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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 computationThu, 10 Mar 2016 07:54:13 +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/10/t1457596485b7nthi6swv44eh8.htm/, Retrieved Wed, 08 May 2024 22:30:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293820, Retrieved Wed, 08 May 2024 22:30:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

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] [(partial) Autocor...] [2016-03-10 07:25:19] [2067968a48489243c2d14909cd8d3ed5]
- R PD  [(Partial) Autocorrelation Function] [Autocorrelation c...] [2016-03-10 07:45:35] [2067968a48489243c2d14909cd8d3ed5]
- R P       [(Partial) Autocorrelation Function] [Autocorrelation c...] [2016-03-10 07:54:13] [4e1138fa3bff5f7fc8fdb388bb0b126b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.13
100.46
101.83
100.82
100.99
99.11
98.99
99.8
100.3
101.56
98.83
101.29
98.24
98.37
99.68
97.8
98.34
98.06
97.19
99.44
99.04
100.81
98.49
101.03
98.59
101.07
99.28
101.65
100.59
101.84
100.27
100.04
97.78
97.59
97.68
100.56
98.9
100.08
101.7
100.9
100.67
100.51
100.01
99.8
97.7
98.14
101.77
99.82
100.03
101.83
98.25
99.88
98.96
98.37
97.52
99.59
97.99
100.68
100.39
99.31
96.93
102.06
97.9
102.29
100.55
100.77
100.68
100.75
100.21
99.85
100.59
101.45

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=293820&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=293820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293820&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.629146-5.30131e-06
20.338372.85120.00285
3-0.194325-1.63740.052985
40.0832710.70170.242595
5-0.244904-2.06360.021356
60.268342.26110.01341
7-0.24203-2.03940.022567
80.1828881.5410.063876
9-0.106061-0.89370.187255
100.1441111.21430.114329
11-0.186312-1.56990.060444
120.2675122.25410.013639
13-0.271589-2.28850.012545
140.0962530.8110.210026
15-0.027813-0.23440.40769
16-0.011301-0.09520.462203
17-0.011289-0.09510.462244
180.0732990.61760.269398
19-0.037356-0.31480.376931
200.0620430.52280.301375
21-0.026416-0.22260.412248
220.0025170.02120.49157
23-0.053999-0.4550.325249
240.0659450.55570.290093
25-0.172867-1.45660.074818
260.2126171.79150.038734
27-0.122207-1.02970.153316
280.1497251.26160.10561
29-0.127416-1.07360.143312
300.118020.99450.16169
31-0.231593-1.95140.027476
320.2093531.7640.041013
33-0.190549-1.60560.056401
340.1314941.1080.135803
35-0.092317-0.77790.219612
360.1348641.13640.129808
37-0.150602-1.2690.104294
380.256572.16190.016999
39-0.241085-2.03140.022978
400.1715631.44560.076343
41-0.156228-1.31640.096136
420.1159140.97670.166015
43-0.135869-1.14480.128058
440.135211.13930.129204
45-0.052809-0.4450.328844
46-0.032226-0.27150.393381
470.0768770.64780.259609
48-0.030546-0.25740.398812

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629146 & -5.3013 & 1e-06 \tabularnewline
2 & 0.33837 & 2.8512 & 0.00285 \tabularnewline
3 & -0.194325 & -1.6374 & 0.052985 \tabularnewline
4 & 0.083271 & 0.7017 & 0.242595 \tabularnewline
5 & -0.244904 & -2.0636 & 0.021356 \tabularnewline
6 & 0.26834 & 2.2611 & 0.01341 \tabularnewline
7 & -0.24203 & -2.0394 & 0.022567 \tabularnewline
8 & 0.182888 & 1.541 & 0.063876 \tabularnewline
9 & -0.106061 & -0.8937 & 0.187255 \tabularnewline
10 & 0.144111 & 1.2143 & 0.114329 \tabularnewline
11 & -0.186312 & -1.5699 & 0.060444 \tabularnewline
12 & 0.267512 & 2.2541 & 0.013639 \tabularnewline
13 & -0.271589 & -2.2885 & 0.012545 \tabularnewline
14 & 0.096253 & 0.811 & 0.210026 \tabularnewline
15 & -0.027813 & -0.2344 & 0.40769 \tabularnewline
16 & -0.011301 & -0.0952 & 0.462203 \tabularnewline
17 & -0.011289 & -0.0951 & 0.462244 \tabularnewline
18 & 0.073299 & 0.6176 & 0.269398 \tabularnewline
19 & -0.037356 & -0.3148 & 0.376931 \tabularnewline
20 & 0.062043 & 0.5228 & 0.301375 \tabularnewline
21 & -0.026416 & -0.2226 & 0.412248 \tabularnewline
22 & 0.002517 & 0.0212 & 0.49157 \tabularnewline
23 & -0.053999 & -0.455 & 0.325249 \tabularnewline
24 & 0.065945 & 0.5557 & 0.290093 \tabularnewline
25 & -0.172867 & -1.4566 & 0.074818 \tabularnewline
26 & 0.212617 & 1.7915 & 0.038734 \tabularnewline
27 & -0.122207 & -1.0297 & 0.153316 \tabularnewline
28 & 0.149725 & 1.2616 & 0.10561 \tabularnewline
29 & -0.127416 & -1.0736 & 0.143312 \tabularnewline
30 & 0.11802 & 0.9945 & 0.16169 \tabularnewline
31 & -0.231593 & -1.9514 & 0.027476 \tabularnewline
32 & 0.209353 & 1.764 & 0.041013 \tabularnewline
33 & -0.190549 & -1.6056 & 0.056401 \tabularnewline
34 & 0.131494 & 1.108 & 0.135803 \tabularnewline
35 & -0.092317 & -0.7779 & 0.219612 \tabularnewline
36 & 0.134864 & 1.1364 & 0.129808 \tabularnewline
37 & -0.150602 & -1.269 & 0.104294 \tabularnewline
38 & 0.25657 & 2.1619 & 0.016999 \tabularnewline
39 & -0.241085 & -2.0314 & 0.022978 \tabularnewline
40 & 0.171563 & 1.4456 & 0.076343 \tabularnewline
41 & -0.156228 & -1.3164 & 0.096136 \tabularnewline
42 & 0.115914 & 0.9767 & 0.166015 \tabularnewline
43 & -0.135869 & -1.1448 & 0.128058 \tabularnewline
44 & 0.13521 & 1.1393 & 0.129204 \tabularnewline
45 & -0.052809 & -0.445 & 0.328844 \tabularnewline
46 & -0.032226 & -0.2715 & 0.393381 \tabularnewline
47 & 0.076877 & 0.6478 & 0.259609 \tabularnewline
48 & -0.030546 & -0.2574 & 0.398812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293820&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]-0.629146[/C][C]-5.3013[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.33837[/C][C]2.8512[/C][C]0.00285[/C][/ROW]
[ROW][C]3[/C][C]-0.194325[/C][C]-1.6374[/C][C]0.052985[/C][/ROW]
[ROW][C]4[/C][C]0.083271[/C][C]0.7017[/C][C]0.242595[/C][/ROW]
[ROW][C]5[/C][C]-0.244904[/C][C]-2.0636[/C][C]0.021356[/C][/ROW]
[ROW][C]6[/C][C]0.26834[/C][C]2.2611[/C][C]0.01341[/C][/ROW]
[ROW][C]7[/C][C]-0.24203[/C][C]-2.0394[/C][C]0.022567[/C][/ROW]
[ROW][C]8[/C][C]0.182888[/C][C]1.541[/C][C]0.063876[/C][/ROW]
[ROW][C]9[/C][C]-0.106061[/C][C]-0.8937[/C][C]0.187255[/C][/ROW]
[ROW][C]10[/C][C]0.144111[/C][C]1.2143[/C][C]0.114329[/C][/ROW]
[ROW][C]11[/C][C]-0.186312[/C][C]-1.5699[/C][C]0.060444[/C][/ROW]
[ROW][C]12[/C][C]0.267512[/C][C]2.2541[/C][C]0.013639[/C][/ROW]
[ROW][C]13[/C][C]-0.271589[/C][C]-2.2885[/C][C]0.012545[/C][/ROW]
[ROW][C]14[/C][C]0.096253[/C][C]0.811[/C][C]0.210026[/C][/ROW]
[ROW][C]15[/C][C]-0.027813[/C][C]-0.2344[/C][C]0.40769[/C][/ROW]
[ROW][C]16[/C][C]-0.011301[/C][C]-0.0952[/C][C]0.462203[/C][/ROW]
[ROW][C]17[/C][C]-0.011289[/C][C]-0.0951[/C][C]0.462244[/C][/ROW]
[ROW][C]18[/C][C]0.073299[/C][C]0.6176[/C][C]0.269398[/C][/ROW]
[ROW][C]19[/C][C]-0.037356[/C][C]-0.3148[/C][C]0.376931[/C][/ROW]
[ROW][C]20[/C][C]0.062043[/C][C]0.5228[/C][C]0.301375[/C][/ROW]
[ROW][C]21[/C][C]-0.026416[/C][C]-0.2226[/C][C]0.412248[/C][/ROW]
[ROW][C]22[/C][C]0.002517[/C][C]0.0212[/C][C]0.49157[/C][/ROW]
[ROW][C]23[/C][C]-0.053999[/C][C]-0.455[/C][C]0.325249[/C][/ROW]
[ROW][C]24[/C][C]0.065945[/C][C]0.5557[/C][C]0.290093[/C][/ROW]
[ROW][C]25[/C][C]-0.172867[/C][C]-1.4566[/C][C]0.074818[/C][/ROW]
[ROW][C]26[/C][C]0.212617[/C][C]1.7915[/C][C]0.038734[/C][/ROW]
[ROW][C]27[/C][C]-0.122207[/C][C]-1.0297[/C][C]0.153316[/C][/ROW]
[ROW][C]28[/C][C]0.149725[/C][C]1.2616[/C][C]0.10561[/C][/ROW]
[ROW][C]29[/C][C]-0.127416[/C][C]-1.0736[/C][C]0.143312[/C][/ROW]
[ROW][C]30[/C][C]0.11802[/C][C]0.9945[/C][C]0.16169[/C][/ROW]
[ROW][C]31[/C][C]-0.231593[/C][C]-1.9514[/C][C]0.027476[/C][/ROW]
[ROW][C]32[/C][C]0.209353[/C][C]1.764[/C][C]0.041013[/C][/ROW]
[ROW][C]33[/C][C]-0.190549[/C][C]-1.6056[/C][C]0.056401[/C][/ROW]
[ROW][C]34[/C][C]0.131494[/C][C]1.108[/C][C]0.135803[/C][/ROW]
[ROW][C]35[/C][C]-0.092317[/C][C]-0.7779[/C][C]0.219612[/C][/ROW]
[ROW][C]36[/C][C]0.134864[/C][C]1.1364[/C][C]0.129808[/C][/ROW]
[ROW][C]37[/C][C]-0.150602[/C][C]-1.269[/C][C]0.104294[/C][/ROW]
[ROW][C]38[/C][C]0.25657[/C][C]2.1619[/C][C]0.016999[/C][/ROW]
[ROW][C]39[/C][C]-0.241085[/C][C]-2.0314[/C][C]0.022978[/C][/ROW]
[ROW][C]40[/C][C]0.171563[/C][C]1.4456[/C][C]0.076343[/C][/ROW]
[ROW][C]41[/C][C]-0.156228[/C][C]-1.3164[/C][C]0.096136[/C][/ROW]
[ROW][C]42[/C][C]0.115914[/C][C]0.9767[/C][C]0.166015[/C][/ROW]
[ROW][C]43[/C][C]-0.135869[/C][C]-1.1448[/C][C]0.128058[/C][/ROW]
[ROW][C]44[/C][C]0.13521[/C][C]1.1393[/C][C]0.129204[/C][/ROW]
[ROW][C]45[/C][C]-0.052809[/C][C]-0.445[/C][C]0.328844[/C][/ROW]
[ROW][C]46[/C][C]-0.032226[/C][C]-0.2715[/C][C]0.393381[/C][/ROW]
[ROW][C]47[/C][C]0.076877[/C][C]0.6478[/C][C]0.259609[/C][/ROW]
[ROW][C]48[/C][C]-0.030546[/C][C]-0.2574[/C][C]0.398812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293820&T=1

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


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.629146-5.30131e-06
20.338372.85120.00285
3-0.194325-1.63740.052985
40.0832710.70170.242595
5-0.244904-2.06360.021356
60.268342.26110.01341
7-0.24203-2.03940.022567
80.1828881.5410.063876
9-0.106061-0.89370.187255
100.1441111.21430.114329
11-0.186312-1.56990.060444
120.2675122.25410.013639
13-0.271589-2.28850.012545
140.0962530.8110.210026
15-0.027813-0.23440.40769
16-0.011301-0.09520.462203
17-0.011289-0.09510.462244
180.0732990.61760.269398
19-0.037356-0.31480.376931
200.0620430.52280.301375
21-0.026416-0.22260.412248
220.0025170.02120.49157
23-0.053999-0.4550.325249
240.0659450.55570.290093
25-0.172867-1.45660.074818
260.2126171.79150.038734
27-0.122207-1.02970.153316
280.1497251.26160.10561
29-0.127416-1.07360.143312
300.118020.99450.16169
31-0.231593-1.95140.027476
320.2093531.7640.041013
33-0.190549-1.60560.056401
340.1314941.1080.135803
35-0.092317-0.77790.219612
360.1348641.13640.129808
37-0.150602-1.2690.104294
380.256572.16190.016999
39-0.241085-2.03140.022978
400.1715631.44560.076343
41-0.156228-1.31640.096136
420.1159140.97670.166015
43-0.135869-1.14480.128058
440.135211.13930.129204
45-0.052809-0.4450.328844
46-0.032226-0.27150.393381
470.0768770.64780.259609
48-0.030546-0.25740.398812






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.629146-5.30131e-06
2-0.095096-0.80130.212818
3-0.035118-0.29590.384082
4-0.055175-0.46490.32171
5-0.371479-3.13010.001268
6-0.087701-0.7390.231177
7-0.091295-0.76930.222144
8-0.087387-0.73630.231975
9-0.112921-0.95150.172293
100.0248010.2090.417532
11-0.09397-0.79180.215557
120.1050.88470.18964
13-0.011861-0.09990.460334
14-0.210618-1.77470.040117
15-0.069103-0.58230.281114
16-0.064078-0.53990.295466
17-0.043421-0.36590.357774
18-0.119504-1.0070.158686
19-0.029014-0.24450.403784
200.0524510.4420.329929
210.0283680.2390.405886
22-0.019649-0.16560.434484
23-0.051958-0.43780.331429
240.0306330.25810.398533
25-0.167506-1.41140.081243
260.0490720.41350.340247
270.0265880.2240.411688
280.1482171.24890.107902
29-0.00203-0.01710.493201
300.0099960.08420.466555
31-0.17543-1.47820.071888
32-0.039619-0.33380.369745
330.0014320.01210.495203
34-0.081471-0.68650.247321
35-0.103401-0.87130.193271
36-0.053759-0.4530.325971
37-0.001913-0.01610.493592
380.0732450.61720.269548
39-0.018418-0.15520.438554
40-0.021372-0.18010.428801
410.0116880.09850.460911
420.0736420.62050.268452
430.0480490.40490.343395
44-0.041766-0.35190.362967
450.0994360.83790.20246
46-0.08177-0.6890.246534
47-0.033697-0.28390.388642
48-0.007118-0.060.476171

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629146 & -5.3013 & 1e-06 \tabularnewline
2 & -0.095096 & -0.8013 & 0.212818 \tabularnewline
3 & -0.035118 & -0.2959 & 0.384082 \tabularnewline
4 & -0.055175 & -0.4649 & 0.32171 \tabularnewline
5 & -0.371479 & -3.1301 & 0.001268 \tabularnewline
6 & -0.087701 & -0.739 & 0.231177 \tabularnewline
7 & -0.091295 & -0.7693 & 0.222144 \tabularnewline
8 & -0.087387 & -0.7363 & 0.231975 \tabularnewline
9 & -0.112921 & -0.9515 & 0.172293 \tabularnewline
10 & 0.024801 & 0.209 & 0.417532 \tabularnewline
11 & -0.09397 & -0.7918 & 0.215557 \tabularnewline
12 & 0.105 & 0.8847 & 0.18964 \tabularnewline
13 & -0.011861 & -0.0999 & 0.460334 \tabularnewline
14 & -0.210618 & -1.7747 & 0.040117 \tabularnewline
15 & -0.069103 & -0.5823 & 0.281114 \tabularnewline
16 & -0.064078 & -0.5399 & 0.295466 \tabularnewline
17 & -0.043421 & -0.3659 & 0.357774 \tabularnewline
18 & -0.119504 & -1.007 & 0.158686 \tabularnewline
19 & -0.029014 & -0.2445 & 0.403784 \tabularnewline
20 & 0.052451 & 0.442 & 0.329929 \tabularnewline
21 & 0.028368 & 0.239 & 0.405886 \tabularnewline
22 & -0.019649 & -0.1656 & 0.434484 \tabularnewline
23 & -0.051958 & -0.4378 & 0.331429 \tabularnewline
24 & 0.030633 & 0.2581 & 0.398533 \tabularnewline
25 & -0.167506 & -1.4114 & 0.081243 \tabularnewline
26 & 0.049072 & 0.4135 & 0.340247 \tabularnewline
27 & 0.026588 & 0.224 & 0.411688 \tabularnewline
28 & 0.148217 & 1.2489 & 0.107902 \tabularnewline
29 & -0.00203 & -0.0171 & 0.493201 \tabularnewline
30 & 0.009996 & 0.0842 & 0.466555 \tabularnewline
31 & -0.17543 & -1.4782 & 0.071888 \tabularnewline
32 & -0.039619 & -0.3338 & 0.369745 \tabularnewline
33 & 0.001432 & 0.0121 & 0.495203 \tabularnewline
34 & -0.081471 & -0.6865 & 0.247321 \tabularnewline
35 & -0.103401 & -0.8713 & 0.193271 \tabularnewline
36 & -0.053759 & -0.453 & 0.325971 \tabularnewline
37 & -0.001913 & -0.0161 & 0.493592 \tabularnewline
38 & 0.073245 & 0.6172 & 0.269548 \tabularnewline
39 & -0.018418 & -0.1552 & 0.438554 \tabularnewline
40 & -0.021372 & -0.1801 & 0.428801 \tabularnewline
41 & 0.011688 & 0.0985 & 0.460911 \tabularnewline
42 & 0.073642 & 0.6205 & 0.268452 \tabularnewline
43 & 0.048049 & 0.4049 & 0.343395 \tabularnewline
44 & -0.041766 & -0.3519 & 0.362967 \tabularnewline
45 & 0.099436 & 0.8379 & 0.20246 \tabularnewline
46 & -0.08177 & -0.689 & 0.246534 \tabularnewline
47 & -0.033697 & -0.2839 & 0.388642 \tabularnewline
48 & -0.007118 & -0.06 & 0.476171 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293820&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]-0.629146[/C][C]-5.3013[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.095096[/C][C]-0.8013[/C][C]0.212818[/C][/ROW]
[ROW][C]3[/C][C]-0.035118[/C][C]-0.2959[/C][C]0.384082[/C][/ROW]
[ROW][C]4[/C][C]-0.055175[/C][C]-0.4649[/C][C]0.32171[/C][/ROW]
[ROW][C]5[/C][C]-0.371479[/C][C]-3.1301[/C][C]0.001268[/C][/ROW]
[ROW][C]6[/C][C]-0.087701[/C][C]-0.739[/C][C]0.231177[/C][/ROW]
[ROW][C]7[/C][C]-0.091295[/C][C]-0.7693[/C][C]0.222144[/C][/ROW]
[ROW][C]8[/C][C]-0.087387[/C][C]-0.7363[/C][C]0.231975[/C][/ROW]
[ROW][C]9[/C][C]-0.112921[/C][C]-0.9515[/C][C]0.172293[/C][/ROW]
[ROW][C]10[/C][C]0.024801[/C][C]0.209[/C][C]0.417532[/C][/ROW]
[ROW][C]11[/C][C]-0.09397[/C][C]-0.7918[/C][C]0.215557[/C][/ROW]
[ROW][C]12[/C][C]0.105[/C][C]0.8847[/C][C]0.18964[/C][/ROW]
[ROW][C]13[/C][C]-0.011861[/C][C]-0.0999[/C][C]0.460334[/C][/ROW]
[ROW][C]14[/C][C]-0.210618[/C][C]-1.7747[/C][C]0.040117[/C][/ROW]
[ROW][C]15[/C][C]-0.069103[/C][C]-0.5823[/C][C]0.281114[/C][/ROW]
[ROW][C]16[/C][C]-0.064078[/C][C]-0.5399[/C][C]0.295466[/C][/ROW]
[ROW][C]17[/C][C]-0.043421[/C][C]-0.3659[/C][C]0.357774[/C][/ROW]
[ROW][C]18[/C][C]-0.119504[/C][C]-1.007[/C][C]0.158686[/C][/ROW]
[ROW][C]19[/C][C]-0.029014[/C][C]-0.2445[/C][C]0.403784[/C][/ROW]
[ROW][C]20[/C][C]0.052451[/C][C]0.442[/C][C]0.329929[/C][/ROW]
[ROW][C]21[/C][C]0.028368[/C][C]0.239[/C][C]0.405886[/C][/ROW]
[ROW][C]22[/C][C]-0.019649[/C][C]-0.1656[/C][C]0.434484[/C][/ROW]
[ROW][C]23[/C][C]-0.051958[/C][C]-0.4378[/C][C]0.331429[/C][/ROW]
[ROW][C]24[/C][C]0.030633[/C][C]0.2581[/C][C]0.398533[/C][/ROW]
[ROW][C]25[/C][C]-0.167506[/C][C]-1.4114[/C][C]0.081243[/C][/ROW]
[ROW][C]26[/C][C]0.049072[/C][C]0.4135[/C][C]0.340247[/C][/ROW]
[ROW][C]27[/C][C]0.026588[/C][C]0.224[/C][C]0.411688[/C][/ROW]
[ROW][C]28[/C][C]0.148217[/C][C]1.2489[/C][C]0.107902[/C][/ROW]
[ROW][C]29[/C][C]-0.00203[/C][C]-0.0171[/C][C]0.493201[/C][/ROW]
[ROW][C]30[/C][C]0.009996[/C][C]0.0842[/C][C]0.466555[/C][/ROW]
[ROW][C]31[/C][C]-0.17543[/C][C]-1.4782[/C][C]0.071888[/C][/ROW]
[ROW][C]32[/C][C]-0.039619[/C][C]-0.3338[/C][C]0.369745[/C][/ROW]
[ROW][C]33[/C][C]0.001432[/C][C]0.0121[/C][C]0.495203[/C][/ROW]
[ROW][C]34[/C][C]-0.081471[/C][C]-0.6865[/C][C]0.247321[/C][/ROW]
[ROW][C]35[/C][C]-0.103401[/C][C]-0.8713[/C][C]0.193271[/C][/ROW]
[ROW][C]36[/C][C]-0.053759[/C][C]-0.453[/C][C]0.325971[/C][/ROW]
[ROW][C]37[/C][C]-0.001913[/C][C]-0.0161[/C][C]0.493592[/C][/ROW]
[ROW][C]38[/C][C]0.073245[/C][C]0.6172[/C][C]0.269548[/C][/ROW]
[ROW][C]39[/C][C]-0.018418[/C][C]-0.1552[/C][C]0.438554[/C][/ROW]
[ROW][C]40[/C][C]-0.021372[/C][C]-0.1801[/C][C]0.428801[/C][/ROW]
[ROW][C]41[/C][C]0.011688[/C][C]0.0985[/C][C]0.460911[/C][/ROW]
[ROW][C]42[/C][C]0.073642[/C][C]0.6205[/C][C]0.268452[/C][/ROW]
[ROW][C]43[/C][C]0.048049[/C][C]0.4049[/C][C]0.343395[/C][/ROW]
[ROW][C]44[/C][C]-0.041766[/C][C]-0.3519[/C][C]0.362967[/C][/ROW]
[ROW][C]45[/C][C]0.099436[/C][C]0.8379[/C][C]0.20246[/C][/ROW]
[ROW][C]46[/C][C]-0.08177[/C][C]-0.689[/C][C]0.246534[/C][/ROW]
[ROW][C]47[/C][C]-0.033697[/C][C]-0.2839[/C][C]0.388642[/C][/ROW]
[ROW][C]48[/C][C]-0.007118[/C][C]-0.06[/C][C]0.476171[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293820&T=2

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


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.629146-5.30131e-06
2-0.095096-0.80130.212818
3-0.035118-0.29590.384082
4-0.055175-0.46490.32171
5-0.371479-3.13010.001268
6-0.087701-0.7390.231177
7-0.091295-0.76930.222144
8-0.087387-0.73630.231975
9-0.112921-0.95150.172293
100.0248010.2090.417532
11-0.09397-0.79180.215557
120.1050.88470.18964
13-0.011861-0.09990.460334
14-0.210618-1.77470.040117
15-0.069103-0.58230.281114
16-0.064078-0.53990.295466
17-0.043421-0.36590.357774
18-0.119504-1.0070.158686
19-0.029014-0.24450.403784
200.0524510.4420.329929
210.0283680.2390.405886
22-0.019649-0.16560.434484
23-0.051958-0.43780.331429
240.0306330.25810.398533
25-0.167506-1.41140.081243
260.0490720.41350.340247
270.0265880.2240.411688
280.1482171.24890.107902
29-0.00203-0.01710.493201
300.0099960.08420.466555
31-0.17543-1.47820.071888
32-0.039619-0.33380.369745
330.0014320.01210.495203
34-0.081471-0.68650.247321
35-0.103401-0.87130.193271
36-0.053759-0.4530.325971
37-0.001913-0.01610.493592
380.0732450.61720.269548
39-0.018418-0.15520.438554
40-0.021372-0.18010.428801
410.0116880.09850.460911
420.0736420.62050.268452
430.0480490.40490.343395
44-0.041766-0.35190.362967
450.0994360.83790.20246
46-0.08177-0.6890.246534
47-0.033697-0.28390.388642
48-0.007118-0.060.476171


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')