Free Statistics

of Irreproducible Research!

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 computationSat, 13 Dec 2008 06:20:33 -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/2008/Dec/13/t1229174478rmeh0ofm41ks0kk.htm/, Retrieved Sun, 19 May 2024 06:27:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33059, Retrieved Sun, 19 May 2024 06:27:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD  [(Partial) Autocorrelation Function] [ACF diesel] [2008-12-06 18:01:53] [8b0d202c3a0c4ea223fd8b8e731dacd8]
F   P       [(Partial) Autocorrelation Function] [step 3 ACF] [2008-12-13 13:20:33] [c33ddd06d9ea3933c8ac89c0e74c9b3a] [Current]
Feedback Forum
2008-12-13 13:42:24 [Ruben Jacobs] [reply
Er is nergens een significante autocorrelatie dus de ARMA-parameters, p,P,q en Q zijn allemaal 0.

Post a new message
Dataseries X:
0.84
0.76
0.77
0.76
0.77
0.78
0.79
0.78
0.76
0.78
0.76
0.74
0.73
0.72
0.71
0.73
0.75
0.75
0.72
0.72
0.72
0.74
0.78
0.74
0.74
0.75
0.78
0.81
0.75
0.7
0.71
0.71
0.73
0.74
0.74
0.75
0.74
0.74
0.73
0.76
0.8
0.83
0.81
0.83
0.88
0.89
0.93
0.91
0.9
0.86
0.88
0.93
0.98
0.97
1.03
1.06
1.06
1.09
1.04
1
1.04




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=33059&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=33059&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33059&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
10.1007180.78020.219183
2-0.101391-0.78540.217664
3-0.089502-0.69330.245405
4-0.121355-0.940.175491
50.1031850.79930.213643
60.1177660.91220.182654
7-0.070884-0.54910.2925
8-0.079183-0.61340.270981
90.0666220.51610.303858
100.1814721.40570.082489
110.193361.49780.069719
12-0.056528-0.43790.33153
130.0307310.2380.406329
14-0.026021-0.20160.420473
15-0.102961-0.79750.214144
16-0.022432-0.17380.431322
170.0675190.5230.30145
180.0040380.03130.487577
190.0650520.50390.308093
200.0688650.53340.297855
21-0.032301-0.25020.401641
220.0065050.05040.47999
23-0.154554-1.19720.117975
240.0329740.25540.399637
250.0004490.00350.498619
26-0.16061-1.24410.109154
270.0087480.06780.473099
280.0596680.46220.32281
290.0210860.16330.435404
300.2012111.55860.062178
31-0.058771-0.45520.325291
32-0.161956-1.25450.107262
33-0.078735-0.60990.272123
34-0.066846-0.51780.303255
350.14761.14330.128727
36-0.020188-0.15640.43813
37-0.066846-0.51780.303255
38-0.042171-0.32670.372532
39-0.025572-0.19810.421826
40-0.05406-0.41870.338448
410.0365630.28320.388992
42-0.072005-0.55780.289545
43-0.177882-1.37790.08668
44-0.077838-0.60290.274415
45-0.025572-0.19810.421826
460.0549570.42570.335926
470.00830.06430.474477
480.1137280.88090.190934
49-0.051368-0.39790.346059
50-0.071781-0.5560.290135
51-0.041723-0.32320.37384
520.0132350.10250.459345
53-0.110139-0.85310.198489
54-0.060565-0.46910.320336
550.0226560.17550.430642
56-0.035442-0.27450.39231
570.0740240.57340.284262
580.0778380.60290.274415
59-0.061687-0.47780.317256
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.100718 & 0.7802 & 0.219183 \tabularnewline
2 & -0.101391 & -0.7854 & 0.217664 \tabularnewline
3 & -0.089502 & -0.6933 & 0.245405 \tabularnewline
4 & -0.121355 & -0.94 & 0.175491 \tabularnewline
5 & 0.103185 & 0.7993 & 0.213643 \tabularnewline
6 & 0.117766 & 0.9122 & 0.182654 \tabularnewline
7 & -0.070884 & -0.5491 & 0.2925 \tabularnewline
8 & -0.079183 & -0.6134 & 0.270981 \tabularnewline
9 & 0.066622 & 0.5161 & 0.303858 \tabularnewline
10 & 0.181472 & 1.4057 & 0.082489 \tabularnewline
11 & 0.19336 & 1.4978 & 0.069719 \tabularnewline
12 & -0.056528 & -0.4379 & 0.33153 \tabularnewline
13 & 0.030731 & 0.238 & 0.406329 \tabularnewline
14 & -0.026021 & -0.2016 & 0.420473 \tabularnewline
15 & -0.102961 & -0.7975 & 0.214144 \tabularnewline
16 & -0.022432 & -0.1738 & 0.431322 \tabularnewline
17 & 0.067519 & 0.523 & 0.30145 \tabularnewline
18 & 0.004038 & 0.0313 & 0.487577 \tabularnewline
19 & 0.065052 & 0.5039 & 0.308093 \tabularnewline
20 & 0.068865 & 0.5334 & 0.297855 \tabularnewline
21 & -0.032301 & -0.2502 & 0.401641 \tabularnewline
22 & 0.006505 & 0.0504 & 0.47999 \tabularnewline
23 & -0.154554 & -1.1972 & 0.117975 \tabularnewline
24 & 0.032974 & 0.2554 & 0.399637 \tabularnewline
25 & 0.000449 & 0.0035 & 0.498619 \tabularnewline
26 & -0.16061 & -1.2441 & 0.109154 \tabularnewline
27 & 0.008748 & 0.0678 & 0.473099 \tabularnewline
28 & 0.059668 & 0.4622 & 0.32281 \tabularnewline
29 & 0.021086 & 0.1633 & 0.435404 \tabularnewline
30 & 0.201211 & 1.5586 & 0.062178 \tabularnewline
31 & -0.058771 & -0.4552 & 0.325291 \tabularnewline
32 & -0.161956 & -1.2545 & 0.107262 \tabularnewline
33 & -0.078735 & -0.6099 & 0.272123 \tabularnewline
34 & -0.066846 & -0.5178 & 0.303255 \tabularnewline
35 & 0.1476 & 1.1433 & 0.128727 \tabularnewline
36 & -0.020188 & -0.1564 & 0.43813 \tabularnewline
37 & -0.066846 & -0.5178 & 0.303255 \tabularnewline
38 & -0.042171 & -0.3267 & 0.372532 \tabularnewline
39 & -0.025572 & -0.1981 & 0.421826 \tabularnewline
40 & -0.05406 & -0.4187 & 0.338448 \tabularnewline
41 & 0.036563 & 0.2832 & 0.388992 \tabularnewline
42 & -0.072005 & -0.5578 & 0.289545 \tabularnewline
43 & -0.177882 & -1.3779 & 0.08668 \tabularnewline
44 & -0.077838 & -0.6029 & 0.274415 \tabularnewline
45 & -0.025572 & -0.1981 & 0.421826 \tabularnewline
46 & 0.054957 & 0.4257 & 0.335926 \tabularnewline
47 & 0.0083 & 0.0643 & 0.474477 \tabularnewline
48 & 0.113728 & 0.8809 & 0.190934 \tabularnewline
49 & -0.051368 & -0.3979 & 0.346059 \tabularnewline
50 & -0.071781 & -0.556 & 0.290135 \tabularnewline
51 & -0.041723 & -0.3232 & 0.37384 \tabularnewline
52 & 0.013235 & 0.1025 & 0.459345 \tabularnewline
53 & -0.110139 & -0.8531 & 0.198489 \tabularnewline
54 & -0.060565 & -0.4691 & 0.320336 \tabularnewline
55 & 0.022656 & 0.1755 & 0.430642 \tabularnewline
56 & -0.035442 & -0.2745 & 0.39231 \tabularnewline
57 & 0.074024 & 0.5734 & 0.284262 \tabularnewline
58 & 0.077838 & 0.6029 & 0.274415 \tabularnewline
59 & -0.061687 & -0.4778 & 0.317256 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33059&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]0.100718[/C][C]0.7802[/C][C]0.219183[/C][/ROW]
[ROW][C]2[/C][C]-0.101391[/C][C]-0.7854[/C][C]0.217664[/C][/ROW]
[ROW][C]3[/C][C]-0.089502[/C][C]-0.6933[/C][C]0.245405[/C][/ROW]
[ROW][C]4[/C][C]-0.121355[/C][C]-0.94[/C][C]0.175491[/C][/ROW]
[ROW][C]5[/C][C]0.103185[/C][C]0.7993[/C][C]0.213643[/C][/ROW]
[ROW][C]6[/C][C]0.117766[/C][C]0.9122[/C][C]0.182654[/C][/ROW]
[ROW][C]7[/C][C]-0.070884[/C][C]-0.5491[/C][C]0.2925[/C][/ROW]
[ROW][C]8[/C][C]-0.079183[/C][C]-0.6134[/C][C]0.270981[/C][/ROW]
[ROW][C]9[/C][C]0.066622[/C][C]0.5161[/C][C]0.303858[/C][/ROW]
[ROW][C]10[/C][C]0.181472[/C][C]1.4057[/C][C]0.082489[/C][/ROW]
[ROW][C]11[/C][C]0.19336[/C][C]1.4978[/C][C]0.069719[/C][/ROW]
[ROW][C]12[/C][C]-0.056528[/C][C]-0.4379[/C][C]0.33153[/C][/ROW]
[ROW][C]13[/C][C]0.030731[/C][C]0.238[/C][C]0.406329[/C][/ROW]
[ROW][C]14[/C][C]-0.026021[/C][C]-0.2016[/C][C]0.420473[/C][/ROW]
[ROW][C]15[/C][C]-0.102961[/C][C]-0.7975[/C][C]0.214144[/C][/ROW]
[ROW][C]16[/C][C]-0.022432[/C][C]-0.1738[/C][C]0.431322[/C][/ROW]
[ROW][C]17[/C][C]0.067519[/C][C]0.523[/C][C]0.30145[/C][/ROW]
[ROW][C]18[/C][C]0.004038[/C][C]0.0313[/C][C]0.487577[/C][/ROW]
[ROW][C]19[/C][C]0.065052[/C][C]0.5039[/C][C]0.308093[/C][/ROW]
[ROW][C]20[/C][C]0.068865[/C][C]0.5334[/C][C]0.297855[/C][/ROW]
[ROW][C]21[/C][C]-0.032301[/C][C]-0.2502[/C][C]0.401641[/C][/ROW]
[ROW][C]22[/C][C]0.006505[/C][C]0.0504[/C][C]0.47999[/C][/ROW]
[ROW][C]23[/C][C]-0.154554[/C][C]-1.1972[/C][C]0.117975[/C][/ROW]
[ROW][C]24[/C][C]0.032974[/C][C]0.2554[/C][C]0.399637[/C][/ROW]
[ROW][C]25[/C][C]0.000449[/C][C]0.0035[/C][C]0.498619[/C][/ROW]
[ROW][C]26[/C][C]-0.16061[/C][C]-1.2441[/C][C]0.109154[/C][/ROW]
[ROW][C]27[/C][C]0.008748[/C][C]0.0678[/C][C]0.473099[/C][/ROW]
[ROW][C]28[/C][C]0.059668[/C][C]0.4622[/C][C]0.32281[/C][/ROW]
[ROW][C]29[/C][C]0.021086[/C][C]0.1633[/C][C]0.435404[/C][/ROW]
[ROW][C]30[/C][C]0.201211[/C][C]1.5586[/C][C]0.062178[/C][/ROW]
[ROW][C]31[/C][C]-0.058771[/C][C]-0.4552[/C][C]0.325291[/C][/ROW]
[ROW][C]32[/C][C]-0.161956[/C][C]-1.2545[/C][C]0.107262[/C][/ROW]
[ROW][C]33[/C][C]-0.078735[/C][C]-0.6099[/C][C]0.272123[/C][/ROW]
[ROW][C]34[/C][C]-0.066846[/C][C]-0.5178[/C][C]0.303255[/C][/ROW]
[ROW][C]35[/C][C]0.1476[/C][C]1.1433[/C][C]0.128727[/C][/ROW]
[ROW][C]36[/C][C]-0.020188[/C][C]-0.1564[/C][C]0.43813[/C][/ROW]
[ROW][C]37[/C][C]-0.066846[/C][C]-0.5178[/C][C]0.303255[/C][/ROW]
[ROW][C]38[/C][C]-0.042171[/C][C]-0.3267[/C][C]0.372532[/C][/ROW]
[ROW][C]39[/C][C]-0.025572[/C][C]-0.1981[/C][C]0.421826[/C][/ROW]
[ROW][C]40[/C][C]-0.05406[/C][C]-0.4187[/C][C]0.338448[/C][/ROW]
[ROW][C]41[/C][C]0.036563[/C][C]0.2832[/C][C]0.388992[/C][/ROW]
[ROW][C]42[/C][C]-0.072005[/C][C]-0.5578[/C][C]0.289545[/C][/ROW]
[ROW][C]43[/C][C]-0.177882[/C][C]-1.3779[/C][C]0.08668[/C][/ROW]
[ROW][C]44[/C][C]-0.077838[/C][C]-0.6029[/C][C]0.274415[/C][/ROW]
[ROW][C]45[/C][C]-0.025572[/C][C]-0.1981[/C][C]0.421826[/C][/ROW]
[ROW][C]46[/C][C]0.054957[/C][C]0.4257[/C][C]0.335926[/C][/ROW]
[ROW][C]47[/C][C]0.0083[/C][C]0.0643[/C][C]0.474477[/C][/ROW]
[ROW][C]48[/C][C]0.113728[/C][C]0.8809[/C][C]0.190934[/C][/ROW]
[ROW][C]49[/C][C]-0.051368[/C][C]-0.3979[/C][C]0.346059[/C][/ROW]
[ROW][C]50[/C][C]-0.071781[/C][C]-0.556[/C][C]0.290135[/C][/ROW]
[ROW][C]51[/C][C]-0.041723[/C][C]-0.3232[/C][C]0.37384[/C][/ROW]
[ROW][C]52[/C][C]0.013235[/C][C]0.1025[/C][C]0.459345[/C][/ROW]
[ROW][C]53[/C][C]-0.110139[/C][C]-0.8531[/C][C]0.198489[/C][/ROW]
[ROW][C]54[/C][C]-0.060565[/C][C]-0.4691[/C][C]0.320336[/C][/ROW]
[ROW][C]55[/C][C]0.022656[/C][C]0.1755[/C][C]0.430642[/C][/ROW]
[ROW][C]56[/C][C]-0.035442[/C][C]-0.2745[/C][C]0.39231[/C][/ROW]
[ROW][C]57[/C][C]0.074024[/C][C]0.5734[/C][C]0.284262[/C][/ROW]
[ROW][C]58[/C][C]0.077838[/C][C]0.6029[/C][C]0.274415[/C][/ROW]
[ROW][C]59[/C][C]-0.061687[/C][C]-0.4778[/C][C]0.317256[/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=33059&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33059&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
10.1007180.78020.219183
2-0.101391-0.78540.217664
3-0.089502-0.69330.245405
4-0.121355-0.940.175491
50.1031850.79930.213643
60.1177660.91220.182654
7-0.070884-0.54910.2925
8-0.079183-0.61340.270981
90.0666220.51610.303858
100.1814721.40570.082489
110.193361.49780.069719
12-0.056528-0.43790.33153
130.0307310.2380.406329
14-0.026021-0.20160.420473
15-0.102961-0.79750.214144
16-0.022432-0.17380.431322
170.0675190.5230.30145
180.0040380.03130.487577
190.0650520.50390.308093
200.0688650.53340.297855
21-0.032301-0.25020.401641
220.0065050.05040.47999
23-0.154554-1.19720.117975
240.0329740.25540.399637
250.0004490.00350.498619
26-0.16061-1.24410.109154
270.0087480.06780.473099
280.0596680.46220.32281
290.0210860.16330.435404
300.2012111.55860.062178
31-0.058771-0.45520.325291
32-0.161956-1.25450.107262
33-0.078735-0.60990.272123
34-0.066846-0.51780.303255
350.14761.14330.128727
36-0.020188-0.15640.43813
37-0.066846-0.51780.303255
38-0.042171-0.32670.372532
39-0.025572-0.19810.421826
40-0.05406-0.41870.338448
410.0365630.28320.388992
42-0.072005-0.55780.289545
43-0.177882-1.37790.08668
44-0.077838-0.60290.274415
45-0.025572-0.19810.421826
460.0549570.42570.335926
470.00830.06430.474477
480.1137280.88090.190934
49-0.051368-0.39790.346059
50-0.071781-0.5560.290135
51-0.041723-0.32320.37384
520.0132350.10250.459345
53-0.110139-0.85310.198489
54-0.060565-0.46910.320336
550.0226560.17550.430642
56-0.035442-0.27450.39231
570.0740240.57340.284262
580.0778380.60290.274415
59-0.061687-0.47780.317256
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1007180.78020.219183
2-0.112678-0.87280.193126
3-0.068343-0.52940.299247
4-0.119025-0.9220.18012
50.1154010.89390.187475
60.0679920.52670.300184
7-0.089223-0.69110.246078
8-0.048234-0.37360.355003
90.1095350.84850.199778
100.168481.3050.098432
110.1409381.09170.139665
12-0.066764-0.51720.303475
130.1525251.18150.121043
140.0099840.07730.469308
15-0.120366-0.93230.177446
16-0.085006-0.65850.256383
170.108110.83740.202841
180.0039710.03080.487783
19-0.001117-0.00860.496564
200.0210940.16340.435378
21-0.004728-0.03660.485454
22-0.014051-0.10880.456846
23-0.230783-1.78760.039443
240.0651110.50430.307932
250.0292050.22620.410901
26-0.190211-1.47340.07294
27-0.032106-0.24870.402225
280.108690.84190.201591
290.0318330.24660.40304
300.0780960.60490.273755
31-0.11161-0.86450.19537
320.01720.13320.447229
33-0.02783-0.21560.415026
34-0.08007-0.62020.26873
350.1335491.03450.152534
360.0221570.17160.432153
37-0.013324-0.10320.459072
38-0.101859-0.7890.216611
39-0.013447-0.10420.458696
40-0.112571-0.8720.193349
41-0.0894-0.69250.245652
42-0.031569-0.24450.403828
43-0.091505-0.70880.240598
44-0.095979-0.74350.230054
45-0.034978-0.27090.393684
460.0093710.07260.471188
47-0.048033-0.37210.355578
480.1352721.04780.149464
49-0.067607-0.52370.301214
500.0414440.3210.374655
510.051810.40130.344806
520.0169580.13140.447967
53-0.005353-0.04150.483532
54-0.024252-0.18790.425811
550.0257380.19940.421326
560.0463950.35940.360289
57-0.011418-0.08840.46491
580.0404030.3130.377698
59-0.127792-0.98990.163105
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.100718 & 0.7802 & 0.219183 \tabularnewline
2 & -0.112678 & -0.8728 & 0.193126 \tabularnewline
3 & -0.068343 & -0.5294 & 0.299247 \tabularnewline
4 & -0.119025 & -0.922 & 0.18012 \tabularnewline
5 & 0.115401 & 0.8939 & 0.187475 \tabularnewline
6 & 0.067992 & 0.5267 & 0.300184 \tabularnewline
7 & -0.089223 & -0.6911 & 0.246078 \tabularnewline
8 & -0.048234 & -0.3736 & 0.355003 \tabularnewline
9 & 0.109535 & 0.8485 & 0.199778 \tabularnewline
10 & 0.16848 & 1.305 & 0.098432 \tabularnewline
11 & 0.140938 & 1.0917 & 0.139665 \tabularnewline
12 & -0.066764 & -0.5172 & 0.303475 \tabularnewline
13 & 0.152525 & 1.1815 & 0.121043 \tabularnewline
14 & 0.009984 & 0.0773 & 0.469308 \tabularnewline
15 & -0.120366 & -0.9323 & 0.177446 \tabularnewline
16 & -0.085006 & -0.6585 & 0.256383 \tabularnewline
17 & 0.10811 & 0.8374 & 0.202841 \tabularnewline
18 & 0.003971 & 0.0308 & 0.487783 \tabularnewline
19 & -0.001117 & -0.0086 & 0.496564 \tabularnewline
20 & 0.021094 & 0.1634 & 0.435378 \tabularnewline
21 & -0.004728 & -0.0366 & 0.485454 \tabularnewline
22 & -0.014051 & -0.1088 & 0.456846 \tabularnewline
23 & -0.230783 & -1.7876 & 0.039443 \tabularnewline
24 & 0.065111 & 0.5043 & 0.307932 \tabularnewline
25 & 0.029205 & 0.2262 & 0.410901 \tabularnewline
26 & -0.190211 & -1.4734 & 0.07294 \tabularnewline
27 & -0.032106 & -0.2487 & 0.402225 \tabularnewline
28 & 0.10869 & 0.8419 & 0.201591 \tabularnewline
29 & 0.031833 & 0.2466 & 0.40304 \tabularnewline
30 & 0.078096 & 0.6049 & 0.273755 \tabularnewline
31 & -0.11161 & -0.8645 & 0.19537 \tabularnewline
32 & 0.0172 & 0.1332 & 0.447229 \tabularnewline
33 & -0.02783 & -0.2156 & 0.415026 \tabularnewline
34 & -0.08007 & -0.6202 & 0.26873 \tabularnewline
35 & 0.133549 & 1.0345 & 0.152534 \tabularnewline
36 & 0.022157 & 0.1716 & 0.432153 \tabularnewline
37 & -0.013324 & -0.1032 & 0.459072 \tabularnewline
38 & -0.101859 & -0.789 & 0.216611 \tabularnewline
39 & -0.013447 & -0.1042 & 0.458696 \tabularnewline
40 & -0.112571 & -0.872 & 0.193349 \tabularnewline
41 & -0.0894 & -0.6925 & 0.245652 \tabularnewline
42 & -0.031569 & -0.2445 & 0.403828 \tabularnewline
43 & -0.091505 & -0.7088 & 0.240598 \tabularnewline
44 & -0.095979 & -0.7435 & 0.230054 \tabularnewline
45 & -0.034978 & -0.2709 & 0.393684 \tabularnewline
46 & 0.009371 & 0.0726 & 0.471188 \tabularnewline
47 & -0.048033 & -0.3721 & 0.355578 \tabularnewline
48 & 0.135272 & 1.0478 & 0.149464 \tabularnewline
49 & -0.067607 & -0.5237 & 0.301214 \tabularnewline
50 & 0.041444 & 0.321 & 0.374655 \tabularnewline
51 & 0.05181 & 0.4013 & 0.344806 \tabularnewline
52 & 0.016958 & 0.1314 & 0.447967 \tabularnewline
53 & -0.005353 & -0.0415 & 0.483532 \tabularnewline
54 & -0.024252 & -0.1879 & 0.425811 \tabularnewline
55 & 0.025738 & 0.1994 & 0.421326 \tabularnewline
56 & 0.046395 & 0.3594 & 0.360289 \tabularnewline
57 & -0.011418 & -0.0884 & 0.46491 \tabularnewline
58 & 0.040403 & 0.313 & 0.377698 \tabularnewline
59 & -0.127792 & -0.9899 & 0.163105 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33059&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]0.100718[/C][C]0.7802[/C][C]0.219183[/C][/ROW]
[ROW][C]2[/C][C]-0.112678[/C][C]-0.8728[/C][C]0.193126[/C][/ROW]
[ROW][C]3[/C][C]-0.068343[/C][C]-0.5294[/C][C]0.299247[/C][/ROW]
[ROW][C]4[/C][C]-0.119025[/C][C]-0.922[/C][C]0.18012[/C][/ROW]
[ROW][C]5[/C][C]0.115401[/C][C]0.8939[/C][C]0.187475[/C][/ROW]
[ROW][C]6[/C][C]0.067992[/C][C]0.5267[/C][C]0.300184[/C][/ROW]
[ROW][C]7[/C][C]-0.089223[/C][C]-0.6911[/C][C]0.246078[/C][/ROW]
[ROW][C]8[/C][C]-0.048234[/C][C]-0.3736[/C][C]0.355003[/C][/ROW]
[ROW][C]9[/C][C]0.109535[/C][C]0.8485[/C][C]0.199778[/C][/ROW]
[ROW][C]10[/C][C]0.16848[/C][C]1.305[/C][C]0.098432[/C][/ROW]
[ROW][C]11[/C][C]0.140938[/C][C]1.0917[/C][C]0.139665[/C][/ROW]
[ROW][C]12[/C][C]-0.066764[/C][C]-0.5172[/C][C]0.303475[/C][/ROW]
[ROW][C]13[/C][C]0.152525[/C][C]1.1815[/C][C]0.121043[/C][/ROW]
[ROW][C]14[/C][C]0.009984[/C][C]0.0773[/C][C]0.469308[/C][/ROW]
[ROW][C]15[/C][C]-0.120366[/C][C]-0.9323[/C][C]0.177446[/C][/ROW]
[ROW][C]16[/C][C]-0.085006[/C][C]-0.6585[/C][C]0.256383[/C][/ROW]
[ROW][C]17[/C][C]0.10811[/C][C]0.8374[/C][C]0.202841[/C][/ROW]
[ROW][C]18[/C][C]0.003971[/C][C]0.0308[/C][C]0.487783[/C][/ROW]
[ROW][C]19[/C][C]-0.001117[/C][C]-0.0086[/C][C]0.496564[/C][/ROW]
[ROW][C]20[/C][C]0.021094[/C][C]0.1634[/C][C]0.435378[/C][/ROW]
[ROW][C]21[/C][C]-0.004728[/C][C]-0.0366[/C][C]0.485454[/C][/ROW]
[ROW][C]22[/C][C]-0.014051[/C][C]-0.1088[/C][C]0.456846[/C][/ROW]
[ROW][C]23[/C][C]-0.230783[/C][C]-1.7876[/C][C]0.039443[/C][/ROW]
[ROW][C]24[/C][C]0.065111[/C][C]0.5043[/C][C]0.307932[/C][/ROW]
[ROW][C]25[/C][C]0.029205[/C][C]0.2262[/C][C]0.410901[/C][/ROW]
[ROW][C]26[/C][C]-0.190211[/C][C]-1.4734[/C][C]0.07294[/C][/ROW]
[ROW][C]27[/C][C]-0.032106[/C][C]-0.2487[/C][C]0.402225[/C][/ROW]
[ROW][C]28[/C][C]0.10869[/C][C]0.8419[/C][C]0.201591[/C][/ROW]
[ROW][C]29[/C][C]0.031833[/C][C]0.2466[/C][C]0.40304[/C][/ROW]
[ROW][C]30[/C][C]0.078096[/C][C]0.6049[/C][C]0.273755[/C][/ROW]
[ROW][C]31[/C][C]-0.11161[/C][C]-0.8645[/C][C]0.19537[/C][/ROW]
[ROW][C]32[/C][C]0.0172[/C][C]0.1332[/C][C]0.447229[/C][/ROW]
[ROW][C]33[/C][C]-0.02783[/C][C]-0.2156[/C][C]0.415026[/C][/ROW]
[ROW][C]34[/C][C]-0.08007[/C][C]-0.6202[/C][C]0.26873[/C][/ROW]
[ROW][C]35[/C][C]0.133549[/C][C]1.0345[/C][C]0.152534[/C][/ROW]
[ROW][C]36[/C][C]0.022157[/C][C]0.1716[/C][C]0.432153[/C][/ROW]
[ROW][C]37[/C][C]-0.013324[/C][C]-0.1032[/C][C]0.459072[/C][/ROW]
[ROW][C]38[/C][C]-0.101859[/C][C]-0.789[/C][C]0.216611[/C][/ROW]
[ROW][C]39[/C][C]-0.013447[/C][C]-0.1042[/C][C]0.458696[/C][/ROW]
[ROW][C]40[/C][C]-0.112571[/C][C]-0.872[/C][C]0.193349[/C][/ROW]
[ROW][C]41[/C][C]-0.0894[/C][C]-0.6925[/C][C]0.245652[/C][/ROW]
[ROW][C]42[/C][C]-0.031569[/C][C]-0.2445[/C][C]0.403828[/C][/ROW]
[ROW][C]43[/C][C]-0.091505[/C][C]-0.7088[/C][C]0.240598[/C][/ROW]
[ROW][C]44[/C][C]-0.095979[/C][C]-0.7435[/C][C]0.230054[/C][/ROW]
[ROW][C]45[/C][C]-0.034978[/C][C]-0.2709[/C][C]0.393684[/C][/ROW]
[ROW][C]46[/C][C]0.009371[/C][C]0.0726[/C][C]0.471188[/C][/ROW]
[ROW][C]47[/C][C]-0.048033[/C][C]-0.3721[/C][C]0.355578[/C][/ROW]
[ROW][C]48[/C][C]0.135272[/C][C]1.0478[/C][C]0.149464[/C][/ROW]
[ROW][C]49[/C][C]-0.067607[/C][C]-0.5237[/C][C]0.301214[/C][/ROW]
[ROW][C]50[/C][C]0.041444[/C][C]0.321[/C][C]0.374655[/C][/ROW]
[ROW][C]51[/C][C]0.05181[/C][C]0.4013[/C][C]0.344806[/C][/ROW]
[ROW][C]52[/C][C]0.016958[/C][C]0.1314[/C][C]0.447967[/C][/ROW]
[ROW][C]53[/C][C]-0.005353[/C][C]-0.0415[/C][C]0.483532[/C][/ROW]
[ROW][C]54[/C][C]-0.024252[/C][C]-0.1879[/C][C]0.425811[/C][/ROW]
[ROW][C]55[/C][C]0.025738[/C][C]0.1994[/C][C]0.421326[/C][/ROW]
[ROW][C]56[/C][C]0.046395[/C][C]0.3594[/C][C]0.360289[/C][/ROW]
[ROW][C]57[/C][C]-0.011418[/C][C]-0.0884[/C][C]0.46491[/C][/ROW]
[ROW][C]58[/C][C]0.040403[/C][C]0.313[/C][C]0.377698[/C][/ROW]
[ROW][C]59[/C][C]-0.127792[/C][C]-0.9899[/C][C]0.163105[/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=33059&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33059&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
10.1007180.78020.219183
2-0.112678-0.87280.193126
3-0.068343-0.52940.299247
4-0.119025-0.9220.18012
50.1154010.89390.187475
60.0679920.52670.300184
7-0.089223-0.69110.246078
8-0.048234-0.37360.355003
90.1095350.84850.199778
100.168481.3050.098432
110.1409381.09170.139665
12-0.066764-0.51720.303475
130.1525251.18150.121043
140.0099840.07730.469308
15-0.120366-0.93230.177446
16-0.085006-0.65850.256383
170.108110.83740.202841
180.0039710.03080.487783
19-0.001117-0.00860.496564
200.0210940.16340.435378
21-0.004728-0.03660.485454
22-0.014051-0.10880.456846
23-0.230783-1.78760.039443
240.0651110.50430.307932
250.0292050.22620.410901
26-0.190211-1.47340.07294
27-0.032106-0.24870.402225
280.108690.84190.201591
290.0318330.24660.40304
300.0780960.60490.273755
31-0.11161-0.86450.19537
320.01720.13320.447229
33-0.02783-0.21560.415026
34-0.08007-0.62020.26873
350.1335491.03450.152534
360.0221570.17160.432153
37-0.013324-0.10320.459072
38-0.101859-0.7890.216611
39-0.013447-0.10420.458696
40-0.112571-0.8720.193349
41-0.0894-0.69250.245652
42-0.031569-0.24450.403828
43-0.091505-0.70880.240598
44-0.095979-0.74350.230054
45-0.034978-0.27090.393684
460.0093710.07260.471188
47-0.048033-0.37210.355578
480.1352721.04780.149464
49-0.067607-0.52370.301214
500.0414440.3210.374655
510.051810.40130.344806
520.0169580.13140.447967
53-0.005353-0.04150.483532
54-0.024252-0.18790.425811
550.0257380.19940.421326
560.0463950.35940.360289
57-0.011418-0.08840.46491
580.0404030.3130.377698
59-0.127792-0.98990.163105
60NANANA



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')