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279358&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
10.945689.26570
2-0.14388-1.40970.080926
30.0009540.00940.496279
4-0.013803-0.13520.446352
5-0.000478-0.00470.498137
60.0501750.49160.312059
70.011750.11510.454293
80.0285840.28010.390016
90.0169790.16640.434114
10-0.008833-0.08650.465605
110.0073380.07190.471416
12-0.021807-0.21370.415631
13-0.097574-0.9560.170731
14-0.057759-0.56590.286386
15-0.000169-0.00170.49934
16-0.05231-0.51250.304728
170.0261670.25640.399102
180.0856750.83940.201655
19-0.030735-0.30110.38198
20-0.051684-0.50640.306868
21-0.038473-0.3770.353518
22-0.034584-0.33890.367731
230.0226740.22220.412333
24-0.065938-0.64610.259891
25-0.081322-0.79680.213771
26-0.026498-0.25960.397853
27-0.010952-0.10730.457386
280.0464940.45560.324871
290.0225010.22050.41299
300.0365540.35820.360507
310.0258930.25370.400135
320.0341250.33440.36942
330.03610.35370.362167
340.0038060.03730.485164
350.0554250.54310.294175
36-0.022029-0.21580.414784
37-0.027921-0.27360.392501
38-0.028273-0.2770.391182
390.0307620.30140.381878
40-0.077913-0.76340.223552
410.0080490.07890.468653
42-0.014946-0.14640.441942
430.0244760.23980.405493
440.0588460.57660.28279
450.008710.08530.466083
46-0.029325-0.28730.38724
470.0173780.17030.432578
48-0.081366-0.79720.213646


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; 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')