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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 18 Dec 2016 15:27:42 +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/2016/Dec/18/t1482071362qfsa7yuo6ugjxr1.htm/, Retrieved Wed, 08 May 2024 13:19:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301107, Retrieved Wed, 08 May 2024 13:19:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301107&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301107&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.329667-3.64132e-04
2-0.233695-2.58120.005514
3-0.040611-0.44860.32727
40.1918332.11890.018065
5-0.131633-1.45390.074266
60.046740.51630.303302
70.040590.44830.327354
8-0.092242-1.01890.155145
9-0.061492-0.67920.249149
100.3013853.32890.000577
110.03690.40760.342151
12-0.503051-5.55640
130.1291521.42650.078135
140.1992732.2010.014808
150.076210.84180.200783
16-0.193095-2.13280.017472
170.079980.88340.189375
18-0.082413-0.91030.182234
190.066410.73350.232325
200.050460.55730.289157
210.0676290.7470.228253
22-0.250947-2.77180.003225
230.1377511.52150.06536
240.0135180.14930.440776
250.0516590.57060.284663
26-0.114415-1.26380.104364
27-0.020842-0.23020.409158
280.0688990.7610.224058
290.0541190.59780.275554
30-0.020923-0.23110.408811
31-0.055354-0.61140.271036
320.0061270.06770.473076
33-0.093485-1.03260.151924
340.1033391.14140.127965
350.0565780.62490.266593
36-0.023394-0.25840.39827
37-0.050444-0.55720.289215
380.0036770.04060.483836
390.0836080.92350.178789
40-0.072615-0.80210.212039
41-0.084875-0.93750.175183
420.1279291.4130.080097
43-0.038134-0.42120.337172
44-0.046755-0.51640.303247
450.1365091.50780.067097
46-0.014784-0.16330.435277
47-0.194338-2.14650.016905
480.0984791.08770.139429

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.329667 & -3.6413 & 2e-04 \tabularnewline
2 & -0.233695 & -2.5812 & 0.005514 \tabularnewline
3 & -0.040611 & -0.4486 & 0.32727 \tabularnewline
4 & 0.191833 & 2.1189 & 0.018065 \tabularnewline
5 & -0.131633 & -1.4539 & 0.074266 \tabularnewline
6 & 0.04674 & 0.5163 & 0.303302 \tabularnewline
7 & 0.04059 & 0.4483 & 0.327354 \tabularnewline
8 & -0.092242 & -1.0189 & 0.155145 \tabularnewline
9 & -0.061492 & -0.6792 & 0.249149 \tabularnewline
10 & 0.301385 & 3.3289 & 0.000577 \tabularnewline
11 & 0.0369 & 0.4076 & 0.342151 \tabularnewline
12 & -0.503051 & -5.5564 & 0 \tabularnewline
13 & 0.129152 & 1.4265 & 0.078135 \tabularnewline
14 & 0.199273 & 2.201 & 0.014808 \tabularnewline
15 & 0.07621 & 0.8418 & 0.200783 \tabularnewline
16 & -0.193095 & -2.1328 & 0.017472 \tabularnewline
17 & 0.07998 & 0.8834 & 0.189375 \tabularnewline
18 & -0.082413 & -0.9103 & 0.182234 \tabularnewline
19 & 0.06641 & 0.7335 & 0.232325 \tabularnewline
20 & 0.05046 & 0.5573 & 0.289157 \tabularnewline
21 & 0.067629 & 0.747 & 0.228253 \tabularnewline
22 & -0.250947 & -2.7718 & 0.003225 \tabularnewline
23 & 0.137751 & 1.5215 & 0.06536 \tabularnewline
24 & 0.013518 & 0.1493 & 0.440776 \tabularnewline
25 & 0.051659 & 0.5706 & 0.284663 \tabularnewline
26 & -0.114415 & -1.2638 & 0.104364 \tabularnewline
27 & -0.020842 & -0.2302 & 0.409158 \tabularnewline
28 & 0.068899 & 0.761 & 0.224058 \tabularnewline
29 & 0.054119 & 0.5978 & 0.275554 \tabularnewline
30 & -0.020923 & -0.2311 & 0.408811 \tabularnewline
31 & -0.055354 & -0.6114 & 0.271036 \tabularnewline
32 & 0.006127 & 0.0677 & 0.473076 \tabularnewline
33 & -0.093485 & -1.0326 & 0.151924 \tabularnewline
34 & 0.103339 & 1.1414 & 0.127965 \tabularnewline
35 & 0.056578 & 0.6249 & 0.266593 \tabularnewline
36 & -0.023394 & -0.2584 & 0.39827 \tabularnewline
37 & -0.050444 & -0.5572 & 0.289215 \tabularnewline
38 & 0.003677 & 0.0406 & 0.483836 \tabularnewline
39 & 0.083608 & 0.9235 & 0.178789 \tabularnewline
40 & -0.072615 & -0.8021 & 0.212039 \tabularnewline
41 & -0.084875 & -0.9375 & 0.175183 \tabularnewline
42 & 0.127929 & 1.413 & 0.080097 \tabularnewline
43 & -0.038134 & -0.4212 & 0.337172 \tabularnewline
44 & -0.046755 & -0.5164 & 0.303247 \tabularnewline
45 & 0.136509 & 1.5078 & 0.067097 \tabularnewline
46 & -0.014784 & -0.1633 & 0.435277 \tabularnewline
47 & -0.194338 & -2.1465 & 0.016905 \tabularnewline
48 & 0.098479 & 1.0877 & 0.139429 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301107&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]-0.329667[/C][C]-3.6413[/C][C]2e-04[/C][/ROW]
[ROW][C]2[/C][C]-0.233695[/C][C]-2.5812[/C][C]0.005514[/C][/ROW]
[ROW][C]3[/C][C]-0.040611[/C][C]-0.4486[/C][C]0.32727[/C][/ROW]
[ROW][C]4[/C][C]0.191833[/C][C]2.1189[/C][C]0.018065[/C][/ROW]
[ROW][C]5[/C][C]-0.131633[/C][C]-1.4539[/C][C]0.074266[/C][/ROW]
[ROW][C]6[/C][C]0.04674[/C][C]0.5163[/C][C]0.303302[/C][/ROW]
[ROW][C]7[/C][C]0.04059[/C][C]0.4483[/C][C]0.327354[/C][/ROW]
[ROW][C]8[/C][C]-0.092242[/C][C]-1.0189[/C][C]0.155145[/C][/ROW]
[ROW][C]9[/C][C]-0.061492[/C][C]-0.6792[/C][C]0.249149[/C][/ROW]
[ROW][C]10[/C][C]0.301385[/C][C]3.3289[/C][C]0.000577[/C][/ROW]
[ROW][C]11[/C][C]0.0369[/C][C]0.4076[/C][C]0.342151[/C][/ROW]
[ROW][C]12[/C][C]-0.503051[/C][C]-5.5564[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.129152[/C][C]1.4265[/C][C]0.078135[/C][/ROW]
[ROW][C]14[/C][C]0.199273[/C][C]2.201[/C][C]0.014808[/C][/ROW]
[ROW][C]15[/C][C]0.07621[/C][C]0.8418[/C][C]0.200783[/C][/ROW]
[ROW][C]16[/C][C]-0.193095[/C][C]-2.1328[/C][C]0.017472[/C][/ROW]
[ROW][C]17[/C][C]0.07998[/C][C]0.8834[/C][C]0.189375[/C][/ROW]
[ROW][C]18[/C][C]-0.082413[/C][C]-0.9103[/C][C]0.182234[/C][/ROW]
[ROW][C]19[/C][C]0.06641[/C][C]0.7335[/C][C]0.232325[/C][/ROW]
[ROW][C]20[/C][C]0.05046[/C][C]0.5573[/C][C]0.289157[/C][/ROW]
[ROW][C]21[/C][C]0.067629[/C][C]0.747[/C][C]0.228253[/C][/ROW]
[ROW][C]22[/C][C]-0.250947[/C][C]-2.7718[/C][C]0.003225[/C][/ROW]
[ROW][C]23[/C][C]0.137751[/C][C]1.5215[/C][C]0.06536[/C][/ROW]
[ROW][C]24[/C][C]0.013518[/C][C]0.1493[/C][C]0.440776[/C][/ROW]
[ROW][C]25[/C][C]0.051659[/C][C]0.5706[/C][C]0.284663[/C][/ROW]
[ROW][C]26[/C][C]-0.114415[/C][C]-1.2638[/C][C]0.104364[/C][/ROW]
[ROW][C]27[/C][C]-0.020842[/C][C]-0.2302[/C][C]0.409158[/C][/ROW]
[ROW][C]28[/C][C]0.068899[/C][C]0.761[/C][C]0.224058[/C][/ROW]
[ROW][C]29[/C][C]0.054119[/C][C]0.5978[/C][C]0.275554[/C][/ROW]
[ROW][C]30[/C][C]-0.020923[/C][C]-0.2311[/C][C]0.408811[/C][/ROW]
[ROW][C]31[/C][C]-0.055354[/C][C]-0.6114[/C][C]0.271036[/C][/ROW]
[ROW][C]32[/C][C]0.006127[/C][C]0.0677[/C][C]0.473076[/C][/ROW]
[ROW][C]33[/C][C]-0.093485[/C][C]-1.0326[/C][C]0.151924[/C][/ROW]
[ROW][C]34[/C][C]0.103339[/C][C]1.1414[/C][C]0.127965[/C][/ROW]
[ROW][C]35[/C][C]0.056578[/C][C]0.6249[/C][C]0.266593[/C][/ROW]
[ROW][C]36[/C][C]-0.023394[/C][C]-0.2584[/C][C]0.39827[/C][/ROW]
[ROW][C]37[/C][C]-0.050444[/C][C]-0.5572[/C][C]0.289215[/C][/ROW]
[ROW][C]38[/C][C]0.003677[/C][C]0.0406[/C][C]0.483836[/C][/ROW]
[ROW][C]39[/C][C]0.083608[/C][C]0.9235[/C][C]0.178789[/C][/ROW]
[ROW][C]40[/C][C]-0.072615[/C][C]-0.8021[/C][C]0.212039[/C][/ROW]
[ROW][C]41[/C][C]-0.084875[/C][C]-0.9375[/C][C]0.175183[/C][/ROW]
[ROW][C]42[/C][C]0.127929[/C][C]1.413[/C][C]0.080097[/C][/ROW]
[ROW][C]43[/C][C]-0.038134[/C][C]-0.4212[/C][C]0.337172[/C][/ROW]
[ROW][C]44[/C][C]-0.046755[/C][C]-0.5164[/C][C]0.303247[/C][/ROW]
[ROW][C]45[/C][C]0.136509[/C][C]1.5078[/C][C]0.067097[/C][/ROW]
[ROW][C]46[/C][C]-0.014784[/C][C]-0.1633[/C][C]0.435277[/C][/ROW]
[ROW][C]47[/C][C]-0.194338[/C][C]-2.1465[/C][C]0.016905[/C][/ROW]
[ROW][C]48[/C][C]0.098479[/C][C]1.0877[/C][C]0.139429[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301107&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
1-0.329667-3.64132e-04
2-0.233695-2.58120.005514
3-0.040611-0.44860.32727
40.1918332.11890.018065
5-0.131633-1.45390.074266
60.046740.51630.303302
70.040590.44830.327354
8-0.092242-1.01890.155145
9-0.061492-0.67920.249149
100.3013853.32890.000577
110.03690.40760.342151
12-0.503051-5.55640
130.1291521.42650.078135
140.1992732.2010.014808
150.076210.84180.200783
16-0.193095-2.13280.017472
170.079980.88340.189375
18-0.082413-0.91030.182234
190.066410.73350.232325
200.050460.55730.289157
210.0676290.7470.228253
22-0.250947-2.77180.003225
230.1377511.52150.06536
240.0135180.14930.440776
250.0516590.57060.284663
26-0.114415-1.26380.104364
27-0.020842-0.23020.409158
280.0688990.7610.224058
290.0541190.59780.275554
30-0.020923-0.23110.408811
31-0.055354-0.61140.271036
320.0061270.06770.473076
33-0.093485-1.03260.151924
340.1033391.14140.127965
350.0565780.62490.266593
36-0.023394-0.25840.39827
37-0.050444-0.55720.289215
380.0036770.04060.483836
390.0836080.92350.178789
40-0.072615-0.80210.212039
41-0.084875-0.93750.175183
420.1279291.4130.080097
43-0.038134-0.42120.337172
44-0.046755-0.51640.303247
450.1365091.50780.067097
46-0.014784-0.16330.435277
47-0.194338-2.14650.016905
480.0984791.08770.139429






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.329667-3.64132e-04
2-0.384121-4.24282.2e-05
3-0.360458-3.98145.8e-05
4-0.120039-1.32590.093679
5-0.268106-2.96130.001841
6-0.135666-1.49850.068296
7-0.071103-0.78540.216883
8-0.20054-2.2150.014307
9-0.266962-2.94870.001913
100.1048711.15830.124494
110.3286373.62990.000208
12-0.247191-2.73030.003632
13-0.196001-2.16490.016171
14-0.205025-2.26460.012652
15-0.030116-0.33260.369988
16-0.072454-0.80030.212552
17-0.090122-0.99540.16075
18-0.210632-2.32650.01082
19-0.098934-1.09280.138327
20-0.07276-0.80370.211579
210.004850.05360.478682
220.0476510.52630.299811
230.325493.59520.000234
24-0.098409-1.0870.139599
25-0.157317-1.73760.042401
26-0.094721-1.04620.148762
27-0.060876-0.67240.251302
28-0.003439-0.0380.484882
290.0248520.27450.392082
30-0.124077-1.37050.086528
31-0.110928-1.22520.111422
320.1093481.20780.114732
33-0.084396-0.93220.176542
34-0.141198-1.55960.060724
350.1872282.0680.020377
36-0.099741-1.10170.136386
37-0.05751-0.63520.263236
38-0.126441-1.39660.082537
390.0574430.63450.263479
400.0006220.00690.497264
41-0.060662-0.670.252051
42-0.039103-0.43190.333287
43-0.073042-0.80680.210684
44-0.033859-0.3740.354532
450.0254560.28120.389526
46-0.006889-0.07610.469735
470.0153320.16930.432903
480.0855380.94480.173315

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.329667 & -3.6413 & 2e-04 \tabularnewline
2 & -0.384121 & -4.2428 & 2.2e-05 \tabularnewline
3 & -0.360458 & -3.9814 & 5.8e-05 \tabularnewline
4 & -0.120039 & -1.3259 & 0.093679 \tabularnewline
5 & -0.268106 & -2.9613 & 0.001841 \tabularnewline
6 & -0.135666 & -1.4985 & 0.068296 \tabularnewline
7 & -0.071103 & -0.7854 & 0.216883 \tabularnewline
8 & -0.20054 & -2.215 & 0.014307 \tabularnewline
9 & -0.266962 & -2.9487 & 0.001913 \tabularnewline
10 & 0.104871 & 1.1583 & 0.124494 \tabularnewline
11 & 0.328637 & 3.6299 & 0.000208 \tabularnewline
12 & -0.247191 & -2.7303 & 0.003632 \tabularnewline
13 & -0.196001 & -2.1649 & 0.016171 \tabularnewline
14 & -0.205025 & -2.2646 & 0.012652 \tabularnewline
15 & -0.030116 & -0.3326 & 0.369988 \tabularnewline
16 & -0.072454 & -0.8003 & 0.212552 \tabularnewline
17 & -0.090122 & -0.9954 & 0.16075 \tabularnewline
18 & -0.210632 & -2.3265 & 0.01082 \tabularnewline
19 & -0.098934 & -1.0928 & 0.138327 \tabularnewline
20 & -0.07276 & -0.8037 & 0.211579 \tabularnewline
21 & 0.00485 & 0.0536 & 0.478682 \tabularnewline
22 & 0.047651 & 0.5263 & 0.299811 \tabularnewline
23 & 0.32549 & 3.5952 & 0.000234 \tabularnewline
24 & -0.098409 & -1.087 & 0.139599 \tabularnewline
25 & -0.157317 & -1.7376 & 0.042401 \tabularnewline
26 & -0.094721 & -1.0462 & 0.148762 \tabularnewline
27 & -0.060876 & -0.6724 & 0.251302 \tabularnewline
28 & -0.003439 & -0.038 & 0.484882 \tabularnewline
29 & 0.024852 & 0.2745 & 0.392082 \tabularnewline
30 & -0.124077 & -1.3705 & 0.086528 \tabularnewline
31 & -0.110928 & -1.2252 & 0.111422 \tabularnewline
32 & 0.109348 & 1.2078 & 0.114732 \tabularnewline
33 & -0.084396 & -0.9322 & 0.176542 \tabularnewline
34 & -0.141198 & -1.5596 & 0.060724 \tabularnewline
35 & 0.187228 & 2.068 & 0.020377 \tabularnewline
36 & -0.099741 & -1.1017 & 0.136386 \tabularnewline
37 & -0.05751 & -0.6352 & 0.263236 \tabularnewline
38 & -0.126441 & -1.3966 & 0.082537 \tabularnewline
39 & 0.057443 & 0.6345 & 0.263479 \tabularnewline
40 & 0.000622 & 0.0069 & 0.497264 \tabularnewline
41 & -0.060662 & -0.67 & 0.252051 \tabularnewline
42 & -0.039103 & -0.4319 & 0.333287 \tabularnewline
43 & -0.073042 & -0.8068 & 0.210684 \tabularnewline
44 & -0.033859 & -0.374 & 0.354532 \tabularnewline
45 & 0.025456 & 0.2812 & 0.389526 \tabularnewline
46 & -0.006889 & -0.0761 & 0.469735 \tabularnewline
47 & 0.015332 & 0.1693 & 0.432903 \tabularnewline
48 & 0.085538 & 0.9448 & 0.173315 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301107&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]-0.329667[/C][C]-3.6413[/C][C]2e-04[/C][/ROW]
[ROW][C]2[/C][C]-0.384121[/C][C]-4.2428[/C][C]2.2e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.360458[/C][C]-3.9814[/C][C]5.8e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.120039[/C][C]-1.3259[/C][C]0.093679[/C][/ROW]
[ROW][C]5[/C][C]-0.268106[/C][C]-2.9613[/C][C]0.001841[/C][/ROW]
[ROW][C]6[/C][C]-0.135666[/C][C]-1.4985[/C][C]0.068296[/C][/ROW]
[ROW][C]7[/C][C]-0.071103[/C][C]-0.7854[/C][C]0.216883[/C][/ROW]
[ROW][C]8[/C][C]-0.20054[/C][C]-2.215[/C][C]0.014307[/C][/ROW]
[ROW][C]9[/C][C]-0.266962[/C][C]-2.9487[/C][C]0.001913[/C][/ROW]
[ROW][C]10[/C][C]0.104871[/C][C]1.1583[/C][C]0.124494[/C][/ROW]
[ROW][C]11[/C][C]0.328637[/C][C]3.6299[/C][C]0.000208[/C][/ROW]
[ROW][C]12[/C][C]-0.247191[/C][C]-2.7303[/C][C]0.003632[/C][/ROW]
[ROW][C]13[/C][C]-0.196001[/C][C]-2.1649[/C][C]0.016171[/C][/ROW]
[ROW][C]14[/C][C]-0.205025[/C][C]-2.2646[/C][C]0.012652[/C][/ROW]
[ROW][C]15[/C][C]-0.030116[/C][C]-0.3326[/C][C]0.369988[/C][/ROW]
[ROW][C]16[/C][C]-0.072454[/C][C]-0.8003[/C][C]0.212552[/C][/ROW]
[ROW][C]17[/C][C]-0.090122[/C][C]-0.9954[/C][C]0.16075[/C][/ROW]
[ROW][C]18[/C][C]-0.210632[/C][C]-2.3265[/C][C]0.01082[/C][/ROW]
[ROW][C]19[/C][C]-0.098934[/C][C]-1.0928[/C][C]0.138327[/C][/ROW]
[ROW][C]20[/C][C]-0.07276[/C][C]-0.8037[/C][C]0.211579[/C][/ROW]
[ROW][C]21[/C][C]0.00485[/C][C]0.0536[/C][C]0.478682[/C][/ROW]
[ROW][C]22[/C][C]0.047651[/C][C]0.5263[/C][C]0.299811[/C][/ROW]
[ROW][C]23[/C][C]0.32549[/C][C]3.5952[/C][C]0.000234[/C][/ROW]
[ROW][C]24[/C][C]-0.098409[/C][C]-1.087[/C][C]0.139599[/C][/ROW]
[ROW][C]25[/C][C]-0.157317[/C][C]-1.7376[/C][C]0.042401[/C][/ROW]
[ROW][C]26[/C][C]-0.094721[/C][C]-1.0462[/C][C]0.148762[/C][/ROW]
[ROW][C]27[/C][C]-0.060876[/C][C]-0.6724[/C][C]0.251302[/C][/ROW]
[ROW][C]28[/C][C]-0.003439[/C][C]-0.038[/C][C]0.484882[/C][/ROW]
[ROW][C]29[/C][C]0.024852[/C][C]0.2745[/C][C]0.392082[/C][/ROW]
[ROW][C]30[/C][C]-0.124077[/C][C]-1.3705[/C][C]0.086528[/C][/ROW]
[ROW][C]31[/C][C]-0.110928[/C][C]-1.2252[/C][C]0.111422[/C][/ROW]
[ROW][C]32[/C][C]0.109348[/C][C]1.2078[/C][C]0.114732[/C][/ROW]
[ROW][C]33[/C][C]-0.084396[/C][C]-0.9322[/C][C]0.176542[/C][/ROW]
[ROW][C]34[/C][C]-0.141198[/C][C]-1.5596[/C][C]0.060724[/C][/ROW]
[ROW][C]35[/C][C]0.187228[/C][C]2.068[/C][C]0.020377[/C][/ROW]
[ROW][C]36[/C][C]-0.099741[/C][C]-1.1017[/C][C]0.136386[/C][/ROW]
[ROW][C]37[/C][C]-0.05751[/C][C]-0.6352[/C][C]0.263236[/C][/ROW]
[ROW][C]38[/C][C]-0.126441[/C][C]-1.3966[/C][C]0.082537[/C][/ROW]
[ROW][C]39[/C][C]0.057443[/C][C]0.6345[/C][C]0.263479[/C][/ROW]
[ROW][C]40[/C][C]0.000622[/C][C]0.0069[/C][C]0.497264[/C][/ROW]
[ROW][C]41[/C][C]-0.060662[/C][C]-0.67[/C][C]0.252051[/C][/ROW]
[ROW][C]42[/C][C]-0.039103[/C][C]-0.4319[/C][C]0.333287[/C][/ROW]
[ROW][C]43[/C][C]-0.073042[/C][C]-0.8068[/C][C]0.210684[/C][/ROW]
[ROW][C]44[/C][C]-0.033859[/C][C]-0.374[/C][C]0.354532[/C][/ROW]
[ROW][C]45[/C][C]0.025456[/C][C]0.2812[/C][C]0.389526[/C][/ROW]
[ROW][C]46[/C][C]-0.006889[/C][C]-0.0761[/C][C]0.469735[/C][/ROW]
[ROW][C]47[/C][C]0.015332[/C][C]0.1693[/C][C]0.432903[/C][/ROW]
[ROW][C]48[/C][C]0.085538[/C][C]0.9448[/C][C]0.173315[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301107&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301107&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
1-0.329667-3.64132e-04
2-0.384121-4.24282.2e-05
3-0.360458-3.98145.8e-05
4-0.120039-1.32590.093679
5-0.268106-2.96130.001841
6-0.135666-1.49850.068296
7-0.071103-0.78540.216883
8-0.20054-2.2150.014307
9-0.266962-2.94870.001913
100.1048711.15830.124494
110.3286373.62990.000208
12-0.247191-2.73030.003632
13-0.196001-2.16490.016171
14-0.205025-2.26460.012652
15-0.030116-0.33260.369988
16-0.072454-0.80030.212552
17-0.090122-0.99540.16075
18-0.210632-2.32650.01082
19-0.098934-1.09280.138327
20-0.07276-0.80370.211579
210.004850.05360.478682
220.0476510.52630.299811
230.325493.59520.000234
24-0.098409-1.0870.139599
25-0.157317-1.73760.042401
26-0.094721-1.04620.148762
27-0.060876-0.67240.251302
28-0.003439-0.0380.484882
290.0248520.27450.392082
30-0.124077-1.37050.086528
31-0.110928-1.22520.111422
320.1093481.20780.114732
33-0.084396-0.93220.176542
34-0.141198-1.55960.060724
350.1872282.0680.020377
36-0.099741-1.10170.136386
37-0.05751-0.63520.263236
38-0.126441-1.39660.082537
390.0574430.63450.263479
400.0006220.00690.497264
41-0.060662-0.670.252051
42-0.039103-0.43190.333287
43-0.073042-0.80680.210684
44-0.033859-0.3740.354532
450.0254560.28120.389526
46-0.006889-0.07610.469735
470.0153320.16930.432903
480.0855380.94480.173315


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 = 1 ; 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,'ACF(k)',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,'PACF(k)',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')