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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, 11 Jan 2016 20:35:52 +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/Jan/11/t1452544588i13pc5sydoir0fm.htm/, Retrieved Fri, 17 May 2024 01:43:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289705, Retrieved Fri, 17 May 2024 01:43:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55

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] [] [2016-01-11 20:35:52] [d1a83db1c928d515dd26931964d56abe] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90.65
90.93
91.42
91.52
91.76
91.47
91.37
91.35
91.74
91.78
91.88
91.99
92.55
92.94
92.81
93.35
93.72
93.94
94.03
93.66
93.78
94.1
94.85
94.83
95.06
95.87
95.97
95.96
96.3
96.17
96.18
96.55
96.76
97.63
97.86
97.82
98.62
99.24
99.63
100.27
100.84
101.05
100.38
100.02
99.97
99.95
100
100.04
100.51
100.29
100.22
101.29
100.29
100.26
100.39
99.3
98.9
98.76
99.12
99.28

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 Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289705&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289705&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289705&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 Ronald Aylmer Fisher' @ fisher.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1069590.82160.207316
20.0153290.11770.453334
30.2681082.05940.02194
4-0.102687-0.78880.216707
5-0.030938-0.23760.406492
6-0.084389-0.64820.259683
7-0.008751-0.06720.473319
80.0269510.2070.418356
9-0.037855-0.29080.386123
100.0830020.63750.263117
110.0891780.6850.248017
120.1226620.94220.17497
130.1098510.84380.2011
140.0865280.66460.254436
150.0372640.28620.387853
16-0.201667-1.5490.063361
17-0.149694-1.14980.127428
18-0.04623-0.35510.361891
19-0.236994-1.82040.036887
20-0.045386-0.34860.364308
21-0.051653-0.39680.34649
22-0.11918-0.91540.181844
230.1039340.79830.21394
24-0.001312-0.01010.495996
250.0427540.32840.371886
260.115440.88670.189417
27-0.13728-1.05450.147984
28-0.054683-0.420.337995
290.0505180.3880.349692
30-0.177364-1.36240.089132
31-0.108381-0.83250.204245
32-0.064008-0.49170.312395
33-0.024597-0.18890.425396
34-0.089612-0.68830.246973
350.0053420.0410.483703
360.1395331.07180.144094
370.0124020.09530.462214
380.0922690.70870.24064
39-0.009495-0.07290.471054
40-0.128186-0.98460.164418
41-0.035943-0.27610.391723
42-0.044253-0.33990.367563
43-0.023794-0.18280.427804
44-0.055139-0.42350.336724
45-0.00794-0.0610.475787
460.0270080.20750.418185
470.0344540.26460.396103
48-0.010516-0.08080.467947

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.106959 & 0.8216 & 0.207316 \tabularnewline
2 & 0.015329 & 0.1177 & 0.453334 \tabularnewline
3 & 0.268108 & 2.0594 & 0.02194 \tabularnewline
4 & -0.102687 & -0.7888 & 0.216707 \tabularnewline
5 & -0.030938 & -0.2376 & 0.406492 \tabularnewline
6 & -0.084389 & -0.6482 & 0.259683 \tabularnewline
7 & -0.008751 & -0.0672 & 0.473319 \tabularnewline
8 & 0.026951 & 0.207 & 0.418356 \tabularnewline
9 & -0.037855 & -0.2908 & 0.386123 \tabularnewline
10 & 0.083002 & 0.6375 & 0.263117 \tabularnewline
11 & 0.089178 & 0.685 & 0.248017 \tabularnewline
12 & 0.122662 & 0.9422 & 0.17497 \tabularnewline
13 & 0.109851 & 0.8438 & 0.2011 \tabularnewline
14 & 0.086528 & 0.6646 & 0.254436 \tabularnewline
15 & 0.037264 & 0.2862 & 0.387853 \tabularnewline
16 & -0.201667 & -1.549 & 0.063361 \tabularnewline
17 & -0.149694 & -1.1498 & 0.127428 \tabularnewline
18 & -0.04623 & -0.3551 & 0.361891 \tabularnewline
19 & -0.236994 & -1.8204 & 0.036887 \tabularnewline
20 & -0.045386 & -0.3486 & 0.364308 \tabularnewline
21 & -0.051653 & -0.3968 & 0.34649 \tabularnewline
22 & -0.11918 & -0.9154 & 0.181844 \tabularnewline
23 & 0.103934 & 0.7983 & 0.21394 \tabularnewline
24 & -0.001312 & -0.0101 & 0.495996 \tabularnewline
25 & 0.042754 & 0.3284 & 0.371886 \tabularnewline
26 & 0.11544 & 0.8867 & 0.189417 \tabularnewline
27 & -0.13728 & -1.0545 & 0.147984 \tabularnewline
28 & -0.054683 & -0.42 & 0.337995 \tabularnewline
29 & 0.050518 & 0.388 & 0.349692 \tabularnewline
30 & -0.177364 & -1.3624 & 0.089132 \tabularnewline
31 & -0.108381 & -0.8325 & 0.204245 \tabularnewline
32 & -0.064008 & -0.4917 & 0.312395 \tabularnewline
33 & -0.024597 & -0.1889 & 0.425396 \tabularnewline
34 & -0.089612 & -0.6883 & 0.246973 \tabularnewline
35 & 0.005342 & 0.041 & 0.483703 \tabularnewline
36 & 0.139533 & 1.0718 & 0.144094 \tabularnewline
37 & 0.012402 & 0.0953 & 0.462214 \tabularnewline
38 & 0.092269 & 0.7087 & 0.24064 \tabularnewline
39 & -0.009495 & -0.0729 & 0.471054 \tabularnewline
40 & -0.128186 & -0.9846 & 0.164418 \tabularnewline
41 & -0.035943 & -0.2761 & 0.391723 \tabularnewline
42 & -0.044253 & -0.3399 & 0.367563 \tabularnewline
43 & -0.023794 & -0.1828 & 0.427804 \tabularnewline
44 & -0.055139 & -0.4235 & 0.336724 \tabularnewline
45 & -0.00794 & -0.061 & 0.475787 \tabularnewline
46 & 0.027008 & 0.2075 & 0.418185 \tabularnewline
47 & 0.034454 & 0.2646 & 0.396103 \tabularnewline
48 & -0.010516 & -0.0808 & 0.467947 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289705&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]0.106959[/C][C]0.8216[/C][C]0.207316[/C][/ROW]
[ROW][C]2[/C][C]0.015329[/C][C]0.1177[/C][C]0.453334[/C][/ROW]
[ROW][C]3[/C][C]0.268108[/C][C]2.0594[/C][C]0.02194[/C][/ROW]
[ROW][C]4[/C][C]-0.102687[/C][C]-0.7888[/C][C]0.216707[/C][/ROW]
[ROW][C]5[/C][C]-0.030938[/C][C]-0.2376[/C][C]0.406492[/C][/ROW]
[ROW][C]6[/C][C]-0.084389[/C][C]-0.6482[/C][C]0.259683[/C][/ROW]
[ROW][C]7[/C][C]-0.008751[/C][C]-0.0672[/C][C]0.473319[/C][/ROW]
[ROW][C]8[/C][C]0.026951[/C][C]0.207[/C][C]0.418356[/C][/ROW]
[ROW][C]9[/C][C]-0.037855[/C][C]-0.2908[/C][C]0.386123[/C][/ROW]
[ROW][C]10[/C][C]0.083002[/C][C]0.6375[/C][C]0.263117[/C][/ROW]
[ROW][C]11[/C][C]0.089178[/C][C]0.685[/C][C]0.248017[/C][/ROW]
[ROW][C]12[/C][C]0.122662[/C][C]0.9422[/C][C]0.17497[/C][/ROW]
[ROW][C]13[/C][C]0.109851[/C][C]0.8438[/C][C]0.2011[/C][/ROW]
[ROW][C]14[/C][C]0.086528[/C][C]0.6646[/C][C]0.254436[/C][/ROW]
[ROW][C]15[/C][C]0.037264[/C][C]0.2862[/C][C]0.387853[/C][/ROW]
[ROW][C]16[/C][C]-0.201667[/C][C]-1.549[/C][C]0.063361[/C][/ROW]
[ROW][C]17[/C][C]-0.149694[/C][C]-1.1498[/C][C]0.127428[/C][/ROW]
[ROW][C]18[/C][C]-0.04623[/C][C]-0.3551[/C][C]0.361891[/C][/ROW]
[ROW][C]19[/C][C]-0.236994[/C][C]-1.8204[/C][C]0.036887[/C][/ROW]
[ROW][C]20[/C][C]-0.045386[/C][C]-0.3486[/C][C]0.364308[/C][/ROW]
[ROW][C]21[/C][C]-0.051653[/C][C]-0.3968[/C][C]0.34649[/C][/ROW]
[ROW][C]22[/C][C]-0.11918[/C][C]-0.9154[/C][C]0.181844[/C][/ROW]
[ROW][C]23[/C][C]0.103934[/C][C]0.7983[/C][C]0.21394[/C][/ROW]
[ROW][C]24[/C][C]-0.001312[/C][C]-0.0101[/C][C]0.495996[/C][/ROW]
[ROW][C]25[/C][C]0.042754[/C][C]0.3284[/C][C]0.371886[/C][/ROW]
[ROW][C]26[/C][C]0.11544[/C][C]0.8867[/C][C]0.189417[/C][/ROW]
[ROW][C]27[/C][C]-0.13728[/C][C]-1.0545[/C][C]0.147984[/C][/ROW]
[ROW][C]28[/C][C]-0.054683[/C][C]-0.42[/C][C]0.337995[/C][/ROW]
[ROW][C]29[/C][C]0.050518[/C][C]0.388[/C][C]0.349692[/C][/ROW]
[ROW][C]30[/C][C]-0.177364[/C][C]-1.3624[/C][C]0.089132[/C][/ROW]
[ROW][C]31[/C][C]-0.108381[/C][C]-0.8325[/C][C]0.204245[/C][/ROW]
[ROW][C]32[/C][C]-0.064008[/C][C]-0.4917[/C][C]0.312395[/C][/ROW]
[ROW][C]33[/C][C]-0.024597[/C][C]-0.1889[/C][C]0.425396[/C][/ROW]
[ROW][C]34[/C][C]-0.089612[/C][C]-0.6883[/C][C]0.246973[/C][/ROW]
[ROW][C]35[/C][C]0.005342[/C][C]0.041[/C][C]0.483703[/C][/ROW]
[ROW][C]36[/C][C]0.139533[/C][C]1.0718[/C][C]0.144094[/C][/ROW]
[ROW][C]37[/C][C]0.012402[/C][C]0.0953[/C][C]0.462214[/C][/ROW]
[ROW][C]38[/C][C]0.092269[/C][C]0.7087[/C][C]0.24064[/C][/ROW]
[ROW][C]39[/C][C]-0.009495[/C][C]-0.0729[/C][C]0.471054[/C][/ROW]
[ROW][C]40[/C][C]-0.128186[/C][C]-0.9846[/C][C]0.164418[/C][/ROW]
[ROW][C]41[/C][C]-0.035943[/C][C]-0.2761[/C][C]0.391723[/C][/ROW]
[ROW][C]42[/C][C]-0.044253[/C][C]-0.3399[/C][C]0.367563[/C][/ROW]
[ROW][C]43[/C][C]-0.023794[/C][C]-0.1828[/C][C]0.427804[/C][/ROW]
[ROW][C]44[/C][C]-0.055139[/C][C]-0.4235[/C][C]0.336724[/C][/ROW]
[ROW][C]45[/C][C]-0.00794[/C][C]-0.061[/C][C]0.475787[/C][/ROW]
[ROW][C]46[/C][C]0.027008[/C][C]0.2075[/C][C]0.418185[/C][/ROW]
[ROW][C]47[/C][C]0.034454[/C][C]0.2646[/C][C]0.396103[/C][/ROW]
[ROW][C]48[/C][C]-0.010516[/C][C]-0.0808[/C][C]0.467947[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289705&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289705&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
10.1069590.82160.207316
20.0153290.11770.453334
30.2681082.05940.02194
4-0.102687-0.78880.216707
5-0.030938-0.23760.406492
6-0.084389-0.64820.259683
7-0.008751-0.06720.473319
80.0269510.2070.418356
9-0.037855-0.29080.386123
100.0830020.63750.263117
110.0891780.6850.248017
120.1226620.94220.17497
130.1098510.84380.2011
140.0865280.66460.254436
150.0372640.28620.387853
16-0.201667-1.5490.063361
17-0.149694-1.14980.127428
18-0.04623-0.35510.361891
19-0.236994-1.82040.036887
20-0.045386-0.34860.364308
21-0.051653-0.39680.34649
22-0.11918-0.91540.181844
230.1039340.79830.21394
24-0.001312-0.01010.495996
250.0427540.32840.371886
260.115440.88670.189417
27-0.13728-1.05450.147984
28-0.054683-0.420.337995
290.0505180.3880.349692
30-0.177364-1.36240.089132
31-0.108381-0.83250.204245
32-0.064008-0.49170.312395
33-0.024597-0.18890.425396
34-0.089612-0.68830.246973
350.0053420.0410.483703
360.1395331.07180.144094
370.0124020.09530.462214
380.0922690.70870.24064
39-0.009495-0.07290.471054
40-0.128186-0.98460.164418
41-0.035943-0.27610.391723
42-0.044253-0.33990.367563
43-0.023794-0.18280.427804
44-0.055139-0.42350.336724
45-0.00794-0.0610.475787
460.0270080.20750.418185
470.0344540.26460.396103
48-0.010516-0.08080.467947






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1069590.82160.207316
20.0039340.03020.487997
30.2691372.06730.021552
4-0.173811-1.33510.093492
50.0074970.05760.477138
6-0.177795-1.36570.088613
70.1208530.92830.178521
8-0.011741-0.09020.464223
90.0440190.33810.368237
100.0207670.15950.436903
110.0852730.6550.257509
120.1115620.85690.197476
130.0583630.44830.32779
140.0546760.420.338014
15-0.042373-0.32550.372988
16-0.231666-1.77950.040157
17-0.12589-0.9670.16875
180.0052650.04040.48394
19-0.124546-0.95670.171322
200.0391890.3010.38223
21-0.129157-0.99210.162606
22-0.064428-0.49490.31126
230.0552210.42420.336496
240.0180890.13890.444983
250.0389180.29890.38302
260.0540310.4150.339815
27-0.155021-1.19070.119263
28-0.008947-0.06870.47272
290.1586121.21830.113975
30-0.043013-0.33040.371138
31-0.018319-0.14070.44429
32-0.149547-1.14870.127659
330.0392530.30150.382043
34-0.113363-0.87080.193708
350.08640.66360.25475
360.0113620.08730.465375
370.0023190.01780.492924
38-0.049361-0.37910.35297
39-0.068004-0.52240.301691
40-0.121946-0.93670.176369
41-0.011381-0.08740.465317
420.1282320.9850.164331
43-0.040857-0.31380.377378
44-0.048264-0.37070.356085
450.0452740.34780.364631
46-0.00825-0.06340.474843
470.0742850.57060.285222
48-0.070413-0.54090.295324

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.106959 & 0.8216 & 0.207316 \tabularnewline
2 & 0.003934 & 0.0302 & 0.487997 \tabularnewline
3 & 0.269137 & 2.0673 & 0.021552 \tabularnewline
4 & -0.173811 & -1.3351 & 0.093492 \tabularnewline
5 & 0.007497 & 0.0576 & 0.477138 \tabularnewline
6 & -0.177795 & -1.3657 & 0.088613 \tabularnewline
7 & 0.120853 & 0.9283 & 0.178521 \tabularnewline
8 & -0.011741 & -0.0902 & 0.464223 \tabularnewline
9 & 0.044019 & 0.3381 & 0.368237 \tabularnewline
10 & 0.020767 & 0.1595 & 0.436903 \tabularnewline
11 & 0.085273 & 0.655 & 0.257509 \tabularnewline
12 & 0.111562 & 0.8569 & 0.197476 \tabularnewline
13 & 0.058363 & 0.4483 & 0.32779 \tabularnewline
14 & 0.054676 & 0.42 & 0.338014 \tabularnewline
15 & -0.042373 & -0.3255 & 0.372988 \tabularnewline
16 & -0.231666 & -1.7795 & 0.040157 \tabularnewline
17 & -0.12589 & -0.967 & 0.16875 \tabularnewline
18 & 0.005265 & 0.0404 & 0.48394 \tabularnewline
19 & -0.124546 & -0.9567 & 0.171322 \tabularnewline
20 & 0.039189 & 0.301 & 0.38223 \tabularnewline
21 & -0.129157 & -0.9921 & 0.162606 \tabularnewline
22 & -0.064428 & -0.4949 & 0.31126 \tabularnewline
23 & 0.055221 & 0.4242 & 0.336496 \tabularnewline
24 & 0.018089 & 0.1389 & 0.444983 \tabularnewline
25 & 0.038918 & 0.2989 & 0.38302 \tabularnewline
26 & 0.054031 & 0.415 & 0.339815 \tabularnewline
27 & -0.155021 & -1.1907 & 0.119263 \tabularnewline
28 & -0.008947 & -0.0687 & 0.47272 \tabularnewline
29 & 0.158612 & 1.2183 & 0.113975 \tabularnewline
30 & -0.043013 & -0.3304 & 0.371138 \tabularnewline
31 & -0.018319 & -0.1407 & 0.44429 \tabularnewline
32 & -0.149547 & -1.1487 & 0.127659 \tabularnewline
33 & 0.039253 & 0.3015 & 0.382043 \tabularnewline
34 & -0.113363 & -0.8708 & 0.193708 \tabularnewline
35 & 0.0864 & 0.6636 & 0.25475 \tabularnewline
36 & 0.011362 & 0.0873 & 0.465375 \tabularnewline
37 & 0.002319 & 0.0178 & 0.492924 \tabularnewline
38 & -0.049361 & -0.3791 & 0.35297 \tabularnewline
39 & -0.068004 & -0.5224 & 0.301691 \tabularnewline
40 & -0.121946 & -0.9367 & 0.176369 \tabularnewline
41 & -0.011381 & -0.0874 & 0.465317 \tabularnewline
42 & 0.128232 & 0.985 & 0.164331 \tabularnewline
43 & -0.040857 & -0.3138 & 0.377378 \tabularnewline
44 & -0.048264 & -0.3707 & 0.356085 \tabularnewline
45 & 0.045274 & 0.3478 & 0.364631 \tabularnewline
46 & -0.00825 & -0.0634 & 0.474843 \tabularnewline
47 & 0.074285 & 0.5706 & 0.285222 \tabularnewline
48 & -0.070413 & -0.5409 & 0.295324 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289705&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]0.106959[/C][C]0.8216[/C][C]0.207316[/C][/ROW]
[ROW][C]2[/C][C]0.003934[/C][C]0.0302[/C][C]0.487997[/C][/ROW]
[ROW][C]3[/C][C]0.269137[/C][C]2.0673[/C][C]0.021552[/C][/ROW]
[ROW][C]4[/C][C]-0.173811[/C][C]-1.3351[/C][C]0.093492[/C][/ROW]
[ROW][C]5[/C][C]0.007497[/C][C]0.0576[/C][C]0.477138[/C][/ROW]
[ROW][C]6[/C][C]-0.177795[/C][C]-1.3657[/C][C]0.088613[/C][/ROW]
[ROW][C]7[/C][C]0.120853[/C][C]0.9283[/C][C]0.178521[/C][/ROW]
[ROW][C]8[/C][C]-0.011741[/C][C]-0.0902[/C][C]0.464223[/C][/ROW]
[ROW][C]9[/C][C]0.044019[/C][C]0.3381[/C][C]0.368237[/C][/ROW]
[ROW][C]10[/C][C]0.020767[/C][C]0.1595[/C][C]0.436903[/C][/ROW]
[ROW][C]11[/C][C]0.085273[/C][C]0.655[/C][C]0.257509[/C][/ROW]
[ROW][C]12[/C][C]0.111562[/C][C]0.8569[/C][C]0.197476[/C][/ROW]
[ROW][C]13[/C][C]0.058363[/C][C]0.4483[/C][C]0.32779[/C][/ROW]
[ROW][C]14[/C][C]0.054676[/C][C]0.42[/C][C]0.338014[/C][/ROW]
[ROW][C]15[/C][C]-0.042373[/C][C]-0.3255[/C][C]0.372988[/C][/ROW]
[ROW][C]16[/C][C]-0.231666[/C][C]-1.7795[/C][C]0.040157[/C][/ROW]
[ROW][C]17[/C][C]-0.12589[/C][C]-0.967[/C][C]0.16875[/C][/ROW]
[ROW][C]18[/C][C]0.005265[/C][C]0.0404[/C][C]0.48394[/C][/ROW]
[ROW][C]19[/C][C]-0.124546[/C][C]-0.9567[/C][C]0.171322[/C][/ROW]
[ROW][C]20[/C][C]0.039189[/C][C]0.301[/C][C]0.38223[/C][/ROW]
[ROW][C]21[/C][C]-0.129157[/C][C]-0.9921[/C][C]0.162606[/C][/ROW]
[ROW][C]22[/C][C]-0.064428[/C][C]-0.4949[/C][C]0.31126[/C][/ROW]
[ROW][C]23[/C][C]0.055221[/C][C]0.4242[/C][C]0.336496[/C][/ROW]
[ROW][C]24[/C][C]0.018089[/C][C]0.1389[/C][C]0.444983[/C][/ROW]
[ROW][C]25[/C][C]0.038918[/C][C]0.2989[/C][C]0.38302[/C][/ROW]
[ROW][C]26[/C][C]0.054031[/C][C]0.415[/C][C]0.339815[/C][/ROW]
[ROW][C]27[/C][C]-0.155021[/C][C]-1.1907[/C][C]0.119263[/C][/ROW]
[ROW][C]28[/C][C]-0.008947[/C][C]-0.0687[/C][C]0.47272[/C][/ROW]
[ROW][C]29[/C][C]0.158612[/C][C]1.2183[/C][C]0.113975[/C][/ROW]
[ROW][C]30[/C][C]-0.043013[/C][C]-0.3304[/C][C]0.371138[/C][/ROW]
[ROW][C]31[/C][C]-0.018319[/C][C]-0.1407[/C][C]0.44429[/C][/ROW]
[ROW][C]32[/C][C]-0.149547[/C][C]-1.1487[/C][C]0.127659[/C][/ROW]
[ROW][C]33[/C][C]0.039253[/C][C]0.3015[/C][C]0.382043[/C][/ROW]
[ROW][C]34[/C][C]-0.113363[/C][C]-0.8708[/C][C]0.193708[/C][/ROW]
[ROW][C]35[/C][C]0.0864[/C][C]0.6636[/C][C]0.25475[/C][/ROW]
[ROW][C]36[/C][C]0.011362[/C][C]0.0873[/C][C]0.465375[/C][/ROW]
[ROW][C]37[/C][C]0.002319[/C][C]0.0178[/C][C]0.492924[/C][/ROW]
[ROW][C]38[/C][C]-0.049361[/C][C]-0.3791[/C][C]0.35297[/C][/ROW]
[ROW][C]39[/C][C]-0.068004[/C][C]-0.5224[/C][C]0.301691[/C][/ROW]
[ROW][C]40[/C][C]-0.121946[/C][C]-0.9367[/C][C]0.176369[/C][/ROW]
[ROW][C]41[/C][C]-0.011381[/C][C]-0.0874[/C][C]0.465317[/C][/ROW]
[ROW][C]42[/C][C]0.128232[/C][C]0.985[/C][C]0.164331[/C][/ROW]
[ROW][C]43[/C][C]-0.040857[/C][C]-0.3138[/C][C]0.377378[/C][/ROW]
[ROW][C]44[/C][C]-0.048264[/C][C]-0.3707[/C][C]0.356085[/C][/ROW]
[ROW][C]45[/C][C]0.045274[/C][C]0.3478[/C][C]0.364631[/C][/ROW]
[ROW][C]46[/C][C]-0.00825[/C][C]-0.0634[/C][C]0.474843[/C][/ROW]
[ROW][C]47[/C][C]0.074285[/C][C]0.5706[/C][C]0.285222[/C][/ROW]
[ROW][C]48[/C][C]-0.070413[/C][C]-0.5409[/C][C]0.295324[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289705&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289705&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
10.1069590.82160.207316
20.0039340.03020.487997
30.2691372.06730.021552
4-0.173811-1.33510.093492
50.0074970.05760.477138
6-0.177795-1.36570.088613
70.1208530.92830.178521
8-0.011741-0.09020.464223
90.0440190.33810.368237
100.0207670.15950.436903
110.0852730.6550.257509
120.1115620.85690.197476
130.0583630.44830.32779
140.0546760.420.338014
15-0.042373-0.32550.372988
16-0.231666-1.77950.040157
17-0.12589-0.9670.16875
180.0052650.04040.48394
19-0.124546-0.95670.171322
200.0391890.3010.38223
21-0.129157-0.99210.162606
22-0.064428-0.49490.31126
230.0552210.42420.336496
240.0180890.13890.444983
250.0389180.29890.38302
260.0540310.4150.339815
27-0.155021-1.19070.119263
28-0.008947-0.06870.47272
290.1586121.21830.113975
30-0.043013-0.33040.371138
31-0.018319-0.14070.44429
32-0.149547-1.14870.127659
330.0392530.30150.382043
34-0.113363-0.87080.193708
350.08640.66360.25475
360.0113620.08730.465375
370.0023190.01780.492924
38-0.049361-0.37910.35297
39-0.068004-0.52240.301691
40-0.121946-0.93670.176369
41-0.011381-0.08740.465317
420.1282320.9850.164331
43-0.040857-0.31380.377378
44-0.048264-0.37070.356085
450.0452740.34780.364631
46-0.00825-0.06340.474843
470.0742850.57060.285222
48-0.070413-0.54090.295324


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')