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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 computationThu, 03 Dec 2009 11:47:03 -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/Dec/03/t1259866238n3pd15d8nunyhwr.htm/, Retrieved Fri, 29 Mar 2024 02:23:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63059, Retrieved Fri, 29 Mar 2024 02:23:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122
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       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
-   PD        [Spectral Analysis] [] [2009-11-27 13:46:28] [023d83ebdf42a2acf423907b4076e8a1]
- R P           [Spectral Analysis] [] [2009-11-27 14:27:00] [023d83ebdf42a2acf423907b4076e8a1]
- R P             [Spectral Analysis] [] [2009-12-03 18:25:52] [023d83ebdf42a2acf423907b4076e8a1]
- RMP                 [(Partial) Autocorrelation Function] [] [2009-12-03 18:47:03] [9f6463b67b1eb7bae5c03a796abf0348] [Current]
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Dataseries X:
12.610
10.862
52.929
56.902
81.776
87.876
82.103
72.846
60.632
33.521
15.342
7.758
8.668
13.082
38.157
58.263
81.153
88.476
72.329
75.845
61.108
37.665
12.755
2.793
12.935
19.533
33.404
52.074
70.735
69.702
61.656
82.993
53.990
32.283
15.686
2.713
12.842
19.244
48.488
54.464
84.192
84.458
85.793
75.163
68.212
49.233
24.302
5.402
15.058
33.559
70.358
85.934
94.452
129.305
113.882
107.256
94.274
57.842
26.611
14.521




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63059&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63059&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63059&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.44346-3.04020.001928
2-0.100928-0.69190.246194
3-0.044245-0.30330.38149
40.2178991.49380.07095
5-0.191975-1.31610.097259
60.1206850.82740.206104
70.0134050.09190.463585
8-0.166774-1.14330.129343
90.1858561.27420.104435
10-0.120706-0.82750.206062
110.1000140.68570.248148
12-0.116674-0.79990.213903
130.0316360.21690.414618
140.0200250.13730.445697
150.0749910.51410.30479
16-0.119328-0.81810.208723
170.0486160.33330.370197
180.0022130.01520.493979
19-0.054847-0.3760.354301
20-0.010013-0.06860.47278
210.1152480.79010.216719
22-0.042626-0.29220.3857
230.0048720.03340.486748
24-0.192919-1.32260.096187
250.2911321.99590.025879
26-0.073165-0.50160.309147
27-0.078245-0.53640.297099
28-0.077314-0.530.299291
290.241711.65710.052082
30-0.127285-0.87260.193653
310.0074070.05080.479857
320.0554450.38010.352787
33-0.186255-1.27690.103955
340.1215490.83330.204447
350.0318910.21860.413941
360.0183110.12550.450319
37-0.112113-0.76860.222986
380.1124630.7710.222281
39-0.118867-0.81490.209617
400.109260.7490.228781
41-0.060051-0.41170.341219
42-0.005361-0.03680.48542
430.006140.04210.483302
440.0423850.29060.386326
45-0.083179-0.57020.285613
460.0531770.36460.358537
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.44346 & -3.0402 & 0.001928 \tabularnewline
2 & -0.100928 & -0.6919 & 0.246194 \tabularnewline
3 & -0.044245 & -0.3033 & 0.38149 \tabularnewline
4 & 0.217899 & 1.4938 & 0.07095 \tabularnewline
5 & -0.191975 & -1.3161 & 0.097259 \tabularnewline
6 & 0.120685 & 0.8274 & 0.206104 \tabularnewline
7 & 0.013405 & 0.0919 & 0.463585 \tabularnewline
8 & -0.166774 & -1.1433 & 0.129343 \tabularnewline
9 & 0.185856 & 1.2742 & 0.104435 \tabularnewline
10 & -0.120706 & -0.8275 & 0.206062 \tabularnewline
11 & 0.100014 & 0.6857 & 0.248148 \tabularnewline
12 & -0.116674 & -0.7999 & 0.213903 \tabularnewline
13 & 0.031636 & 0.2169 & 0.414618 \tabularnewline
14 & 0.020025 & 0.1373 & 0.445697 \tabularnewline
15 & 0.074991 & 0.5141 & 0.30479 \tabularnewline
16 & -0.119328 & -0.8181 & 0.208723 \tabularnewline
17 & 0.048616 & 0.3333 & 0.370197 \tabularnewline
18 & 0.002213 & 0.0152 & 0.493979 \tabularnewline
19 & -0.054847 & -0.376 & 0.354301 \tabularnewline
20 & -0.010013 & -0.0686 & 0.47278 \tabularnewline
21 & 0.115248 & 0.7901 & 0.216719 \tabularnewline
22 & -0.042626 & -0.2922 & 0.3857 \tabularnewline
23 & 0.004872 & 0.0334 & 0.486748 \tabularnewline
24 & -0.192919 & -1.3226 & 0.096187 \tabularnewline
25 & 0.291132 & 1.9959 & 0.025879 \tabularnewline
26 & -0.073165 & -0.5016 & 0.309147 \tabularnewline
27 & -0.078245 & -0.5364 & 0.297099 \tabularnewline
28 & -0.077314 & -0.53 & 0.299291 \tabularnewline
29 & 0.24171 & 1.6571 & 0.052082 \tabularnewline
30 & -0.127285 & -0.8726 & 0.193653 \tabularnewline
31 & 0.007407 & 0.0508 & 0.479857 \tabularnewline
32 & 0.055445 & 0.3801 & 0.352787 \tabularnewline
33 & -0.186255 & -1.2769 & 0.103955 \tabularnewline
34 & 0.121549 & 0.8333 & 0.204447 \tabularnewline
35 & 0.031891 & 0.2186 & 0.413941 \tabularnewline
36 & 0.018311 & 0.1255 & 0.450319 \tabularnewline
37 & -0.112113 & -0.7686 & 0.222986 \tabularnewline
38 & 0.112463 & 0.771 & 0.222281 \tabularnewline
39 & -0.118867 & -0.8149 & 0.209617 \tabularnewline
40 & 0.10926 & 0.749 & 0.228781 \tabularnewline
41 & -0.060051 & -0.4117 & 0.341219 \tabularnewline
42 & -0.005361 & -0.0368 & 0.48542 \tabularnewline
43 & 0.00614 & 0.0421 & 0.483302 \tabularnewline
44 & 0.042385 & 0.2906 & 0.386326 \tabularnewline
45 & -0.083179 & -0.5702 & 0.285613 \tabularnewline
46 & 0.053177 & 0.3646 & 0.358537 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63059&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]-0.44346[/C][C]-3.0402[/C][C]0.001928[/C][/ROW]
[ROW][C]2[/C][C]-0.100928[/C][C]-0.6919[/C][C]0.246194[/C][/ROW]
[ROW][C]3[/C][C]-0.044245[/C][C]-0.3033[/C][C]0.38149[/C][/ROW]
[ROW][C]4[/C][C]0.217899[/C][C]1.4938[/C][C]0.07095[/C][/ROW]
[ROW][C]5[/C][C]-0.191975[/C][C]-1.3161[/C][C]0.097259[/C][/ROW]
[ROW][C]6[/C][C]0.120685[/C][C]0.8274[/C][C]0.206104[/C][/ROW]
[ROW][C]7[/C][C]0.013405[/C][C]0.0919[/C][C]0.463585[/C][/ROW]
[ROW][C]8[/C][C]-0.166774[/C][C]-1.1433[/C][C]0.129343[/C][/ROW]
[ROW][C]9[/C][C]0.185856[/C][C]1.2742[/C][C]0.104435[/C][/ROW]
[ROW][C]10[/C][C]-0.120706[/C][C]-0.8275[/C][C]0.206062[/C][/ROW]
[ROW][C]11[/C][C]0.100014[/C][C]0.6857[/C][C]0.248148[/C][/ROW]
[ROW][C]12[/C][C]-0.116674[/C][C]-0.7999[/C][C]0.213903[/C][/ROW]
[ROW][C]13[/C][C]0.031636[/C][C]0.2169[/C][C]0.414618[/C][/ROW]
[ROW][C]14[/C][C]0.020025[/C][C]0.1373[/C][C]0.445697[/C][/ROW]
[ROW][C]15[/C][C]0.074991[/C][C]0.5141[/C][C]0.30479[/C][/ROW]
[ROW][C]16[/C][C]-0.119328[/C][C]-0.8181[/C][C]0.208723[/C][/ROW]
[ROW][C]17[/C][C]0.048616[/C][C]0.3333[/C][C]0.370197[/C][/ROW]
[ROW][C]18[/C][C]0.002213[/C][C]0.0152[/C][C]0.493979[/C][/ROW]
[ROW][C]19[/C][C]-0.054847[/C][C]-0.376[/C][C]0.354301[/C][/ROW]
[ROW][C]20[/C][C]-0.010013[/C][C]-0.0686[/C][C]0.47278[/C][/ROW]
[ROW][C]21[/C][C]0.115248[/C][C]0.7901[/C][C]0.216719[/C][/ROW]
[ROW][C]22[/C][C]-0.042626[/C][C]-0.2922[/C][C]0.3857[/C][/ROW]
[ROW][C]23[/C][C]0.004872[/C][C]0.0334[/C][C]0.486748[/C][/ROW]
[ROW][C]24[/C][C]-0.192919[/C][C]-1.3226[/C][C]0.096187[/C][/ROW]
[ROW][C]25[/C][C]0.291132[/C][C]1.9959[/C][C]0.025879[/C][/ROW]
[ROW][C]26[/C][C]-0.073165[/C][C]-0.5016[/C][C]0.309147[/C][/ROW]
[ROW][C]27[/C][C]-0.078245[/C][C]-0.5364[/C][C]0.297099[/C][/ROW]
[ROW][C]28[/C][C]-0.077314[/C][C]-0.53[/C][C]0.299291[/C][/ROW]
[ROW][C]29[/C][C]0.24171[/C][C]1.6571[/C][C]0.052082[/C][/ROW]
[ROW][C]30[/C][C]-0.127285[/C][C]-0.8726[/C][C]0.193653[/C][/ROW]
[ROW][C]31[/C][C]0.007407[/C][C]0.0508[/C][C]0.479857[/C][/ROW]
[ROW][C]32[/C][C]0.055445[/C][C]0.3801[/C][C]0.352787[/C][/ROW]
[ROW][C]33[/C][C]-0.186255[/C][C]-1.2769[/C][C]0.103955[/C][/ROW]
[ROW][C]34[/C][C]0.121549[/C][C]0.8333[/C][C]0.204447[/C][/ROW]
[ROW][C]35[/C][C]0.031891[/C][C]0.2186[/C][C]0.413941[/C][/ROW]
[ROW][C]36[/C][C]0.018311[/C][C]0.1255[/C][C]0.450319[/C][/ROW]
[ROW][C]37[/C][C]-0.112113[/C][C]-0.7686[/C][C]0.222986[/C][/ROW]
[ROW][C]38[/C][C]0.112463[/C][C]0.771[/C][C]0.222281[/C][/ROW]
[ROW][C]39[/C][C]-0.118867[/C][C]-0.8149[/C][C]0.209617[/C][/ROW]
[ROW][C]40[/C][C]0.10926[/C][C]0.749[/C][C]0.228781[/C][/ROW]
[ROW][C]41[/C][C]-0.060051[/C][C]-0.4117[/C][C]0.341219[/C][/ROW]
[ROW][C]42[/C][C]-0.005361[/C][C]-0.0368[/C][C]0.48542[/C][/ROW]
[ROW][C]43[/C][C]0.00614[/C][C]0.0421[/C][C]0.483302[/C][/ROW]
[ROW][C]44[/C][C]0.042385[/C][C]0.2906[/C][C]0.386326[/C][/ROW]
[ROW][C]45[/C][C]-0.083179[/C][C]-0.5702[/C][C]0.285613[/C][/ROW]
[ROW][C]46[/C][C]0.053177[/C][C]0.3646[/C][C]0.358537[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63059&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63059&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.44346-3.04020.001928
2-0.100928-0.69190.246194
3-0.044245-0.30330.38149
40.2178991.49380.07095
5-0.191975-1.31610.097259
60.1206850.82740.206104
70.0134050.09190.463585
8-0.166774-1.14330.129343
90.1858561.27420.104435
10-0.120706-0.82750.206062
110.1000140.68570.248148
12-0.116674-0.79990.213903
130.0316360.21690.414618
140.0200250.13730.445697
150.0749910.51410.30479
16-0.119328-0.81810.208723
170.0486160.33330.370197
180.0022130.01520.493979
19-0.054847-0.3760.354301
20-0.010013-0.06860.47278
210.1152480.79010.216719
22-0.042626-0.29220.3857
230.0048720.03340.486748
24-0.192919-1.32260.096187
250.2911321.99590.025879
26-0.073165-0.50160.309147
27-0.078245-0.53640.297099
28-0.077314-0.530.299291
290.241711.65710.052082
30-0.127285-0.87260.193653
310.0074070.05080.479857
320.0554450.38010.352787
33-0.186255-1.27690.103955
340.1215490.83330.204447
350.0318910.21860.413941
360.0183110.12550.450319
37-0.112113-0.76860.222986
380.1124630.7710.222281
39-0.118867-0.81490.209617
400.109260.7490.228781
41-0.060051-0.41170.341219
42-0.005361-0.03680.48542
430.006140.04210.483302
440.0423850.29060.386326
45-0.083179-0.57020.285613
460.0531770.36460.358537
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.44346-3.04020.001928
2-0.370433-2.53960.007233
3-0.389339-2.66920.005203
4-0.083828-0.57470.284118
5-0.227697-1.5610.062615
6-0.039563-0.27120.393701
70.0780350.5350.297593
8-0.181595-1.2450.109661
90.1127570.7730.221689
10-0.121639-0.83390.204273
110.045880.31450.377253
12-0.021121-0.14480.442744
13-0.196314-1.34590.092402
140.0124750.08550.466103
15-0.020338-0.13940.444854
16-0.058469-0.40080.345177
170.0736860.50520.307902
18-0.090777-0.62230.268365
19-0.049329-0.33820.368365
20-0.201734-1.3830.086597
21-0.080701-0.55330.291354
220.019280.13220.447704
230.0525720.36040.360075
24-0.267269-1.83230.036623
250.1167620.80050.213731
260.0400780.27480.392351
27-0.013051-0.08950.464544
28-0.07481-0.51290.305221
290.0392590.26910.394497
300.0872170.59790.276379
310.111310.76310.224608
320.0929040.63690.263635
33-0.051274-0.35150.363387
34-0.066256-0.45420.325877
35-0.043002-0.29480.38472
36-0.106072-0.72720.235358
370.0331410.22720.410625
380.0234730.16090.436422
39-0.035631-0.24430.404041
400.0092060.06310.474972
41-0.036043-0.24710.402953
42-0.01352-0.09270.463273
43-0.083417-0.57190.285064
44-0.054394-0.37290.355447
45-0.038991-0.26730.3952
46-0.091228-0.62540.267357
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.44346 & -3.0402 & 0.001928 \tabularnewline
2 & -0.370433 & -2.5396 & 0.007233 \tabularnewline
3 & -0.389339 & -2.6692 & 0.005203 \tabularnewline
4 & -0.083828 & -0.5747 & 0.284118 \tabularnewline
5 & -0.227697 & -1.561 & 0.062615 \tabularnewline
6 & -0.039563 & -0.2712 & 0.393701 \tabularnewline
7 & 0.078035 & 0.535 & 0.297593 \tabularnewline
8 & -0.181595 & -1.245 & 0.109661 \tabularnewline
9 & 0.112757 & 0.773 & 0.221689 \tabularnewline
10 & -0.121639 & -0.8339 & 0.204273 \tabularnewline
11 & 0.04588 & 0.3145 & 0.377253 \tabularnewline
12 & -0.021121 & -0.1448 & 0.442744 \tabularnewline
13 & -0.196314 & -1.3459 & 0.092402 \tabularnewline
14 & 0.012475 & 0.0855 & 0.466103 \tabularnewline
15 & -0.020338 & -0.1394 & 0.444854 \tabularnewline
16 & -0.058469 & -0.4008 & 0.345177 \tabularnewline
17 & 0.073686 & 0.5052 & 0.307902 \tabularnewline
18 & -0.090777 & -0.6223 & 0.268365 \tabularnewline
19 & -0.049329 & -0.3382 & 0.368365 \tabularnewline
20 & -0.201734 & -1.383 & 0.086597 \tabularnewline
21 & -0.080701 & -0.5533 & 0.291354 \tabularnewline
22 & 0.01928 & 0.1322 & 0.447704 \tabularnewline
23 & 0.052572 & 0.3604 & 0.360075 \tabularnewline
24 & -0.267269 & -1.8323 & 0.036623 \tabularnewline
25 & 0.116762 & 0.8005 & 0.213731 \tabularnewline
26 & 0.040078 & 0.2748 & 0.392351 \tabularnewline
27 & -0.013051 & -0.0895 & 0.464544 \tabularnewline
28 & -0.07481 & -0.5129 & 0.305221 \tabularnewline
29 & 0.039259 & 0.2691 & 0.394497 \tabularnewline
30 & 0.087217 & 0.5979 & 0.276379 \tabularnewline
31 & 0.11131 & 0.7631 & 0.224608 \tabularnewline
32 & 0.092904 & 0.6369 & 0.263635 \tabularnewline
33 & -0.051274 & -0.3515 & 0.363387 \tabularnewline
34 & -0.066256 & -0.4542 & 0.325877 \tabularnewline
35 & -0.043002 & -0.2948 & 0.38472 \tabularnewline
36 & -0.106072 & -0.7272 & 0.235358 \tabularnewline
37 & 0.033141 & 0.2272 & 0.410625 \tabularnewline
38 & 0.023473 & 0.1609 & 0.436422 \tabularnewline
39 & -0.035631 & -0.2443 & 0.404041 \tabularnewline
40 & 0.009206 & 0.0631 & 0.474972 \tabularnewline
41 & -0.036043 & -0.2471 & 0.402953 \tabularnewline
42 & -0.01352 & -0.0927 & 0.463273 \tabularnewline
43 & -0.083417 & -0.5719 & 0.285064 \tabularnewline
44 & -0.054394 & -0.3729 & 0.355447 \tabularnewline
45 & -0.038991 & -0.2673 & 0.3952 \tabularnewline
46 & -0.091228 & -0.6254 & 0.267357 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63059&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]-0.44346[/C][C]-3.0402[/C][C]0.001928[/C][/ROW]
[ROW][C]2[/C][C]-0.370433[/C][C]-2.5396[/C][C]0.007233[/C][/ROW]
[ROW][C]3[/C][C]-0.389339[/C][C]-2.6692[/C][C]0.005203[/C][/ROW]
[ROW][C]4[/C][C]-0.083828[/C][C]-0.5747[/C][C]0.284118[/C][/ROW]
[ROW][C]5[/C][C]-0.227697[/C][C]-1.561[/C][C]0.062615[/C][/ROW]
[ROW][C]6[/C][C]-0.039563[/C][C]-0.2712[/C][C]0.393701[/C][/ROW]
[ROW][C]7[/C][C]0.078035[/C][C]0.535[/C][C]0.297593[/C][/ROW]
[ROW][C]8[/C][C]-0.181595[/C][C]-1.245[/C][C]0.109661[/C][/ROW]
[ROW][C]9[/C][C]0.112757[/C][C]0.773[/C][C]0.221689[/C][/ROW]
[ROW][C]10[/C][C]-0.121639[/C][C]-0.8339[/C][C]0.204273[/C][/ROW]
[ROW][C]11[/C][C]0.04588[/C][C]0.3145[/C][C]0.377253[/C][/ROW]
[ROW][C]12[/C][C]-0.021121[/C][C]-0.1448[/C][C]0.442744[/C][/ROW]
[ROW][C]13[/C][C]-0.196314[/C][C]-1.3459[/C][C]0.092402[/C][/ROW]
[ROW][C]14[/C][C]0.012475[/C][C]0.0855[/C][C]0.466103[/C][/ROW]
[ROW][C]15[/C][C]-0.020338[/C][C]-0.1394[/C][C]0.444854[/C][/ROW]
[ROW][C]16[/C][C]-0.058469[/C][C]-0.4008[/C][C]0.345177[/C][/ROW]
[ROW][C]17[/C][C]0.073686[/C][C]0.5052[/C][C]0.307902[/C][/ROW]
[ROW][C]18[/C][C]-0.090777[/C][C]-0.6223[/C][C]0.268365[/C][/ROW]
[ROW][C]19[/C][C]-0.049329[/C][C]-0.3382[/C][C]0.368365[/C][/ROW]
[ROW][C]20[/C][C]-0.201734[/C][C]-1.383[/C][C]0.086597[/C][/ROW]
[ROW][C]21[/C][C]-0.080701[/C][C]-0.5533[/C][C]0.291354[/C][/ROW]
[ROW][C]22[/C][C]0.01928[/C][C]0.1322[/C][C]0.447704[/C][/ROW]
[ROW][C]23[/C][C]0.052572[/C][C]0.3604[/C][C]0.360075[/C][/ROW]
[ROW][C]24[/C][C]-0.267269[/C][C]-1.8323[/C][C]0.036623[/C][/ROW]
[ROW][C]25[/C][C]0.116762[/C][C]0.8005[/C][C]0.213731[/C][/ROW]
[ROW][C]26[/C][C]0.040078[/C][C]0.2748[/C][C]0.392351[/C][/ROW]
[ROW][C]27[/C][C]-0.013051[/C][C]-0.0895[/C][C]0.464544[/C][/ROW]
[ROW][C]28[/C][C]-0.07481[/C][C]-0.5129[/C][C]0.305221[/C][/ROW]
[ROW][C]29[/C][C]0.039259[/C][C]0.2691[/C][C]0.394497[/C][/ROW]
[ROW][C]30[/C][C]0.087217[/C][C]0.5979[/C][C]0.276379[/C][/ROW]
[ROW][C]31[/C][C]0.11131[/C][C]0.7631[/C][C]0.224608[/C][/ROW]
[ROW][C]32[/C][C]0.092904[/C][C]0.6369[/C][C]0.263635[/C][/ROW]
[ROW][C]33[/C][C]-0.051274[/C][C]-0.3515[/C][C]0.363387[/C][/ROW]
[ROW][C]34[/C][C]-0.066256[/C][C]-0.4542[/C][C]0.325877[/C][/ROW]
[ROW][C]35[/C][C]-0.043002[/C][C]-0.2948[/C][C]0.38472[/C][/ROW]
[ROW][C]36[/C][C]-0.106072[/C][C]-0.7272[/C][C]0.235358[/C][/ROW]
[ROW][C]37[/C][C]0.033141[/C][C]0.2272[/C][C]0.410625[/C][/ROW]
[ROW][C]38[/C][C]0.023473[/C][C]0.1609[/C][C]0.436422[/C][/ROW]
[ROW][C]39[/C][C]-0.035631[/C][C]-0.2443[/C][C]0.404041[/C][/ROW]
[ROW][C]40[/C][C]0.009206[/C][C]0.0631[/C][C]0.474972[/C][/ROW]
[ROW][C]41[/C][C]-0.036043[/C][C]-0.2471[/C][C]0.402953[/C][/ROW]
[ROW][C]42[/C][C]-0.01352[/C][C]-0.0927[/C][C]0.463273[/C][/ROW]
[ROW][C]43[/C][C]-0.083417[/C][C]-0.5719[/C][C]0.285064[/C][/ROW]
[ROW][C]44[/C][C]-0.054394[/C][C]-0.3729[/C][C]0.355447[/C][/ROW]
[ROW][C]45[/C][C]-0.038991[/C][C]-0.2673[/C][C]0.3952[/C][/ROW]
[ROW][C]46[/C][C]-0.091228[/C][C]-0.6254[/C][C]0.267357[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63059&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63059&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.44346-3.04020.001928
2-0.370433-2.53960.007233
3-0.389339-2.66920.005203
4-0.083828-0.57470.284118
5-0.227697-1.5610.062615
6-0.039563-0.27120.393701
70.0780350.5350.297593
8-0.181595-1.2450.109661
90.1127570.7730.221689
10-0.121639-0.83390.204273
110.045880.31450.377253
12-0.021121-0.14480.442744
13-0.196314-1.34590.092402
140.0124750.08550.466103
15-0.020338-0.13940.444854
16-0.058469-0.40080.345177
170.0736860.50520.307902
18-0.090777-0.62230.268365
19-0.049329-0.33820.368365
20-0.201734-1.3830.086597
21-0.080701-0.55330.291354
220.019280.13220.447704
230.0525720.36040.360075
24-0.267269-1.83230.036623
250.1167620.80050.213731
260.0400780.27480.392351
27-0.013051-0.08950.464544
28-0.07481-0.51290.305221
290.0392590.26910.394497
300.0872170.59790.276379
310.111310.76310.224608
320.0929040.63690.263635
33-0.051274-0.35150.363387
34-0.066256-0.45420.325877
35-0.043002-0.29480.38472
36-0.106072-0.72720.235358
370.0331410.22720.410625
380.0234730.16090.436422
39-0.035631-0.24430.404041
400.0092060.06310.474972
41-0.036043-0.24710.402953
42-0.01352-0.09270.463273
43-0.083417-0.57190.285064
44-0.054394-0.37290.355447
45-0.038991-0.26730.3952
46-0.091228-0.62540.267357
47NANANA
48NANANA



Parameters (Session):
par1 = 48 ; par2 = 0.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 0.3 ; par3 = 1 ; 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')