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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 computationSun, 13 Dec 2009 10:13:07 -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/13/t1260724436lwtrcxr1m633jd4.htm/, Retrieved Sun, 28 Apr 2024 06:42:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67370, Retrieved Sun, 28 Apr 2024 06:42:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
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] [W8] [2009-11-25 18:19:32] [315ba876df544ad397193b5931d5f354]
-    D          [(Partial) Autocorrelation Function] [ws8 1.1] [2009-11-27 16:22:27] [95cead3ebb75668735f848316249436a]
-   P             [(Partial) Autocorrelation Function] [ws8.2] [2009-11-27 16:33:59] [95cead3ebb75668735f848316249436a]
-   PD              [(Partial) Autocorrelation Function] [D=1 d=0] [2009-12-13 14:12:45] [95cead3ebb75668735f848316249436a]
-   PD                [(Partial) Autocorrelation Function] [deel2 D=0, d=1] [2009-12-13 17:08:02] [95cead3ebb75668735f848316249436a]
-   P                     [(Partial) Autocorrelation Function] [deel 2 D=1 d=2] [2009-12-13 17:13:07] [95523ebdb89b97dbf680ec91e0b4bca2] [Current]
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Dataseries X:
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17




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=67370&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=67370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67370&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
1-0.395521-2.95980.002253
2-0.157604-1.17940.121612
30.1299690.97260.167467
4-0.222071-1.66180.051068
50.3029592.26710.013631
60.0875540.65520.257513
7-0.343723-2.57220.006393
80.1827761.36780.088424
9-0.008527-0.06380.474673
10-0.106735-0.79870.213911
110.4498233.36620.000691
12-0.423381-3.16830.001242
13-0.107984-0.80810.211232
140.3091872.31370.012188
15-0.106802-0.79920.213766
160.0897170.67140.252369
17-0.086232-0.64530.260684
18-0.184536-1.38090.086392
190.2475221.85230.034629
20-0.053234-0.39840.345938
21-0.013399-0.10030.460243
220.0329410.24650.403096
23-0.067907-0.50820.306665
24-0.066428-0.49710.310531
250.1654811.23830.110377
26-0.103082-0.77140.221857
27-0.024582-0.1840.427355
280.0563120.42140.337539
29-0.071082-0.53190.298439
300.0786230.58840.279329
31-0.05732-0.42890.334806
320.012180.09110.463852
330.0033010.02470.490189
340.0128540.09620.461857
35-0.06707-0.50190.30885
360.0451830.33810.368269
370.0158270.11840.453071
38-0.034248-0.25630.399335
390.0339980.25440.400053
40-0.039839-0.29810.383354
410.0056690.04240.483156
420.0329690.24670.403015
43-0.038048-0.28470.388453
44-0.000883-0.00660.497376
45-0.013688-0.10240.459389
460.0094410.07060.471965
470.0170210.12740.44955
480.0059530.04450.482313
49-0.031488-0.23560.407288
500.0005920.00440.498241
51-0.000392-0.00290.498834
520.0054450.04070.483821
530.0025710.01920.492358
54-0.013864-0.10370.458869
550.0038050.02850.488694
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.395521 & -2.9598 & 0.002253 \tabularnewline
2 & -0.157604 & -1.1794 & 0.121612 \tabularnewline
3 & 0.129969 & 0.9726 & 0.167467 \tabularnewline
4 & -0.222071 & -1.6618 & 0.051068 \tabularnewline
5 & 0.302959 & 2.2671 & 0.013631 \tabularnewline
6 & 0.087554 & 0.6552 & 0.257513 \tabularnewline
7 & -0.343723 & -2.5722 & 0.006393 \tabularnewline
8 & 0.182776 & 1.3678 & 0.088424 \tabularnewline
9 & -0.008527 & -0.0638 & 0.474673 \tabularnewline
10 & -0.106735 & -0.7987 & 0.213911 \tabularnewline
11 & 0.449823 & 3.3662 & 0.000691 \tabularnewline
12 & -0.423381 & -3.1683 & 0.001242 \tabularnewline
13 & -0.107984 & -0.8081 & 0.211232 \tabularnewline
14 & 0.309187 & 2.3137 & 0.012188 \tabularnewline
15 & -0.106802 & -0.7992 & 0.213766 \tabularnewline
16 & 0.089717 & 0.6714 & 0.252369 \tabularnewline
17 & -0.086232 & -0.6453 & 0.260684 \tabularnewline
18 & -0.184536 & -1.3809 & 0.086392 \tabularnewline
19 & 0.247522 & 1.8523 & 0.034629 \tabularnewline
20 & -0.053234 & -0.3984 & 0.345938 \tabularnewline
21 & -0.013399 & -0.1003 & 0.460243 \tabularnewline
22 & 0.032941 & 0.2465 & 0.403096 \tabularnewline
23 & -0.067907 & -0.5082 & 0.306665 \tabularnewline
24 & -0.066428 & -0.4971 & 0.310531 \tabularnewline
25 & 0.165481 & 1.2383 & 0.110377 \tabularnewline
26 & -0.103082 & -0.7714 & 0.221857 \tabularnewline
27 & -0.024582 & -0.184 & 0.427355 \tabularnewline
28 & 0.056312 & 0.4214 & 0.337539 \tabularnewline
29 & -0.071082 & -0.5319 & 0.298439 \tabularnewline
30 & 0.078623 & 0.5884 & 0.279329 \tabularnewline
31 & -0.05732 & -0.4289 & 0.334806 \tabularnewline
32 & 0.01218 & 0.0911 & 0.463852 \tabularnewline
33 & 0.003301 & 0.0247 & 0.490189 \tabularnewline
34 & 0.012854 & 0.0962 & 0.461857 \tabularnewline
35 & -0.06707 & -0.5019 & 0.30885 \tabularnewline
36 & 0.045183 & 0.3381 & 0.368269 \tabularnewline
37 & 0.015827 & 0.1184 & 0.453071 \tabularnewline
38 & -0.034248 & -0.2563 & 0.399335 \tabularnewline
39 & 0.033998 & 0.2544 & 0.400053 \tabularnewline
40 & -0.039839 & -0.2981 & 0.383354 \tabularnewline
41 & 0.005669 & 0.0424 & 0.483156 \tabularnewline
42 & 0.032969 & 0.2467 & 0.403015 \tabularnewline
43 & -0.038048 & -0.2847 & 0.388453 \tabularnewline
44 & -0.000883 & -0.0066 & 0.497376 \tabularnewline
45 & -0.013688 & -0.1024 & 0.459389 \tabularnewline
46 & 0.009441 & 0.0706 & 0.471965 \tabularnewline
47 & 0.017021 & 0.1274 & 0.44955 \tabularnewline
48 & 0.005953 & 0.0445 & 0.482313 \tabularnewline
49 & -0.031488 & -0.2356 & 0.407288 \tabularnewline
50 & 0.000592 & 0.0044 & 0.498241 \tabularnewline
51 & -0.000392 & -0.0029 & 0.498834 \tabularnewline
52 & 0.005445 & 0.0407 & 0.483821 \tabularnewline
53 & 0.002571 & 0.0192 & 0.492358 \tabularnewline
54 & -0.013864 & -0.1037 & 0.458869 \tabularnewline
55 & 0.003805 & 0.0285 & 0.488694 \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67370&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]-0.395521[/C][C]-2.9598[/C][C]0.002253[/C][/ROW]
[ROW][C]2[/C][C]-0.157604[/C][C]-1.1794[/C][C]0.121612[/C][/ROW]
[ROW][C]3[/C][C]0.129969[/C][C]0.9726[/C][C]0.167467[/C][/ROW]
[ROW][C]4[/C][C]-0.222071[/C][C]-1.6618[/C][C]0.051068[/C][/ROW]
[ROW][C]5[/C][C]0.302959[/C][C]2.2671[/C][C]0.013631[/C][/ROW]
[ROW][C]6[/C][C]0.087554[/C][C]0.6552[/C][C]0.257513[/C][/ROW]
[ROW][C]7[/C][C]-0.343723[/C][C]-2.5722[/C][C]0.006393[/C][/ROW]
[ROW][C]8[/C][C]0.182776[/C][C]1.3678[/C][C]0.088424[/C][/ROW]
[ROW][C]9[/C][C]-0.008527[/C][C]-0.0638[/C][C]0.474673[/C][/ROW]
[ROW][C]10[/C][C]-0.106735[/C][C]-0.7987[/C][C]0.213911[/C][/ROW]
[ROW][C]11[/C][C]0.449823[/C][C]3.3662[/C][C]0.000691[/C][/ROW]
[ROW][C]12[/C][C]-0.423381[/C][C]-3.1683[/C][C]0.001242[/C][/ROW]
[ROW][C]13[/C][C]-0.107984[/C][C]-0.8081[/C][C]0.211232[/C][/ROW]
[ROW][C]14[/C][C]0.309187[/C][C]2.3137[/C][C]0.012188[/C][/ROW]
[ROW][C]15[/C][C]-0.106802[/C][C]-0.7992[/C][C]0.213766[/C][/ROW]
[ROW][C]16[/C][C]0.089717[/C][C]0.6714[/C][C]0.252369[/C][/ROW]
[ROW][C]17[/C][C]-0.086232[/C][C]-0.6453[/C][C]0.260684[/C][/ROW]
[ROW][C]18[/C][C]-0.184536[/C][C]-1.3809[/C][C]0.086392[/C][/ROW]
[ROW][C]19[/C][C]0.247522[/C][C]1.8523[/C][C]0.034629[/C][/ROW]
[ROW][C]20[/C][C]-0.053234[/C][C]-0.3984[/C][C]0.345938[/C][/ROW]
[ROW][C]21[/C][C]-0.013399[/C][C]-0.1003[/C][C]0.460243[/C][/ROW]
[ROW][C]22[/C][C]0.032941[/C][C]0.2465[/C][C]0.403096[/C][/ROW]
[ROW][C]23[/C][C]-0.067907[/C][C]-0.5082[/C][C]0.306665[/C][/ROW]
[ROW][C]24[/C][C]-0.066428[/C][C]-0.4971[/C][C]0.310531[/C][/ROW]
[ROW][C]25[/C][C]0.165481[/C][C]1.2383[/C][C]0.110377[/C][/ROW]
[ROW][C]26[/C][C]-0.103082[/C][C]-0.7714[/C][C]0.221857[/C][/ROW]
[ROW][C]27[/C][C]-0.024582[/C][C]-0.184[/C][C]0.427355[/C][/ROW]
[ROW][C]28[/C][C]0.056312[/C][C]0.4214[/C][C]0.337539[/C][/ROW]
[ROW][C]29[/C][C]-0.071082[/C][C]-0.5319[/C][C]0.298439[/C][/ROW]
[ROW][C]30[/C][C]0.078623[/C][C]0.5884[/C][C]0.279329[/C][/ROW]
[ROW][C]31[/C][C]-0.05732[/C][C]-0.4289[/C][C]0.334806[/C][/ROW]
[ROW][C]32[/C][C]0.01218[/C][C]0.0911[/C][C]0.463852[/C][/ROW]
[ROW][C]33[/C][C]0.003301[/C][C]0.0247[/C][C]0.490189[/C][/ROW]
[ROW][C]34[/C][C]0.012854[/C][C]0.0962[/C][C]0.461857[/C][/ROW]
[ROW][C]35[/C][C]-0.06707[/C][C]-0.5019[/C][C]0.30885[/C][/ROW]
[ROW][C]36[/C][C]0.045183[/C][C]0.3381[/C][C]0.368269[/C][/ROW]
[ROW][C]37[/C][C]0.015827[/C][C]0.1184[/C][C]0.453071[/C][/ROW]
[ROW][C]38[/C][C]-0.034248[/C][C]-0.2563[/C][C]0.399335[/C][/ROW]
[ROW][C]39[/C][C]0.033998[/C][C]0.2544[/C][C]0.400053[/C][/ROW]
[ROW][C]40[/C][C]-0.039839[/C][C]-0.2981[/C][C]0.383354[/C][/ROW]
[ROW][C]41[/C][C]0.005669[/C][C]0.0424[/C][C]0.483156[/C][/ROW]
[ROW][C]42[/C][C]0.032969[/C][C]0.2467[/C][C]0.403015[/C][/ROW]
[ROW][C]43[/C][C]-0.038048[/C][C]-0.2847[/C][C]0.388453[/C][/ROW]
[ROW][C]44[/C][C]-0.000883[/C][C]-0.0066[/C][C]0.497376[/C][/ROW]
[ROW][C]45[/C][C]-0.013688[/C][C]-0.1024[/C][C]0.459389[/C][/ROW]
[ROW][C]46[/C][C]0.009441[/C][C]0.0706[/C][C]0.471965[/C][/ROW]
[ROW][C]47[/C][C]0.017021[/C][C]0.1274[/C][C]0.44955[/C][/ROW]
[ROW][C]48[/C][C]0.005953[/C][C]0.0445[/C][C]0.482313[/C][/ROW]
[ROW][C]49[/C][C]-0.031488[/C][C]-0.2356[/C][C]0.407288[/C][/ROW]
[ROW][C]50[/C][C]0.000592[/C][C]0.0044[/C][C]0.498241[/C][/ROW]
[ROW][C]51[/C][C]-0.000392[/C][C]-0.0029[/C][C]0.498834[/C][/ROW]
[ROW][C]52[/C][C]0.005445[/C][C]0.0407[/C][C]0.483821[/C][/ROW]
[ROW][C]53[/C][C]0.002571[/C][C]0.0192[/C][C]0.492358[/C][/ROW]
[ROW][C]54[/C][C]-0.013864[/C][C]-0.1037[/C][C]0.458869[/C][/ROW]
[ROW][C]55[/C][C]0.003805[/C][C]0.0285[/C][C]0.488694[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67370&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67370&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
1-0.395521-2.95980.002253
2-0.157604-1.17940.121612
30.1299690.97260.167467
4-0.222071-1.66180.051068
50.3029592.26710.013631
60.0875540.65520.257513
7-0.343723-2.57220.006393
80.1827761.36780.088424
9-0.008527-0.06380.474673
10-0.106735-0.79870.213911
110.4498233.36620.000691
12-0.423381-3.16830.001242
13-0.107984-0.80810.211232
140.3091872.31370.012188
15-0.106802-0.79920.213766
160.0897170.67140.252369
17-0.086232-0.64530.260684
18-0.184536-1.38090.086392
190.2475221.85230.034629
20-0.053234-0.39840.345938
21-0.013399-0.10030.460243
220.0329410.24650.403096
23-0.067907-0.50820.306665
24-0.066428-0.49710.310531
250.1654811.23830.110377
26-0.103082-0.77140.221857
27-0.024582-0.1840.427355
280.0563120.42140.337539
29-0.071082-0.53190.298439
300.0786230.58840.279329
31-0.05732-0.42890.334806
320.012180.09110.463852
330.0033010.02470.490189
340.0128540.09620.461857
35-0.06707-0.50190.30885
360.0451830.33810.368269
370.0158270.11840.453071
38-0.034248-0.25630.399335
390.0339980.25440.400053
40-0.039839-0.29810.383354
410.0056690.04240.483156
420.0329690.24670.403015
43-0.038048-0.28470.388453
44-0.000883-0.00660.497376
45-0.013688-0.10240.459389
460.0094410.07060.471965
470.0170210.12740.44955
480.0059530.04450.482313
49-0.031488-0.23560.407288
500.0005920.00440.498241
51-0.000392-0.00290.498834
520.0054450.04070.483821
530.0025710.01920.492358
54-0.013864-0.10370.458869
550.0038050.02850.488694
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.395521-2.95980.002253
2-0.372279-2.78590.003636
3-0.141495-1.05880.147107
4-0.381156-2.85230.003035
50.0501770.37550.354357
60.2530181.89340.031737
7-0.051333-0.38410.351166
80.0595380.44550.328822
90.0802080.60020.27539
10-0.105744-0.79130.21605
110.4051653.0320.001838
120.0421440.31540.376823
13-0.185766-1.39010.084993
14-0.000524-0.00390.498444
150.1080840.80880.211019
16-0.075905-0.5680.286145
17-0.135085-1.01090.15821
180.01430.1070.457582
19-0.052565-0.39340.347774
20-0.20625-1.54340.06418
210.1367931.02370.155197
22-0.117812-0.88160.190874
230.1911081.43010.079119
240.0032110.0240.490456
25-0.094722-0.70880.240685
26-0.123509-0.92430.179659
270.0063940.04780.481004
280.0623920.46690.321191
29-0.074506-0.55760.289685
30-0.061925-0.46340.322435
31-0.020101-0.15040.440485
32-0.03837-0.28710.387534
330.0651210.48730.313968
34-0.021677-0.16220.435861
350.0393680.29460.384693
36-0.01727-0.12920.448818
37-0.017155-0.12840.449156
380.0037370.0280.488894
390.0024910.01860.492598
400.0555730.41590.339548
410.0467550.34990.363869
42-0.075427-0.56440.287354
43-0.09783-0.73210.233582
44-0.078575-0.5880.279446
45-0.002819-0.02110.491623
46-0.041126-0.30780.379703
47-0.013306-0.09960.460519
48-0.043557-0.3260.372837
49-0.015539-0.11630.453922
500.0421250.31520.376878
51-0.029083-0.21760.414252
520.0090160.06750.473225
53-0.028621-0.21420.415592
540.017020.12740.449554
55-0.039746-0.29740.383619
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.395521 & -2.9598 & 0.002253 \tabularnewline
2 & -0.372279 & -2.7859 & 0.003636 \tabularnewline
3 & -0.141495 & -1.0588 & 0.147107 \tabularnewline
4 & -0.381156 & -2.8523 & 0.003035 \tabularnewline
5 & 0.050177 & 0.3755 & 0.354357 \tabularnewline
6 & 0.253018 & 1.8934 & 0.031737 \tabularnewline
7 & -0.051333 & -0.3841 & 0.351166 \tabularnewline
8 & 0.059538 & 0.4455 & 0.328822 \tabularnewline
9 & 0.080208 & 0.6002 & 0.27539 \tabularnewline
10 & -0.105744 & -0.7913 & 0.21605 \tabularnewline
11 & 0.405165 & 3.032 & 0.001838 \tabularnewline
12 & 0.042144 & 0.3154 & 0.376823 \tabularnewline
13 & -0.185766 & -1.3901 & 0.084993 \tabularnewline
14 & -0.000524 & -0.0039 & 0.498444 \tabularnewline
15 & 0.108084 & 0.8088 & 0.211019 \tabularnewline
16 & -0.075905 & -0.568 & 0.286145 \tabularnewline
17 & -0.135085 & -1.0109 & 0.15821 \tabularnewline
18 & 0.0143 & 0.107 & 0.457582 \tabularnewline
19 & -0.052565 & -0.3934 & 0.347774 \tabularnewline
20 & -0.20625 & -1.5434 & 0.06418 \tabularnewline
21 & 0.136793 & 1.0237 & 0.155197 \tabularnewline
22 & -0.117812 & -0.8816 & 0.190874 \tabularnewline
23 & 0.191108 & 1.4301 & 0.079119 \tabularnewline
24 & 0.003211 & 0.024 & 0.490456 \tabularnewline
25 & -0.094722 & -0.7088 & 0.240685 \tabularnewline
26 & -0.123509 & -0.9243 & 0.179659 \tabularnewline
27 & 0.006394 & 0.0478 & 0.481004 \tabularnewline
28 & 0.062392 & 0.4669 & 0.321191 \tabularnewline
29 & -0.074506 & -0.5576 & 0.289685 \tabularnewline
30 & -0.061925 & -0.4634 & 0.322435 \tabularnewline
31 & -0.020101 & -0.1504 & 0.440485 \tabularnewline
32 & -0.03837 & -0.2871 & 0.387534 \tabularnewline
33 & 0.065121 & 0.4873 & 0.313968 \tabularnewline
34 & -0.021677 & -0.1622 & 0.435861 \tabularnewline
35 & 0.039368 & 0.2946 & 0.384693 \tabularnewline
36 & -0.01727 & -0.1292 & 0.448818 \tabularnewline
37 & -0.017155 & -0.1284 & 0.449156 \tabularnewline
38 & 0.003737 & 0.028 & 0.488894 \tabularnewline
39 & 0.002491 & 0.0186 & 0.492598 \tabularnewline
40 & 0.055573 & 0.4159 & 0.339548 \tabularnewline
41 & 0.046755 & 0.3499 & 0.363869 \tabularnewline
42 & -0.075427 & -0.5644 & 0.287354 \tabularnewline
43 & -0.09783 & -0.7321 & 0.233582 \tabularnewline
44 & -0.078575 & -0.588 & 0.279446 \tabularnewline
45 & -0.002819 & -0.0211 & 0.491623 \tabularnewline
46 & -0.041126 & -0.3078 & 0.379703 \tabularnewline
47 & -0.013306 & -0.0996 & 0.460519 \tabularnewline
48 & -0.043557 & -0.326 & 0.372837 \tabularnewline
49 & -0.015539 & -0.1163 & 0.453922 \tabularnewline
50 & 0.042125 & 0.3152 & 0.376878 \tabularnewline
51 & -0.029083 & -0.2176 & 0.414252 \tabularnewline
52 & 0.009016 & 0.0675 & 0.473225 \tabularnewline
53 & -0.028621 & -0.2142 & 0.415592 \tabularnewline
54 & 0.01702 & 0.1274 & 0.449554 \tabularnewline
55 & -0.039746 & -0.2974 & 0.383619 \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67370&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]-0.395521[/C][C]-2.9598[/C][C]0.002253[/C][/ROW]
[ROW][C]2[/C][C]-0.372279[/C][C]-2.7859[/C][C]0.003636[/C][/ROW]
[ROW][C]3[/C][C]-0.141495[/C][C]-1.0588[/C][C]0.147107[/C][/ROW]
[ROW][C]4[/C][C]-0.381156[/C][C]-2.8523[/C][C]0.003035[/C][/ROW]
[ROW][C]5[/C][C]0.050177[/C][C]0.3755[/C][C]0.354357[/C][/ROW]
[ROW][C]6[/C][C]0.253018[/C][C]1.8934[/C][C]0.031737[/C][/ROW]
[ROW][C]7[/C][C]-0.051333[/C][C]-0.3841[/C][C]0.351166[/C][/ROW]
[ROW][C]8[/C][C]0.059538[/C][C]0.4455[/C][C]0.328822[/C][/ROW]
[ROW][C]9[/C][C]0.080208[/C][C]0.6002[/C][C]0.27539[/C][/ROW]
[ROW][C]10[/C][C]-0.105744[/C][C]-0.7913[/C][C]0.21605[/C][/ROW]
[ROW][C]11[/C][C]0.405165[/C][C]3.032[/C][C]0.001838[/C][/ROW]
[ROW][C]12[/C][C]0.042144[/C][C]0.3154[/C][C]0.376823[/C][/ROW]
[ROW][C]13[/C][C]-0.185766[/C][C]-1.3901[/C][C]0.084993[/C][/ROW]
[ROW][C]14[/C][C]-0.000524[/C][C]-0.0039[/C][C]0.498444[/C][/ROW]
[ROW][C]15[/C][C]0.108084[/C][C]0.8088[/C][C]0.211019[/C][/ROW]
[ROW][C]16[/C][C]-0.075905[/C][C]-0.568[/C][C]0.286145[/C][/ROW]
[ROW][C]17[/C][C]-0.135085[/C][C]-1.0109[/C][C]0.15821[/C][/ROW]
[ROW][C]18[/C][C]0.0143[/C][C]0.107[/C][C]0.457582[/C][/ROW]
[ROW][C]19[/C][C]-0.052565[/C][C]-0.3934[/C][C]0.347774[/C][/ROW]
[ROW][C]20[/C][C]-0.20625[/C][C]-1.5434[/C][C]0.06418[/C][/ROW]
[ROW][C]21[/C][C]0.136793[/C][C]1.0237[/C][C]0.155197[/C][/ROW]
[ROW][C]22[/C][C]-0.117812[/C][C]-0.8816[/C][C]0.190874[/C][/ROW]
[ROW][C]23[/C][C]0.191108[/C][C]1.4301[/C][C]0.079119[/C][/ROW]
[ROW][C]24[/C][C]0.003211[/C][C]0.024[/C][C]0.490456[/C][/ROW]
[ROW][C]25[/C][C]-0.094722[/C][C]-0.7088[/C][C]0.240685[/C][/ROW]
[ROW][C]26[/C][C]-0.123509[/C][C]-0.9243[/C][C]0.179659[/C][/ROW]
[ROW][C]27[/C][C]0.006394[/C][C]0.0478[/C][C]0.481004[/C][/ROW]
[ROW][C]28[/C][C]0.062392[/C][C]0.4669[/C][C]0.321191[/C][/ROW]
[ROW][C]29[/C][C]-0.074506[/C][C]-0.5576[/C][C]0.289685[/C][/ROW]
[ROW][C]30[/C][C]-0.061925[/C][C]-0.4634[/C][C]0.322435[/C][/ROW]
[ROW][C]31[/C][C]-0.020101[/C][C]-0.1504[/C][C]0.440485[/C][/ROW]
[ROW][C]32[/C][C]-0.03837[/C][C]-0.2871[/C][C]0.387534[/C][/ROW]
[ROW][C]33[/C][C]0.065121[/C][C]0.4873[/C][C]0.313968[/C][/ROW]
[ROW][C]34[/C][C]-0.021677[/C][C]-0.1622[/C][C]0.435861[/C][/ROW]
[ROW][C]35[/C][C]0.039368[/C][C]0.2946[/C][C]0.384693[/C][/ROW]
[ROW][C]36[/C][C]-0.01727[/C][C]-0.1292[/C][C]0.448818[/C][/ROW]
[ROW][C]37[/C][C]-0.017155[/C][C]-0.1284[/C][C]0.449156[/C][/ROW]
[ROW][C]38[/C][C]0.003737[/C][C]0.028[/C][C]0.488894[/C][/ROW]
[ROW][C]39[/C][C]0.002491[/C][C]0.0186[/C][C]0.492598[/C][/ROW]
[ROW][C]40[/C][C]0.055573[/C][C]0.4159[/C][C]0.339548[/C][/ROW]
[ROW][C]41[/C][C]0.046755[/C][C]0.3499[/C][C]0.363869[/C][/ROW]
[ROW][C]42[/C][C]-0.075427[/C][C]-0.5644[/C][C]0.287354[/C][/ROW]
[ROW][C]43[/C][C]-0.09783[/C][C]-0.7321[/C][C]0.233582[/C][/ROW]
[ROW][C]44[/C][C]-0.078575[/C][C]-0.588[/C][C]0.279446[/C][/ROW]
[ROW][C]45[/C][C]-0.002819[/C][C]-0.0211[/C][C]0.491623[/C][/ROW]
[ROW][C]46[/C][C]-0.041126[/C][C]-0.3078[/C][C]0.379703[/C][/ROW]
[ROW][C]47[/C][C]-0.013306[/C][C]-0.0996[/C][C]0.460519[/C][/ROW]
[ROW][C]48[/C][C]-0.043557[/C][C]-0.326[/C][C]0.372837[/C][/ROW]
[ROW][C]49[/C][C]-0.015539[/C][C]-0.1163[/C][C]0.453922[/C][/ROW]
[ROW][C]50[/C][C]0.042125[/C][C]0.3152[/C][C]0.376878[/C][/ROW]
[ROW][C]51[/C][C]-0.029083[/C][C]-0.2176[/C][C]0.414252[/C][/ROW]
[ROW][C]52[/C][C]0.009016[/C][C]0.0675[/C][C]0.473225[/C][/ROW]
[ROW][C]53[/C][C]-0.028621[/C][C]-0.2142[/C][C]0.415592[/C][/ROW]
[ROW][C]54[/C][C]0.01702[/C][C]0.1274[/C][C]0.449554[/C][/ROW]
[ROW][C]55[/C][C]-0.039746[/C][C]-0.2974[/C][C]0.383619[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67370&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67370&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
1-0.395521-2.95980.002253
2-0.372279-2.78590.003636
3-0.141495-1.05880.147107
4-0.381156-2.85230.003035
50.0501770.37550.354357
60.2530181.89340.031737
7-0.051333-0.38410.351166
80.0595380.44550.328822
90.0802080.60020.27539
10-0.105744-0.79130.21605
110.4051653.0320.001838
120.0421440.31540.376823
13-0.185766-1.39010.084993
14-0.000524-0.00390.498444
150.1080840.80880.211019
16-0.075905-0.5680.286145
17-0.135085-1.01090.15821
180.01430.1070.457582
19-0.052565-0.39340.347774
20-0.20625-1.54340.06418
210.1367931.02370.155197
22-0.117812-0.88160.190874
230.1911081.43010.079119
240.0032110.0240.490456
25-0.094722-0.70880.240685
26-0.123509-0.92430.179659
270.0063940.04780.481004
280.0623920.46690.321191
29-0.074506-0.55760.289685
30-0.061925-0.46340.322435
31-0.020101-0.15040.440485
32-0.03837-0.28710.387534
330.0651210.48730.313968
34-0.021677-0.16220.435861
350.0393680.29460.384693
36-0.01727-0.12920.448818
37-0.017155-0.12840.449156
380.0037370.0280.488894
390.0024910.01860.492598
400.0555730.41590.339548
410.0467550.34990.363869
42-0.075427-0.56440.287354
43-0.09783-0.73210.233582
44-0.078575-0.5880.279446
45-0.002819-0.02110.491623
46-0.041126-0.30780.379703
47-0.013306-0.09960.460519
48-0.043557-0.3260.372837
49-0.015539-0.11630.453922
500.0421250.31520.376878
51-0.029083-0.21760.414252
520.0090160.06750.473225
53-0.028621-0.21420.415592
540.017020.12740.449554
55-0.039746-0.29740.383619
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')