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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 computationWed, 25 Nov 2009 14:12:55 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/25/t12591841849ogxzxfai7b4s2e.htm/, Retrieved Tue, 07 May 2024 13:50:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59648, Retrieved Tue, 07 May 2024 13:50:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [WS8 d=1 D=1] [2009-11-25 16:19:15] [445b292c553470d9fed8bc2796fd3a00]
-   PD            [(Partial) Autocorrelation Function] [ws 8 d=2 D=1] [2009-11-25 21:12:55] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
-   P               [(Partial) Autocorrelation Function] [wsact d=2 D=0] [2009-11-25 22:00:58] [134dc66689e3d457a82860db6471d419]
-   PD                [(Partial) Autocorrelation Function] [WS8 ACF d=2 D=0] [2009-11-26 21:14:29] [3425351e86519d261a643e224a0c8ee1]
-   P                 [(Partial) Autocorrelation Function] [ws 9 acf] [2009-12-04 18:58:49] [134dc66689e3d457a82860db6471d419]
-   P                   [(Partial) Autocorrelation Function] [] [2009-12-11 13:52:45] [8d2349dc1d6314bc274adc9ad027c980]
-   P               [(Partial) Autocorrelation Function] [WS 8: review2 blog1] [2009-12-04 14:29:50] [b97b96148b0223bc16666763988dc147]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.01
103.84
104.48
95.43
104.80
108.64
105.65
108.42
115.35
113.64
115.24
100.33
101.29
104.48
99.26
100.11
103.52
101.18
96.39
97.56
96.39
85.10
79.77
79.13
80.84
82.75
92.55
96.60
96.92
95.32
98.52
100.22
104.91
103.10
97.13
103.42
111.72
118.11
111.62
100.22
102.03
105.76
107.68
110.77
105.44
112.26
114.07
117.90
124.72
126.42
134.73
135.79
143.36
140.37
144.74
151.98
150.92
163.38
154.43
146.66
157.95
162.10
180.42
179.57
171.58
185.43
190.64
203.00
202.36
193.41
186.17
192.24
209.60
206.41
209.82
230.37
235.80
232.07
244.64
242.19
217.48
209.39
211.73
221.00
203.11
214.71
224.19
238.04
238.36
246.24
259.87
249.97
266.48
282.98
306.31
301.73
314.62
332.62
355.51
370.32
408.13
433.58
440.51
386.29
342.84
254.97
203.42
170.09
174.03
167.85
177.01
188.19
211.20
240.91
230.26
251.25
241.66

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59648&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59648&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59648&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.321274-3.26060.000754
2-0.031363-0.31830.375451
3-0.108156-1.09770.137456
40.1410221.43120.077697
5-0.124603-1.26460.104437
6-0.089813-0.91150.18208
70.1496331.51860.065962
80.0658250.6680.252798
9-0.148699-1.50910.067163
100.0039940.04050.483873
110.2047882.07840.02008
12-0.279131-2.83290.002775
13-0.106308-1.07890.141575
140.0110860.11250.455319
150.2595232.63390.004871
16-0.168189-1.70690.045424
170.0303570.30810.379317
18-0.027652-0.28060.389775
190.0920110.93380.176293
20-0.15566-1.57980.058612
210.1318431.33810.091912
220.0030980.03140.487491
23-0.021554-0.21880.413638
24-0.123081-1.24910.107224
250.138181.40240.081905
260.0985160.99980.159869
27-0.092048-0.93420.176197
28-0.016183-0.16420.434933
29-0.053125-0.53920.29547
300.1147711.16480.123396
31-0.087845-0.89150.18736
320.0436230.44270.329447
330.0066450.06740.47318
34-0.084479-0.85740.196615
350.0687180.69740.243559
36-0.010339-0.10490.458317

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.321274 & -3.2606 & 0.000754 \tabularnewline
2 & -0.031363 & -0.3183 & 0.375451 \tabularnewline
3 & -0.108156 & -1.0977 & 0.137456 \tabularnewline
4 & 0.141022 & 1.4312 & 0.077697 \tabularnewline
5 & -0.124603 & -1.2646 & 0.104437 \tabularnewline
6 & -0.089813 & -0.9115 & 0.18208 \tabularnewline
7 & 0.149633 & 1.5186 & 0.065962 \tabularnewline
8 & 0.065825 & 0.668 & 0.252798 \tabularnewline
9 & -0.148699 & -1.5091 & 0.067163 \tabularnewline
10 & 0.003994 & 0.0405 & 0.483873 \tabularnewline
11 & 0.204788 & 2.0784 & 0.02008 \tabularnewline
12 & -0.279131 & -2.8329 & 0.002775 \tabularnewline
13 & -0.106308 & -1.0789 & 0.141575 \tabularnewline
14 & 0.011086 & 0.1125 & 0.455319 \tabularnewline
15 & 0.259523 & 2.6339 & 0.004871 \tabularnewline
16 & -0.168189 & -1.7069 & 0.045424 \tabularnewline
17 & 0.030357 & 0.3081 & 0.379317 \tabularnewline
18 & -0.027652 & -0.2806 & 0.389775 \tabularnewline
19 & 0.092011 & 0.9338 & 0.176293 \tabularnewline
20 & -0.15566 & -1.5798 & 0.058612 \tabularnewline
21 & 0.131843 & 1.3381 & 0.091912 \tabularnewline
22 & 0.003098 & 0.0314 & 0.487491 \tabularnewline
23 & -0.021554 & -0.2188 & 0.413638 \tabularnewline
24 & -0.123081 & -1.2491 & 0.107224 \tabularnewline
25 & 0.13818 & 1.4024 & 0.081905 \tabularnewline
26 & 0.098516 & 0.9998 & 0.159869 \tabularnewline
27 & -0.092048 & -0.9342 & 0.176197 \tabularnewline
28 & -0.016183 & -0.1642 & 0.434933 \tabularnewline
29 & -0.053125 & -0.5392 & 0.29547 \tabularnewline
30 & 0.114771 & 1.1648 & 0.123396 \tabularnewline
31 & -0.087845 & -0.8915 & 0.18736 \tabularnewline
32 & 0.043623 & 0.4427 & 0.329447 \tabularnewline
33 & 0.006645 & 0.0674 & 0.47318 \tabularnewline
34 & -0.084479 & -0.8574 & 0.196615 \tabularnewline
35 & 0.068718 & 0.6974 & 0.243559 \tabularnewline
36 & -0.010339 & -0.1049 & 0.458317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59648&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]-0.321274[/C][C]-3.2606[/C][C]0.000754[/C][/ROW]
[ROW][C]2[/C][C]-0.031363[/C][C]-0.3183[/C][C]0.375451[/C][/ROW]
[ROW][C]3[/C][C]-0.108156[/C][C]-1.0977[/C][C]0.137456[/C][/ROW]
[ROW][C]4[/C][C]0.141022[/C][C]1.4312[/C][C]0.077697[/C][/ROW]
[ROW][C]5[/C][C]-0.124603[/C][C]-1.2646[/C][C]0.104437[/C][/ROW]
[ROW][C]6[/C][C]-0.089813[/C][C]-0.9115[/C][C]0.18208[/C][/ROW]
[ROW][C]7[/C][C]0.149633[/C][C]1.5186[/C][C]0.065962[/C][/ROW]
[ROW][C]8[/C][C]0.065825[/C][C]0.668[/C][C]0.252798[/C][/ROW]
[ROW][C]9[/C][C]-0.148699[/C][C]-1.5091[/C][C]0.067163[/C][/ROW]
[ROW][C]10[/C][C]0.003994[/C][C]0.0405[/C][C]0.483873[/C][/ROW]
[ROW][C]11[/C][C]0.204788[/C][C]2.0784[/C][C]0.02008[/C][/ROW]
[ROW][C]12[/C][C]-0.279131[/C][C]-2.8329[/C][C]0.002775[/C][/ROW]
[ROW][C]13[/C][C]-0.106308[/C][C]-1.0789[/C][C]0.141575[/C][/ROW]
[ROW][C]14[/C][C]0.011086[/C][C]0.1125[/C][C]0.455319[/C][/ROW]
[ROW][C]15[/C][C]0.259523[/C][C]2.6339[/C][C]0.004871[/C][/ROW]
[ROW][C]16[/C][C]-0.168189[/C][C]-1.7069[/C][C]0.045424[/C][/ROW]
[ROW][C]17[/C][C]0.030357[/C][C]0.3081[/C][C]0.379317[/C][/ROW]
[ROW][C]18[/C][C]-0.027652[/C][C]-0.2806[/C][C]0.389775[/C][/ROW]
[ROW][C]19[/C][C]0.092011[/C][C]0.9338[/C][C]0.176293[/C][/ROW]
[ROW][C]20[/C][C]-0.15566[/C][C]-1.5798[/C][C]0.058612[/C][/ROW]
[ROW][C]21[/C][C]0.131843[/C][C]1.3381[/C][C]0.091912[/C][/ROW]
[ROW][C]22[/C][C]0.003098[/C][C]0.0314[/C][C]0.487491[/C][/ROW]
[ROW][C]23[/C][C]-0.021554[/C][C]-0.2188[/C][C]0.413638[/C][/ROW]
[ROW][C]24[/C][C]-0.123081[/C][C]-1.2491[/C][C]0.107224[/C][/ROW]
[ROW][C]25[/C][C]0.13818[/C][C]1.4024[/C][C]0.081905[/C][/ROW]
[ROW][C]26[/C][C]0.098516[/C][C]0.9998[/C][C]0.159869[/C][/ROW]
[ROW][C]27[/C][C]-0.092048[/C][C]-0.9342[/C][C]0.176197[/C][/ROW]
[ROW][C]28[/C][C]-0.016183[/C][C]-0.1642[/C][C]0.434933[/C][/ROW]
[ROW][C]29[/C][C]-0.053125[/C][C]-0.5392[/C][C]0.29547[/C][/ROW]
[ROW][C]30[/C][C]0.114771[/C][C]1.1648[/C][C]0.123396[/C][/ROW]
[ROW][C]31[/C][C]-0.087845[/C][C]-0.8915[/C][C]0.18736[/C][/ROW]
[ROW][C]32[/C][C]0.043623[/C][C]0.4427[/C][C]0.329447[/C][/ROW]
[ROW][C]33[/C][C]0.006645[/C][C]0.0674[/C][C]0.47318[/C][/ROW]
[ROW][C]34[/C][C]-0.084479[/C][C]-0.8574[/C][C]0.196615[/C][/ROW]
[ROW][C]35[/C][C]0.068718[/C][C]0.6974[/C][C]0.243559[/C][/ROW]
[ROW][C]36[/C][C]-0.010339[/C][C]-0.1049[/C][C]0.458317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59648&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59648&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
1-0.321274-3.26060.000754
2-0.031363-0.31830.375451
3-0.108156-1.09770.137456
40.1410221.43120.077697
5-0.124603-1.26460.104437
6-0.089813-0.91150.18208
70.1496331.51860.065962
80.0658250.6680.252798
9-0.148699-1.50910.067163
100.0039940.04050.483873
110.2047882.07840.02008
12-0.279131-2.83290.002775
13-0.106308-1.07890.141575
140.0110860.11250.455319
150.2595232.63390.004871
16-0.168189-1.70690.045424
170.0303570.30810.379317
18-0.027652-0.28060.389775
190.0920110.93380.176293
20-0.15566-1.57980.058612
210.1318431.33810.091912
220.0030980.03140.487491
23-0.021554-0.21880.413638
24-0.123081-1.24910.107224
250.138181.40240.081905
260.0985160.99980.159869
27-0.092048-0.93420.176197
28-0.016183-0.16420.434933
29-0.053125-0.53920.29547
300.1147711.16480.123396
31-0.087845-0.89150.18736
320.0436230.44270.329447
330.0066450.06740.47318
34-0.084479-0.85740.196615
350.0687180.69740.243559
36-0.010339-0.10490.458317






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.321274-3.26060.000754
2-0.15007-1.5230.065406
3-0.191604-1.94460.027277
40.0348950.35410.361976
5-0.102922-1.04450.14934
6-0.192156-1.95020.026937
70.0558880.56720.285906
80.0947960.96210.169133
9-0.09795-0.99410.161256
10-0.033861-0.34370.365904
110.1875171.90310.02991
12-0.231516-2.34960.010349
13-0.251951-2.5570.006007
14-0.161743-1.64150.05187
150.0629770.63910.262072
16-0.054743-0.55560.289852
17-0.004126-0.04190.48334
18-0.150344-1.52580.065059
19-0.01974-0.20030.420805
20-0.003526-0.03580.485762
210.0820740.8330.203397
22-0.050692-0.51450.304015
23-0.003331-0.03380.486548
24-0.13676-1.3880.084072
25-0.069794-0.70830.240171
260.0311830.31650.376141
270.0703690.71420.238369
280.0261150.2650.395755
29-0.119293-1.21070.114391
30-0.04025-0.40850.341881
310.0303610.30810.379303
320.0059670.06060.475913
330.0647910.65760.256145
34-0.150575-1.52820.064768
350.057110.57960.281722
36-0.085526-0.8680.193709

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.321274 & -3.2606 & 0.000754 \tabularnewline
2 & -0.15007 & -1.523 & 0.065406 \tabularnewline
3 & -0.191604 & -1.9446 & 0.027277 \tabularnewline
4 & 0.034895 & 0.3541 & 0.361976 \tabularnewline
5 & -0.102922 & -1.0445 & 0.14934 \tabularnewline
6 & -0.192156 & -1.9502 & 0.026937 \tabularnewline
7 & 0.055888 & 0.5672 & 0.285906 \tabularnewline
8 & 0.094796 & 0.9621 & 0.169133 \tabularnewline
9 & -0.09795 & -0.9941 & 0.161256 \tabularnewline
10 & -0.033861 & -0.3437 & 0.365904 \tabularnewline
11 & 0.187517 & 1.9031 & 0.02991 \tabularnewline
12 & -0.231516 & -2.3496 & 0.010349 \tabularnewline
13 & -0.251951 & -2.557 & 0.006007 \tabularnewline
14 & -0.161743 & -1.6415 & 0.05187 \tabularnewline
15 & 0.062977 & 0.6391 & 0.262072 \tabularnewline
16 & -0.054743 & -0.5556 & 0.289852 \tabularnewline
17 & -0.004126 & -0.0419 & 0.48334 \tabularnewline
18 & -0.150344 & -1.5258 & 0.065059 \tabularnewline
19 & -0.01974 & -0.2003 & 0.420805 \tabularnewline
20 & -0.003526 & -0.0358 & 0.485762 \tabularnewline
21 & 0.082074 & 0.833 & 0.203397 \tabularnewline
22 & -0.050692 & -0.5145 & 0.304015 \tabularnewline
23 & -0.003331 & -0.0338 & 0.486548 \tabularnewline
24 & -0.13676 & -1.388 & 0.084072 \tabularnewline
25 & -0.069794 & -0.7083 & 0.240171 \tabularnewline
26 & 0.031183 & 0.3165 & 0.376141 \tabularnewline
27 & 0.070369 & 0.7142 & 0.238369 \tabularnewline
28 & 0.026115 & 0.265 & 0.395755 \tabularnewline
29 & -0.119293 & -1.2107 & 0.114391 \tabularnewline
30 & -0.04025 & -0.4085 & 0.341881 \tabularnewline
31 & 0.030361 & 0.3081 & 0.379303 \tabularnewline
32 & 0.005967 & 0.0606 & 0.475913 \tabularnewline
33 & 0.064791 & 0.6576 & 0.256145 \tabularnewline
34 & -0.150575 & -1.5282 & 0.064768 \tabularnewline
35 & 0.05711 & 0.5796 & 0.281722 \tabularnewline
36 & -0.085526 & -0.868 & 0.193709 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59648&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]-0.321274[/C][C]-3.2606[/C][C]0.000754[/C][/ROW]
[ROW][C]2[/C][C]-0.15007[/C][C]-1.523[/C][C]0.065406[/C][/ROW]
[ROW][C]3[/C][C]-0.191604[/C][C]-1.9446[/C][C]0.027277[/C][/ROW]
[ROW][C]4[/C][C]0.034895[/C][C]0.3541[/C][C]0.361976[/C][/ROW]
[ROW][C]5[/C][C]-0.102922[/C][C]-1.0445[/C][C]0.14934[/C][/ROW]
[ROW][C]6[/C][C]-0.192156[/C][C]-1.9502[/C][C]0.026937[/C][/ROW]
[ROW][C]7[/C][C]0.055888[/C][C]0.5672[/C][C]0.285906[/C][/ROW]
[ROW][C]8[/C][C]0.094796[/C][C]0.9621[/C][C]0.169133[/C][/ROW]
[ROW][C]9[/C][C]-0.09795[/C][C]-0.9941[/C][C]0.161256[/C][/ROW]
[ROW][C]10[/C][C]-0.033861[/C][C]-0.3437[/C][C]0.365904[/C][/ROW]
[ROW][C]11[/C][C]0.187517[/C][C]1.9031[/C][C]0.02991[/C][/ROW]
[ROW][C]12[/C][C]-0.231516[/C][C]-2.3496[/C][C]0.010349[/C][/ROW]
[ROW][C]13[/C][C]-0.251951[/C][C]-2.557[/C][C]0.006007[/C][/ROW]
[ROW][C]14[/C][C]-0.161743[/C][C]-1.6415[/C][C]0.05187[/C][/ROW]
[ROW][C]15[/C][C]0.062977[/C][C]0.6391[/C][C]0.262072[/C][/ROW]
[ROW][C]16[/C][C]-0.054743[/C][C]-0.5556[/C][C]0.289852[/C][/ROW]
[ROW][C]17[/C][C]-0.004126[/C][C]-0.0419[/C][C]0.48334[/C][/ROW]
[ROW][C]18[/C][C]-0.150344[/C][C]-1.5258[/C][C]0.065059[/C][/ROW]
[ROW][C]19[/C][C]-0.01974[/C][C]-0.2003[/C][C]0.420805[/C][/ROW]
[ROW][C]20[/C][C]-0.003526[/C][C]-0.0358[/C][C]0.485762[/C][/ROW]
[ROW][C]21[/C][C]0.082074[/C][C]0.833[/C][C]0.203397[/C][/ROW]
[ROW][C]22[/C][C]-0.050692[/C][C]-0.5145[/C][C]0.304015[/C][/ROW]
[ROW][C]23[/C][C]-0.003331[/C][C]-0.0338[/C][C]0.486548[/C][/ROW]
[ROW][C]24[/C][C]-0.13676[/C][C]-1.388[/C][C]0.084072[/C][/ROW]
[ROW][C]25[/C][C]-0.069794[/C][C]-0.7083[/C][C]0.240171[/C][/ROW]
[ROW][C]26[/C][C]0.031183[/C][C]0.3165[/C][C]0.376141[/C][/ROW]
[ROW][C]27[/C][C]0.070369[/C][C]0.7142[/C][C]0.238369[/C][/ROW]
[ROW][C]28[/C][C]0.026115[/C][C]0.265[/C][C]0.395755[/C][/ROW]
[ROW][C]29[/C][C]-0.119293[/C][C]-1.2107[/C][C]0.114391[/C][/ROW]
[ROW][C]30[/C][C]-0.04025[/C][C]-0.4085[/C][C]0.341881[/C][/ROW]
[ROW][C]31[/C][C]0.030361[/C][C]0.3081[/C][C]0.379303[/C][/ROW]
[ROW][C]32[/C][C]0.005967[/C][C]0.0606[/C][C]0.475913[/C][/ROW]
[ROW][C]33[/C][C]0.064791[/C][C]0.6576[/C][C]0.256145[/C][/ROW]
[ROW][C]34[/C][C]-0.150575[/C][C]-1.5282[/C][C]0.064768[/C][/ROW]
[ROW][C]35[/C][C]0.05711[/C][C]0.5796[/C][C]0.281722[/C][/ROW]
[ROW][C]36[/C][C]-0.085526[/C][C]-0.868[/C][C]0.193709[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59648&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59648&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
1-0.321274-3.26060.000754
2-0.15007-1.5230.065406
3-0.191604-1.94460.027277
40.0348950.35410.361976
5-0.102922-1.04450.14934
6-0.192156-1.95020.026937
70.0558880.56720.285906
80.0947960.96210.169133
9-0.09795-0.99410.161256
10-0.033861-0.34370.365904
110.1875171.90310.02991
12-0.231516-2.34960.010349
13-0.251951-2.5570.006007
14-0.161743-1.64150.05187
150.0629770.63910.262072
16-0.054743-0.55560.289852
17-0.004126-0.04190.48334
18-0.150344-1.52580.065059
19-0.01974-0.20030.420805
20-0.003526-0.03580.485762
210.0820740.8330.203397
22-0.050692-0.51450.304015
23-0.003331-0.03380.486548
24-0.13676-1.3880.084072
25-0.069794-0.70830.240171
260.0311830.31650.376141
270.0703690.71420.238369
280.0261150.2650.395755
29-0.119293-1.21070.114391
30-0.04025-0.40850.341881
310.0303610.30810.379303
320.0059670.06060.475913
330.0647910.65760.256145
34-0.150575-1.52820.064768
350.057110.57960.281722
36-0.085526-0.8680.193709


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')