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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, 14 Mar 2016 19:59:35 +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/2016/Mar/14/t1457985606pvw0efzofkksuou.htm/, Retrieved Mon, 29 Apr 2024 00:23:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294050, Retrieved Mon, 29 Apr 2024 00:23:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64

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] [] [2016-03-14 19:59:35] [1e8cb0485fd9b8c1cf436607044e417d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92.86
94.06
95.51
96.05
96.71
97.91
97.74
97.64
98.55
98.46
99.19
99.18
99.95
100.66
101.12
101.14
100.73
99.92
100.06
100.64
100.89
100.87
100.72
100.72
100.98
100.15
100.13
100.39
99.87
99.93
99.96
99.61
99.57
99.71
99.78
99.92
100.3
100.83
100.84
97.87
97.99
98.03
97.58
97.45
97.47
98.31
98.29
98.13
98.44
98.05
98.32
97.55
97.74
98.01
97.93
99.23
101.03
100.81
100.57
100.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294050&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294050&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294050&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1771661.36080.08937
2-0.011493-0.08830.464977
30.090330.69380.245252
4-0.016693-0.12820.449204
5-0.005538-0.04250.483108
6-0.078986-0.60670.273188
70.0691610.53120.298624
80.2008711.54290.064099
90.027170.20870.417701
100.15381.18140.1211
110.162711.24980.108154
120.0339170.26050.397683
13-0.079097-0.60760.272907
140.0105830.08130.467744
15-0.063309-0.48630.314283
16-0.130411-1.00170.160287
17-0.158965-1.2210.113466
180.080370.61730.269695
190.0689980.530.299057
20-0.077187-0.59290.277763
21-0.032713-0.25130.401237
220.0882720.6780.250202
23-0.013131-0.10090.460003
24-0.056373-0.4330.333293
25-0.049961-0.38380.351268
26-0.044302-0.34030.367423
27-0.133577-1.0260.154534
28-0.055233-0.42430.336463
29-0.088387-0.67890.249925
30-0.071131-0.54640.293437
31-0.132405-1.0170.156648
320.0635950.48850.31351
330.0494720.380.352655
34-0.105823-0.81280.209788
35-0.016409-0.1260.450065
36-0.014807-0.11370.454918
37-0.145989-1.12140.133338
38-0.205133-1.57570.060227
39-0.160934-1.23620.11065
40-0.021768-0.16720.43389
41-0.037517-0.28820.387111
420.0678620.52130.302068
430.0877890.67430.25137
440.0276460.21230.416283
45-0.011465-0.08810.465062
46-0.04267-0.32780.372129
47-0.029956-0.23010.409407
480.0193590.14870.441149

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.177166 & 1.3608 & 0.08937 \tabularnewline
2 & -0.011493 & -0.0883 & 0.464977 \tabularnewline
3 & 0.09033 & 0.6938 & 0.245252 \tabularnewline
4 & -0.016693 & -0.1282 & 0.449204 \tabularnewline
5 & -0.005538 & -0.0425 & 0.483108 \tabularnewline
6 & -0.078986 & -0.6067 & 0.273188 \tabularnewline
7 & 0.069161 & 0.5312 & 0.298624 \tabularnewline
8 & 0.200871 & 1.5429 & 0.064099 \tabularnewline
9 & 0.02717 & 0.2087 & 0.417701 \tabularnewline
10 & 0.1538 & 1.1814 & 0.1211 \tabularnewline
11 & 0.16271 & 1.2498 & 0.108154 \tabularnewline
12 & 0.033917 & 0.2605 & 0.397683 \tabularnewline
13 & -0.079097 & -0.6076 & 0.272907 \tabularnewline
14 & 0.010583 & 0.0813 & 0.467744 \tabularnewline
15 & -0.063309 & -0.4863 & 0.314283 \tabularnewline
16 & -0.130411 & -1.0017 & 0.160287 \tabularnewline
17 & -0.158965 & -1.221 & 0.113466 \tabularnewline
18 & 0.08037 & 0.6173 & 0.269695 \tabularnewline
19 & 0.068998 & 0.53 & 0.299057 \tabularnewline
20 & -0.077187 & -0.5929 & 0.277763 \tabularnewline
21 & -0.032713 & -0.2513 & 0.401237 \tabularnewline
22 & 0.088272 & 0.678 & 0.250202 \tabularnewline
23 & -0.013131 & -0.1009 & 0.460003 \tabularnewline
24 & -0.056373 & -0.433 & 0.333293 \tabularnewline
25 & -0.049961 & -0.3838 & 0.351268 \tabularnewline
26 & -0.044302 & -0.3403 & 0.367423 \tabularnewline
27 & -0.133577 & -1.026 & 0.154534 \tabularnewline
28 & -0.055233 & -0.4243 & 0.336463 \tabularnewline
29 & -0.088387 & -0.6789 & 0.249925 \tabularnewline
30 & -0.071131 & -0.5464 & 0.293437 \tabularnewline
31 & -0.132405 & -1.017 & 0.156648 \tabularnewline
32 & 0.063595 & 0.4885 & 0.31351 \tabularnewline
33 & 0.049472 & 0.38 & 0.352655 \tabularnewline
34 & -0.105823 & -0.8128 & 0.209788 \tabularnewline
35 & -0.016409 & -0.126 & 0.450065 \tabularnewline
36 & -0.014807 & -0.1137 & 0.454918 \tabularnewline
37 & -0.145989 & -1.1214 & 0.133338 \tabularnewline
38 & -0.205133 & -1.5757 & 0.060227 \tabularnewline
39 & -0.160934 & -1.2362 & 0.11065 \tabularnewline
40 & -0.021768 & -0.1672 & 0.43389 \tabularnewline
41 & -0.037517 & -0.2882 & 0.387111 \tabularnewline
42 & 0.067862 & 0.5213 & 0.302068 \tabularnewline
43 & 0.087789 & 0.6743 & 0.25137 \tabularnewline
44 & 0.027646 & 0.2123 & 0.416283 \tabularnewline
45 & -0.011465 & -0.0881 & 0.465062 \tabularnewline
46 & -0.04267 & -0.3278 & 0.372129 \tabularnewline
47 & -0.029956 & -0.2301 & 0.409407 \tabularnewline
48 & 0.019359 & 0.1487 & 0.441149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294050&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]0.177166[/C][C]1.3608[/C][C]0.08937[/C][/ROW]
[ROW][C]2[/C][C]-0.011493[/C][C]-0.0883[/C][C]0.464977[/C][/ROW]
[ROW][C]3[/C][C]0.09033[/C][C]0.6938[/C][C]0.245252[/C][/ROW]
[ROW][C]4[/C][C]-0.016693[/C][C]-0.1282[/C][C]0.449204[/C][/ROW]
[ROW][C]5[/C][C]-0.005538[/C][C]-0.0425[/C][C]0.483108[/C][/ROW]
[ROW][C]6[/C][C]-0.078986[/C][C]-0.6067[/C][C]0.273188[/C][/ROW]
[ROW][C]7[/C][C]0.069161[/C][C]0.5312[/C][C]0.298624[/C][/ROW]
[ROW][C]8[/C][C]0.200871[/C][C]1.5429[/C][C]0.064099[/C][/ROW]
[ROW][C]9[/C][C]0.02717[/C][C]0.2087[/C][C]0.417701[/C][/ROW]
[ROW][C]10[/C][C]0.1538[/C][C]1.1814[/C][C]0.1211[/C][/ROW]
[ROW][C]11[/C][C]0.16271[/C][C]1.2498[/C][C]0.108154[/C][/ROW]
[ROW][C]12[/C][C]0.033917[/C][C]0.2605[/C][C]0.397683[/C][/ROW]
[ROW][C]13[/C][C]-0.079097[/C][C]-0.6076[/C][C]0.272907[/C][/ROW]
[ROW][C]14[/C][C]0.010583[/C][C]0.0813[/C][C]0.467744[/C][/ROW]
[ROW][C]15[/C][C]-0.063309[/C][C]-0.4863[/C][C]0.314283[/C][/ROW]
[ROW][C]16[/C][C]-0.130411[/C][C]-1.0017[/C][C]0.160287[/C][/ROW]
[ROW][C]17[/C][C]-0.158965[/C][C]-1.221[/C][C]0.113466[/C][/ROW]
[ROW][C]18[/C][C]0.08037[/C][C]0.6173[/C][C]0.269695[/C][/ROW]
[ROW][C]19[/C][C]0.068998[/C][C]0.53[/C][C]0.299057[/C][/ROW]
[ROW][C]20[/C][C]-0.077187[/C][C]-0.5929[/C][C]0.277763[/C][/ROW]
[ROW][C]21[/C][C]-0.032713[/C][C]-0.2513[/C][C]0.401237[/C][/ROW]
[ROW][C]22[/C][C]0.088272[/C][C]0.678[/C][C]0.250202[/C][/ROW]
[ROW][C]23[/C][C]-0.013131[/C][C]-0.1009[/C][C]0.460003[/C][/ROW]
[ROW][C]24[/C][C]-0.056373[/C][C]-0.433[/C][C]0.333293[/C][/ROW]
[ROW][C]25[/C][C]-0.049961[/C][C]-0.3838[/C][C]0.351268[/C][/ROW]
[ROW][C]26[/C][C]-0.044302[/C][C]-0.3403[/C][C]0.367423[/C][/ROW]
[ROW][C]27[/C][C]-0.133577[/C][C]-1.026[/C][C]0.154534[/C][/ROW]
[ROW][C]28[/C][C]-0.055233[/C][C]-0.4243[/C][C]0.336463[/C][/ROW]
[ROW][C]29[/C][C]-0.088387[/C][C]-0.6789[/C][C]0.249925[/C][/ROW]
[ROW][C]30[/C][C]-0.071131[/C][C]-0.5464[/C][C]0.293437[/C][/ROW]
[ROW][C]31[/C][C]-0.132405[/C][C]-1.017[/C][C]0.156648[/C][/ROW]
[ROW][C]32[/C][C]0.063595[/C][C]0.4885[/C][C]0.31351[/C][/ROW]
[ROW][C]33[/C][C]0.049472[/C][C]0.38[/C][C]0.352655[/C][/ROW]
[ROW][C]34[/C][C]-0.105823[/C][C]-0.8128[/C][C]0.209788[/C][/ROW]
[ROW][C]35[/C][C]-0.016409[/C][C]-0.126[/C][C]0.450065[/C][/ROW]
[ROW][C]36[/C][C]-0.014807[/C][C]-0.1137[/C][C]0.454918[/C][/ROW]
[ROW][C]37[/C][C]-0.145989[/C][C]-1.1214[/C][C]0.133338[/C][/ROW]
[ROW][C]38[/C][C]-0.205133[/C][C]-1.5757[/C][C]0.060227[/C][/ROW]
[ROW][C]39[/C][C]-0.160934[/C][C]-1.2362[/C][C]0.11065[/C][/ROW]
[ROW][C]40[/C][C]-0.021768[/C][C]-0.1672[/C][C]0.43389[/C][/ROW]
[ROW][C]41[/C][C]-0.037517[/C][C]-0.2882[/C][C]0.387111[/C][/ROW]
[ROW][C]42[/C][C]0.067862[/C][C]0.5213[/C][C]0.302068[/C][/ROW]
[ROW][C]43[/C][C]0.087789[/C][C]0.6743[/C][C]0.25137[/C][/ROW]
[ROW][C]44[/C][C]0.027646[/C][C]0.2123[/C][C]0.416283[/C][/ROW]
[ROW][C]45[/C][C]-0.011465[/C][C]-0.0881[/C][C]0.465062[/C][/ROW]
[ROW][C]46[/C][C]-0.04267[/C][C]-0.3278[/C][C]0.372129[/C][/ROW]
[ROW][C]47[/C][C]-0.029956[/C][C]-0.2301[/C][C]0.409407[/C][/ROW]
[ROW][C]48[/C][C]0.019359[/C][C]0.1487[/C][C]0.441149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294050&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294050&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
10.1771661.36080.08937
2-0.011493-0.08830.464977
30.090330.69380.245252
4-0.016693-0.12820.449204
5-0.005538-0.04250.483108
6-0.078986-0.60670.273188
70.0691610.53120.298624
80.2008711.54290.064099
90.027170.20870.417701
100.15381.18140.1211
110.162711.24980.108154
120.0339170.26050.397683
13-0.079097-0.60760.272907
140.0105830.08130.467744
15-0.063309-0.48630.314283
16-0.130411-1.00170.160287
17-0.158965-1.2210.113466
180.080370.61730.269695
190.0689980.530.299057
20-0.077187-0.59290.277763
21-0.032713-0.25130.401237
220.0882720.6780.250202
23-0.013131-0.10090.460003
24-0.056373-0.4330.333293
25-0.049961-0.38380.351268
26-0.044302-0.34030.367423
27-0.133577-1.0260.154534
28-0.055233-0.42430.336463
29-0.088387-0.67890.249925
30-0.071131-0.54640.293437
31-0.132405-1.0170.156648
320.0635950.48850.31351
330.0494720.380.352655
34-0.105823-0.81280.209788
35-0.016409-0.1260.450065
36-0.014807-0.11370.454918
37-0.145989-1.12140.133338
38-0.205133-1.57570.060227
39-0.160934-1.23620.11065
40-0.021768-0.16720.43389
41-0.037517-0.28820.387111
420.0678620.52130.302068
430.0877890.67430.25137
440.0276460.21230.416283
45-0.011465-0.08810.465062
46-0.04267-0.32780.372129
47-0.029956-0.23010.409407
480.0193590.14870.441149






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1771661.36080.08937
2-0.044271-0.340.367514
30.1037540.79690.214339
4-0.05535-0.42510.336138
50.0156210.120.452451
6-0.097467-0.74870.228518
70.1165430.89520.187163
80.1650051.26740.104991
9-0.017081-0.13120.448031
100.156971.20570.116372
110.0829570.63720.263228
120.0105710.08120.467778
13-0.105101-0.80730.21137
140.0685880.52680.300142
15-0.125933-0.96730.16867
16-0.100987-0.77570.220512
17-0.161725-1.24220.109533
180.0919290.70610.241446
19-0.032905-0.25270.40067
20-0.075092-0.57680.283137
21-0.04937-0.37920.352943
220.0781880.60060.275211
230.0121150.09310.463087
240.0377450.28990.386444
250.0208090.15980.436778
26-0.039987-0.30710.379908
27-0.060446-0.46430.322073
280.0251910.19350.423616
29-0.132468-1.01750.156534
30-0.08868-0.68120.249216
31-0.118815-0.91260.182574
320.095270.73180.233598
33-0.053928-0.41420.340104
34-0.072978-0.56060.288612
350.0789210.60620.273353
36-0.015908-0.12220.45158
37-0.110972-0.85240.198722
38-0.124073-0.9530.172234
390.0017070.01310.494793
40-0.052103-0.40020.345223
410.0169090.12990.448553
420.1035260.79520.214843
430.0219960.1690.433207
44-0.039751-0.30530.380593
450.0695310.53410.297646
46-0.03889-0.29870.383102
47-0.013595-0.10440.458595
480.1296920.99620.161615

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.177166 & 1.3608 & 0.08937 \tabularnewline
2 & -0.044271 & -0.34 & 0.367514 \tabularnewline
3 & 0.103754 & 0.7969 & 0.214339 \tabularnewline
4 & -0.05535 & -0.4251 & 0.336138 \tabularnewline
5 & 0.015621 & 0.12 & 0.452451 \tabularnewline
6 & -0.097467 & -0.7487 & 0.228518 \tabularnewline
7 & 0.116543 & 0.8952 & 0.187163 \tabularnewline
8 & 0.165005 & 1.2674 & 0.104991 \tabularnewline
9 & -0.017081 & -0.1312 & 0.448031 \tabularnewline
10 & 0.15697 & 1.2057 & 0.116372 \tabularnewline
11 & 0.082957 & 0.6372 & 0.263228 \tabularnewline
12 & 0.010571 & 0.0812 & 0.467778 \tabularnewline
13 & -0.105101 & -0.8073 & 0.21137 \tabularnewline
14 & 0.068588 & 0.5268 & 0.300142 \tabularnewline
15 & -0.125933 & -0.9673 & 0.16867 \tabularnewline
16 & -0.100987 & -0.7757 & 0.220512 \tabularnewline
17 & -0.161725 & -1.2422 & 0.109533 \tabularnewline
18 & 0.091929 & 0.7061 & 0.241446 \tabularnewline
19 & -0.032905 & -0.2527 & 0.40067 \tabularnewline
20 & -0.075092 & -0.5768 & 0.283137 \tabularnewline
21 & -0.04937 & -0.3792 & 0.352943 \tabularnewline
22 & 0.078188 & 0.6006 & 0.275211 \tabularnewline
23 & 0.012115 & 0.0931 & 0.463087 \tabularnewline
24 & 0.037745 & 0.2899 & 0.386444 \tabularnewline
25 & 0.020809 & 0.1598 & 0.436778 \tabularnewline
26 & -0.039987 & -0.3071 & 0.379908 \tabularnewline
27 & -0.060446 & -0.4643 & 0.322073 \tabularnewline
28 & 0.025191 & 0.1935 & 0.423616 \tabularnewline
29 & -0.132468 & -1.0175 & 0.156534 \tabularnewline
30 & -0.08868 & -0.6812 & 0.249216 \tabularnewline
31 & -0.118815 & -0.9126 & 0.182574 \tabularnewline
32 & 0.09527 & 0.7318 & 0.233598 \tabularnewline
33 & -0.053928 & -0.4142 & 0.340104 \tabularnewline
34 & -0.072978 & -0.5606 & 0.288612 \tabularnewline
35 & 0.078921 & 0.6062 & 0.273353 \tabularnewline
36 & -0.015908 & -0.1222 & 0.45158 \tabularnewline
37 & -0.110972 & -0.8524 & 0.198722 \tabularnewline
38 & -0.124073 & -0.953 & 0.172234 \tabularnewline
39 & 0.001707 & 0.0131 & 0.494793 \tabularnewline
40 & -0.052103 & -0.4002 & 0.345223 \tabularnewline
41 & 0.016909 & 0.1299 & 0.448553 \tabularnewline
42 & 0.103526 & 0.7952 & 0.214843 \tabularnewline
43 & 0.021996 & 0.169 & 0.433207 \tabularnewline
44 & -0.039751 & -0.3053 & 0.380593 \tabularnewline
45 & 0.069531 & 0.5341 & 0.297646 \tabularnewline
46 & -0.03889 & -0.2987 & 0.383102 \tabularnewline
47 & -0.013595 & -0.1044 & 0.458595 \tabularnewline
48 & 0.129692 & 0.9962 & 0.161615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294050&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]0.177166[/C][C]1.3608[/C][C]0.08937[/C][/ROW]
[ROW][C]2[/C][C]-0.044271[/C][C]-0.34[/C][C]0.367514[/C][/ROW]
[ROW][C]3[/C][C]0.103754[/C][C]0.7969[/C][C]0.214339[/C][/ROW]
[ROW][C]4[/C][C]-0.05535[/C][C]-0.4251[/C][C]0.336138[/C][/ROW]
[ROW][C]5[/C][C]0.015621[/C][C]0.12[/C][C]0.452451[/C][/ROW]
[ROW][C]6[/C][C]-0.097467[/C][C]-0.7487[/C][C]0.228518[/C][/ROW]
[ROW][C]7[/C][C]0.116543[/C][C]0.8952[/C][C]0.187163[/C][/ROW]
[ROW][C]8[/C][C]0.165005[/C][C]1.2674[/C][C]0.104991[/C][/ROW]
[ROW][C]9[/C][C]-0.017081[/C][C]-0.1312[/C][C]0.448031[/C][/ROW]
[ROW][C]10[/C][C]0.15697[/C][C]1.2057[/C][C]0.116372[/C][/ROW]
[ROW][C]11[/C][C]0.082957[/C][C]0.6372[/C][C]0.263228[/C][/ROW]
[ROW][C]12[/C][C]0.010571[/C][C]0.0812[/C][C]0.467778[/C][/ROW]
[ROW][C]13[/C][C]-0.105101[/C][C]-0.8073[/C][C]0.21137[/C][/ROW]
[ROW][C]14[/C][C]0.068588[/C][C]0.5268[/C][C]0.300142[/C][/ROW]
[ROW][C]15[/C][C]-0.125933[/C][C]-0.9673[/C][C]0.16867[/C][/ROW]
[ROW][C]16[/C][C]-0.100987[/C][C]-0.7757[/C][C]0.220512[/C][/ROW]
[ROW][C]17[/C][C]-0.161725[/C][C]-1.2422[/C][C]0.109533[/C][/ROW]
[ROW][C]18[/C][C]0.091929[/C][C]0.7061[/C][C]0.241446[/C][/ROW]
[ROW][C]19[/C][C]-0.032905[/C][C]-0.2527[/C][C]0.40067[/C][/ROW]
[ROW][C]20[/C][C]-0.075092[/C][C]-0.5768[/C][C]0.283137[/C][/ROW]
[ROW][C]21[/C][C]-0.04937[/C][C]-0.3792[/C][C]0.352943[/C][/ROW]
[ROW][C]22[/C][C]0.078188[/C][C]0.6006[/C][C]0.275211[/C][/ROW]
[ROW][C]23[/C][C]0.012115[/C][C]0.0931[/C][C]0.463087[/C][/ROW]
[ROW][C]24[/C][C]0.037745[/C][C]0.2899[/C][C]0.386444[/C][/ROW]
[ROW][C]25[/C][C]0.020809[/C][C]0.1598[/C][C]0.436778[/C][/ROW]
[ROW][C]26[/C][C]-0.039987[/C][C]-0.3071[/C][C]0.379908[/C][/ROW]
[ROW][C]27[/C][C]-0.060446[/C][C]-0.4643[/C][C]0.322073[/C][/ROW]
[ROW][C]28[/C][C]0.025191[/C][C]0.1935[/C][C]0.423616[/C][/ROW]
[ROW][C]29[/C][C]-0.132468[/C][C]-1.0175[/C][C]0.156534[/C][/ROW]
[ROW][C]30[/C][C]-0.08868[/C][C]-0.6812[/C][C]0.249216[/C][/ROW]
[ROW][C]31[/C][C]-0.118815[/C][C]-0.9126[/C][C]0.182574[/C][/ROW]
[ROW][C]32[/C][C]0.09527[/C][C]0.7318[/C][C]0.233598[/C][/ROW]
[ROW][C]33[/C][C]-0.053928[/C][C]-0.4142[/C][C]0.340104[/C][/ROW]
[ROW][C]34[/C][C]-0.072978[/C][C]-0.5606[/C][C]0.288612[/C][/ROW]
[ROW][C]35[/C][C]0.078921[/C][C]0.6062[/C][C]0.273353[/C][/ROW]
[ROW][C]36[/C][C]-0.015908[/C][C]-0.1222[/C][C]0.45158[/C][/ROW]
[ROW][C]37[/C][C]-0.110972[/C][C]-0.8524[/C][C]0.198722[/C][/ROW]
[ROW][C]38[/C][C]-0.124073[/C][C]-0.953[/C][C]0.172234[/C][/ROW]
[ROW][C]39[/C][C]0.001707[/C][C]0.0131[/C][C]0.494793[/C][/ROW]
[ROW][C]40[/C][C]-0.052103[/C][C]-0.4002[/C][C]0.345223[/C][/ROW]
[ROW][C]41[/C][C]0.016909[/C][C]0.1299[/C][C]0.448553[/C][/ROW]
[ROW][C]42[/C][C]0.103526[/C][C]0.7952[/C][C]0.214843[/C][/ROW]
[ROW][C]43[/C][C]0.021996[/C][C]0.169[/C][C]0.433207[/C][/ROW]
[ROW][C]44[/C][C]-0.039751[/C][C]-0.3053[/C][C]0.380593[/C][/ROW]
[ROW][C]45[/C][C]0.069531[/C][C]0.5341[/C][C]0.297646[/C][/ROW]
[ROW][C]46[/C][C]-0.03889[/C][C]-0.2987[/C][C]0.383102[/C][/ROW]
[ROW][C]47[/C][C]-0.013595[/C][C]-0.1044[/C][C]0.458595[/C][/ROW]
[ROW][C]48[/C][C]0.129692[/C][C]0.9962[/C][C]0.161615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294050&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294050&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
10.1771661.36080.08937
2-0.044271-0.340.367514
30.1037540.79690.214339
4-0.05535-0.42510.336138
50.0156210.120.452451
6-0.097467-0.74870.228518
70.1165430.89520.187163
80.1650051.26740.104991
9-0.017081-0.13120.448031
100.156971.20570.116372
110.0829570.63720.263228
120.0105710.08120.467778
13-0.105101-0.80730.21137
140.0685880.52680.300142
15-0.125933-0.96730.16867
16-0.100987-0.77570.220512
17-0.161725-1.24220.109533
180.0919290.70610.241446
19-0.032905-0.25270.40067
20-0.075092-0.57680.283137
21-0.04937-0.37920.352943
220.0781880.60060.275211
230.0121150.09310.463087
240.0377450.28990.386444
250.0208090.15980.436778
26-0.039987-0.30710.379908
27-0.060446-0.46430.322073
280.0251910.19350.423616
29-0.132468-1.01750.156534
30-0.08868-0.68120.249216
31-0.118815-0.91260.182574
320.095270.73180.233598
33-0.053928-0.41420.340104
34-0.072978-0.56060.288612
350.0789210.60620.273353
36-0.015908-0.12220.45158
37-0.110972-0.85240.198722
38-0.124073-0.9530.172234
390.0017070.01310.494793
40-0.052103-0.40020.345223
410.0169090.12990.448553
420.1035260.79520.214843
430.0219960.1690.433207
44-0.039751-0.30530.380593
450.0695310.53410.297646
46-0.03889-0.29870.383102
47-0.013595-0.10440.458595
480.1296920.99620.161615


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 = 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)
x <- na.omit(x)
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')