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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 computationFri, 19 Dec 2008 08:23:40 -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/19/t1229700260wgj6jkpsewjqp1d.htm/, Retrieved Thu, 31 Oct 2024 22:53:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35182, Retrieved Thu, 31 Oct 2024 22:53:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact229
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 RMP   [(Partial) Autocorrelation Function] [Taak 10 Stap 4] [2008-12-03 16:24:10] [6fea0e9a9b3b29a63badf2c274e82506]
-   P     [(Partial) Autocorrelation Function] [Identification an...] [2008-12-08 19:12:52] [79c17183721a40a589db5f9f561947d8]
-   PD        [(Partial) Autocorrelation Function] [ACF/PACF elektric...] [2008-12-19 15:23:40] [1aceffc2fa350402d9e8f8edd757a2e8] [Current]
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Dataseries X:
97.57
97.74
97.92
98.19
98.23
98.41
98.59
98.71
99.14
99.62
100.18
100.66
101.19
101.75
102.2
102.87
98.81
97.6
96.68
95.96
98.89
99.05
99.2
99.11
99.19
99.77
100.70
100.78
100.53
101.01
100.92
101.10
103.11
102.99
102.31
102.61
103.68
104.72
107.66
108.87
108.12
107.61
106.42
105.61
105.71
105.49
105.57
105.18
106.09
106.34
108.47
116.87
121.08
123.27
124.18
125.60
126.57
127.18
128.04
128.55
129.67




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35182&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35182&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.233547-1.79390.038976
2-0.155931-1.19770.117906
30.0568080.43640.332086
4-0.255271-1.96080.027316
50.0701730.5390.295953
60.0400840.30790.379626
70.0863710.66340.254821
8-0.130318-1.0010.16046
90.0016010.01230.495114
10-0.031148-0.23930.40587
11-0.152927-1.17470.122426
120.1836221.41040.081832
130.0657340.50490.30775
14-0.013345-0.10250.459351
150.0354520.27230.393166
16-0.071992-0.5530.291182
17-0.040215-0.30890.379243
180.0268010.20590.418804
190.1361951.04610.149883
20-0.093239-0.71620.238351
21-0.005733-0.0440.482512
22-0.093611-0.7190.237476
23-0.010034-0.07710.469414
240.0682550.52430.301026
25-0.005701-0.04380.48261
260.0905170.69530.244806
27-0.053363-0.40990.341687
28-0.01517-0.11650.453816
29-0.021729-0.16690.434008
30-0.087704-0.67370.251576
310.2769312.12710.018799
32-0.11604-0.89130.188188
330.0407740.31320.377621
340.0024520.01880.492519
35-0.262356-2.01520.024224
360.104470.80250.212756
370.0112770.08660.465634
380.0683070.52470.300887
39-0.047626-0.36580.357903
400.0210810.16190.43596
410.0204190.15680.437953
42-0.010185-0.07820.468952
430.0370010.28420.388623
44-0.036562-0.28080.38991
450.0021040.01620.49358
460.0003510.00270.498928
47-0.011734-0.09010.464244
480.0078130.060.476174
49-0.001127-0.00870.496562
500.002650.02040.491915
51-0.002486-0.01910.492416
520.0021370.01640.493478
530.0003080.00240.499061
54-0.000944-0.00730.497119
550.0012590.00970.496159
56-0.0012-0.00920.49634
570.0003170.00240.499033
58-2.5e-05-2e-040.499924
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.233547 & -1.7939 & 0.038976 \tabularnewline
2 & -0.155931 & -1.1977 & 0.117906 \tabularnewline
3 & 0.056808 & 0.4364 & 0.332086 \tabularnewline
4 & -0.255271 & -1.9608 & 0.027316 \tabularnewline
5 & 0.070173 & 0.539 & 0.295953 \tabularnewline
6 & 0.040084 & 0.3079 & 0.379626 \tabularnewline
7 & 0.086371 & 0.6634 & 0.254821 \tabularnewline
8 & -0.130318 & -1.001 & 0.16046 \tabularnewline
9 & 0.001601 & 0.0123 & 0.495114 \tabularnewline
10 & -0.031148 & -0.2393 & 0.40587 \tabularnewline
11 & -0.152927 & -1.1747 & 0.122426 \tabularnewline
12 & 0.183622 & 1.4104 & 0.081832 \tabularnewline
13 & 0.065734 & 0.5049 & 0.30775 \tabularnewline
14 & -0.013345 & -0.1025 & 0.459351 \tabularnewline
15 & 0.035452 & 0.2723 & 0.393166 \tabularnewline
16 & -0.071992 & -0.553 & 0.291182 \tabularnewline
17 & -0.040215 & -0.3089 & 0.379243 \tabularnewline
18 & 0.026801 & 0.2059 & 0.418804 \tabularnewline
19 & 0.136195 & 1.0461 & 0.149883 \tabularnewline
20 & -0.093239 & -0.7162 & 0.238351 \tabularnewline
21 & -0.005733 & -0.044 & 0.482512 \tabularnewline
22 & -0.093611 & -0.719 & 0.237476 \tabularnewline
23 & -0.010034 & -0.0771 & 0.469414 \tabularnewline
24 & 0.068255 & 0.5243 & 0.301026 \tabularnewline
25 & -0.005701 & -0.0438 & 0.48261 \tabularnewline
26 & 0.090517 & 0.6953 & 0.244806 \tabularnewline
27 & -0.053363 & -0.4099 & 0.341687 \tabularnewline
28 & -0.01517 & -0.1165 & 0.453816 \tabularnewline
29 & -0.021729 & -0.1669 & 0.434008 \tabularnewline
30 & -0.087704 & -0.6737 & 0.251576 \tabularnewline
31 & 0.276931 & 2.1271 & 0.018799 \tabularnewline
32 & -0.11604 & -0.8913 & 0.188188 \tabularnewline
33 & 0.040774 & 0.3132 & 0.377621 \tabularnewline
34 & 0.002452 & 0.0188 & 0.492519 \tabularnewline
35 & -0.262356 & -2.0152 & 0.024224 \tabularnewline
36 & 0.10447 & 0.8025 & 0.212756 \tabularnewline
37 & 0.011277 & 0.0866 & 0.465634 \tabularnewline
38 & 0.068307 & 0.5247 & 0.300887 \tabularnewline
39 & -0.047626 & -0.3658 & 0.357903 \tabularnewline
40 & 0.021081 & 0.1619 & 0.43596 \tabularnewline
41 & 0.020419 & 0.1568 & 0.437953 \tabularnewline
42 & -0.010185 & -0.0782 & 0.468952 \tabularnewline
43 & 0.037001 & 0.2842 & 0.388623 \tabularnewline
44 & -0.036562 & -0.2808 & 0.38991 \tabularnewline
45 & 0.002104 & 0.0162 & 0.49358 \tabularnewline
46 & 0.000351 & 0.0027 & 0.498928 \tabularnewline
47 & -0.011734 & -0.0901 & 0.464244 \tabularnewline
48 & 0.007813 & 0.06 & 0.476174 \tabularnewline
49 & -0.001127 & -0.0087 & 0.496562 \tabularnewline
50 & 0.00265 & 0.0204 & 0.491915 \tabularnewline
51 & -0.002486 & -0.0191 & 0.492416 \tabularnewline
52 & 0.002137 & 0.0164 & 0.493478 \tabularnewline
53 & 0.000308 & 0.0024 & 0.499061 \tabularnewline
54 & -0.000944 & -0.0073 & 0.497119 \tabularnewline
55 & 0.001259 & 0.0097 & 0.496159 \tabularnewline
56 & -0.0012 & -0.0092 & 0.49634 \tabularnewline
57 & 0.000317 & 0.0024 & 0.499033 \tabularnewline
58 & -2.5e-05 & -2e-04 & 0.499924 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35182&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]-0.233547[/C][C]-1.7939[/C][C]0.038976[/C][/ROW]
[ROW][C]2[/C][C]-0.155931[/C][C]-1.1977[/C][C]0.117906[/C][/ROW]
[ROW][C]3[/C][C]0.056808[/C][C]0.4364[/C][C]0.332086[/C][/ROW]
[ROW][C]4[/C][C]-0.255271[/C][C]-1.9608[/C][C]0.027316[/C][/ROW]
[ROW][C]5[/C][C]0.070173[/C][C]0.539[/C][C]0.295953[/C][/ROW]
[ROW][C]6[/C][C]0.040084[/C][C]0.3079[/C][C]0.379626[/C][/ROW]
[ROW][C]7[/C][C]0.086371[/C][C]0.6634[/C][C]0.254821[/C][/ROW]
[ROW][C]8[/C][C]-0.130318[/C][C]-1.001[/C][C]0.16046[/C][/ROW]
[ROW][C]9[/C][C]0.001601[/C][C]0.0123[/C][C]0.495114[/C][/ROW]
[ROW][C]10[/C][C]-0.031148[/C][C]-0.2393[/C][C]0.40587[/C][/ROW]
[ROW][C]11[/C][C]-0.152927[/C][C]-1.1747[/C][C]0.122426[/C][/ROW]
[ROW][C]12[/C][C]0.183622[/C][C]1.4104[/C][C]0.081832[/C][/ROW]
[ROW][C]13[/C][C]0.065734[/C][C]0.5049[/C][C]0.30775[/C][/ROW]
[ROW][C]14[/C][C]-0.013345[/C][C]-0.1025[/C][C]0.459351[/C][/ROW]
[ROW][C]15[/C][C]0.035452[/C][C]0.2723[/C][C]0.393166[/C][/ROW]
[ROW][C]16[/C][C]-0.071992[/C][C]-0.553[/C][C]0.291182[/C][/ROW]
[ROW][C]17[/C][C]-0.040215[/C][C]-0.3089[/C][C]0.379243[/C][/ROW]
[ROW][C]18[/C][C]0.026801[/C][C]0.2059[/C][C]0.418804[/C][/ROW]
[ROW][C]19[/C][C]0.136195[/C][C]1.0461[/C][C]0.149883[/C][/ROW]
[ROW][C]20[/C][C]-0.093239[/C][C]-0.7162[/C][C]0.238351[/C][/ROW]
[ROW][C]21[/C][C]-0.005733[/C][C]-0.044[/C][C]0.482512[/C][/ROW]
[ROW][C]22[/C][C]-0.093611[/C][C]-0.719[/C][C]0.237476[/C][/ROW]
[ROW][C]23[/C][C]-0.010034[/C][C]-0.0771[/C][C]0.469414[/C][/ROW]
[ROW][C]24[/C][C]0.068255[/C][C]0.5243[/C][C]0.301026[/C][/ROW]
[ROW][C]25[/C][C]-0.005701[/C][C]-0.0438[/C][C]0.48261[/C][/ROW]
[ROW][C]26[/C][C]0.090517[/C][C]0.6953[/C][C]0.244806[/C][/ROW]
[ROW][C]27[/C][C]-0.053363[/C][C]-0.4099[/C][C]0.341687[/C][/ROW]
[ROW][C]28[/C][C]-0.01517[/C][C]-0.1165[/C][C]0.453816[/C][/ROW]
[ROW][C]29[/C][C]-0.021729[/C][C]-0.1669[/C][C]0.434008[/C][/ROW]
[ROW][C]30[/C][C]-0.087704[/C][C]-0.6737[/C][C]0.251576[/C][/ROW]
[ROW][C]31[/C][C]0.276931[/C][C]2.1271[/C][C]0.018799[/C][/ROW]
[ROW][C]32[/C][C]-0.11604[/C][C]-0.8913[/C][C]0.188188[/C][/ROW]
[ROW][C]33[/C][C]0.040774[/C][C]0.3132[/C][C]0.377621[/C][/ROW]
[ROW][C]34[/C][C]0.002452[/C][C]0.0188[/C][C]0.492519[/C][/ROW]
[ROW][C]35[/C][C]-0.262356[/C][C]-2.0152[/C][C]0.024224[/C][/ROW]
[ROW][C]36[/C][C]0.10447[/C][C]0.8025[/C][C]0.212756[/C][/ROW]
[ROW][C]37[/C][C]0.011277[/C][C]0.0866[/C][C]0.465634[/C][/ROW]
[ROW][C]38[/C][C]0.068307[/C][C]0.5247[/C][C]0.300887[/C][/ROW]
[ROW][C]39[/C][C]-0.047626[/C][C]-0.3658[/C][C]0.357903[/C][/ROW]
[ROW][C]40[/C][C]0.021081[/C][C]0.1619[/C][C]0.43596[/C][/ROW]
[ROW][C]41[/C][C]0.020419[/C][C]0.1568[/C][C]0.437953[/C][/ROW]
[ROW][C]42[/C][C]-0.010185[/C][C]-0.0782[/C][C]0.468952[/C][/ROW]
[ROW][C]43[/C][C]0.037001[/C][C]0.2842[/C][C]0.388623[/C][/ROW]
[ROW][C]44[/C][C]-0.036562[/C][C]-0.2808[/C][C]0.38991[/C][/ROW]
[ROW][C]45[/C][C]0.002104[/C][C]0.0162[/C][C]0.49358[/C][/ROW]
[ROW][C]46[/C][C]0.000351[/C][C]0.0027[/C][C]0.498928[/C][/ROW]
[ROW][C]47[/C][C]-0.011734[/C][C]-0.0901[/C][C]0.464244[/C][/ROW]
[ROW][C]48[/C][C]0.007813[/C][C]0.06[/C][C]0.476174[/C][/ROW]
[ROW][C]49[/C][C]-0.001127[/C][C]-0.0087[/C][C]0.496562[/C][/ROW]
[ROW][C]50[/C][C]0.00265[/C][C]0.0204[/C][C]0.491915[/C][/ROW]
[ROW][C]51[/C][C]-0.002486[/C][C]-0.0191[/C][C]0.492416[/C][/ROW]
[ROW][C]52[/C][C]0.002137[/C][C]0.0164[/C][C]0.493478[/C][/ROW]
[ROW][C]53[/C][C]0.000308[/C][C]0.0024[/C][C]0.499061[/C][/ROW]
[ROW][C]54[/C][C]-0.000944[/C][C]-0.0073[/C][C]0.497119[/C][/ROW]
[ROW][C]55[/C][C]0.001259[/C][C]0.0097[/C][C]0.496159[/C][/ROW]
[ROW][C]56[/C][C]-0.0012[/C][C]-0.0092[/C][C]0.49634[/C][/ROW]
[ROW][C]57[/C][C]0.000317[/C][C]0.0024[/C][C]0.499033[/C][/ROW]
[ROW][C]58[/C][C]-2.5e-05[/C][C]-2e-04[/C][C]0.499924[/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=35182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35182&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
1-0.233547-1.79390.038976
2-0.155931-1.19770.117906
30.0568080.43640.332086
4-0.255271-1.96080.027316
50.0701730.5390.295953
60.0400840.30790.379626
70.0863710.66340.254821
8-0.130318-1.0010.16046
90.0016010.01230.495114
10-0.031148-0.23930.40587
11-0.152927-1.17470.122426
120.1836221.41040.081832
130.0657340.50490.30775
14-0.013345-0.10250.459351
150.0354520.27230.393166
16-0.071992-0.5530.291182
17-0.040215-0.30890.379243
180.0268010.20590.418804
190.1361951.04610.149883
20-0.093239-0.71620.238351
21-0.005733-0.0440.482512
22-0.093611-0.7190.237476
23-0.010034-0.07710.469414
240.0682550.52430.301026
25-0.005701-0.04380.48261
260.0905170.69530.244806
27-0.053363-0.40990.341687
28-0.01517-0.11650.453816
29-0.021729-0.16690.434008
30-0.087704-0.67370.251576
310.2769312.12710.018799
32-0.11604-0.89130.188188
330.0407740.31320.377621
340.0024520.01880.492519
35-0.262356-2.01520.024224
360.104470.80250.212756
370.0112770.08660.465634
380.0683070.52470.300887
39-0.047626-0.36580.357903
400.0210810.16190.43596
410.0204190.15680.437953
42-0.010185-0.07820.468952
430.0370010.28420.388623
44-0.036562-0.28080.38991
450.0021040.01620.49358
460.0003510.00270.498928
47-0.011734-0.09010.464244
480.0078130.060.476174
49-0.001127-0.00870.496562
500.002650.02040.491915
51-0.002486-0.01910.492416
520.0021370.01640.493478
530.0003080.00240.499061
54-0.000944-0.00730.497119
550.0012590.00970.496159
56-0.0012-0.00920.49634
570.0003170.00240.499033
58-2.5e-05-2e-040.499924
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.233547-1.79390.038976
2-0.222618-1.710.046264
3-0.044188-0.33940.36775
4-0.318329-2.44510.008742
5-0.108066-0.83010.204922
6-0.111856-0.85920.196859
70.0642590.49360.311717
8-0.206984-1.58990.058604
9-0.067882-0.52140.302016
10-0.16693-1.28220.102391
11-0.248949-1.91220.030354
12-0.118572-0.91080.183063
13-0.047965-0.36840.356937
14-0.070634-0.54250.294742
15-0.05626-0.43210.333608
16-0.08564-0.65780.256609
17-0.090546-0.69550.244738
18-0.077125-0.59240.277919
190.0601740.46220.322818
20-0.079602-0.61140.27163
21-0.022215-0.17060.432547
22-0.198167-1.52210.066657
23-0.016399-0.1260.450095
24-0.082275-0.6320.264925
25-0.058008-0.44560.328769
26-0.037028-0.28440.388542
27-0.032506-0.24970.401851
28-0.05997-0.46060.323376
29-0.04987-0.38310.351527
30-0.176978-1.35940.089598
310.1917251.47270.073078
32-0.088439-0.67930.249799
330.1455741.11820.134012
340.0244220.18760.42592
35-0.044693-0.34330.366298
36-0.05978-0.45920.323897
370.0250650.19250.423994
38-0.034938-0.26840.394677
39-0.07141-0.54850.292706
40-0.063677-0.48910.313287
410.0465690.35770.36092
420.1025330.78760.21705
43-0.029588-0.22730.410501
44-0.036928-0.28360.388836
45-0.047177-0.36240.359183
46-0.114896-0.88250.190534
47-0.029325-0.22530.411281
48-0.023746-0.18240.427949
490.0056060.04310.4829
50-0.103917-0.79820.213978
510.0196590.1510.440243
52-0.071535-0.54950.292379
530.0750550.57650.283233
54-0.066073-0.50750.306842
55-0.001623-0.01250.495046
56-0.071794-0.55150.2917
57-0.094079-0.72260.236379
58-0.009879-0.07590.469884
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.233547 & -1.7939 & 0.038976 \tabularnewline
2 & -0.222618 & -1.71 & 0.046264 \tabularnewline
3 & -0.044188 & -0.3394 & 0.36775 \tabularnewline
4 & -0.318329 & -2.4451 & 0.008742 \tabularnewline
5 & -0.108066 & -0.8301 & 0.204922 \tabularnewline
6 & -0.111856 & -0.8592 & 0.196859 \tabularnewline
7 & 0.064259 & 0.4936 & 0.311717 \tabularnewline
8 & -0.206984 & -1.5899 & 0.058604 \tabularnewline
9 & -0.067882 & -0.5214 & 0.302016 \tabularnewline
10 & -0.16693 & -1.2822 & 0.102391 \tabularnewline
11 & -0.248949 & -1.9122 & 0.030354 \tabularnewline
12 & -0.118572 & -0.9108 & 0.183063 \tabularnewline
13 & -0.047965 & -0.3684 & 0.356937 \tabularnewline
14 & -0.070634 & -0.5425 & 0.294742 \tabularnewline
15 & -0.05626 & -0.4321 & 0.333608 \tabularnewline
16 & -0.08564 & -0.6578 & 0.256609 \tabularnewline
17 & -0.090546 & -0.6955 & 0.244738 \tabularnewline
18 & -0.077125 & -0.5924 & 0.277919 \tabularnewline
19 & 0.060174 & 0.4622 & 0.322818 \tabularnewline
20 & -0.079602 & -0.6114 & 0.27163 \tabularnewline
21 & -0.022215 & -0.1706 & 0.432547 \tabularnewline
22 & -0.198167 & -1.5221 & 0.066657 \tabularnewline
23 & -0.016399 & -0.126 & 0.450095 \tabularnewline
24 & -0.082275 & -0.632 & 0.264925 \tabularnewline
25 & -0.058008 & -0.4456 & 0.328769 \tabularnewline
26 & -0.037028 & -0.2844 & 0.388542 \tabularnewline
27 & -0.032506 & -0.2497 & 0.401851 \tabularnewline
28 & -0.05997 & -0.4606 & 0.323376 \tabularnewline
29 & -0.04987 & -0.3831 & 0.351527 \tabularnewline
30 & -0.176978 & -1.3594 & 0.089598 \tabularnewline
31 & 0.191725 & 1.4727 & 0.073078 \tabularnewline
32 & -0.088439 & -0.6793 & 0.249799 \tabularnewline
33 & 0.145574 & 1.1182 & 0.134012 \tabularnewline
34 & 0.024422 & 0.1876 & 0.42592 \tabularnewline
35 & -0.044693 & -0.3433 & 0.366298 \tabularnewline
36 & -0.05978 & -0.4592 & 0.323897 \tabularnewline
37 & 0.025065 & 0.1925 & 0.423994 \tabularnewline
38 & -0.034938 & -0.2684 & 0.394677 \tabularnewline
39 & -0.07141 & -0.5485 & 0.292706 \tabularnewline
40 & -0.063677 & -0.4891 & 0.313287 \tabularnewline
41 & 0.046569 & 0.3577 & 0.36092 \tabularnewline
42 & 0.102533 & 0.7876 & 0.21705 \tabularnewline
43 & -0.029588 & -0.2273 & 0.410501 \tabularnewline
44 & -0.036928 & -0.2836 & 0.388836 \tabularnewline
45 & -0.047177 & -0.3624 & 0.359183 \tabularnewline
46 & -0.114896 & -0.8825 & 0.190534 \tabularnewline
47 & -0.029325 & -0.2253 & 0.411281 \tabularnewline
48 & -0.023746 & -0.1824 & 0.427949 \tabularnewline
49 & 0.005606 & 0.0431 & 0.4829 \tabularnewline
50 & -0.103917 & -0.7982 & 0.213978 \tabularnewline
51 & 0.019659 & 0.151 & 0.440243 \tabularnewline
52 & -0.071535 & -0.5495 & 0.292379 \tabularnewline
53 & 0.075055 & 0.5765 & 0.283233 \tabularnewline
54 & -0.066073 & -0.5075 & 0.306842 \tabularnewline
55 & -0.001623 & -0.0125 & 0.495046 \tabularnewline
56 & -0.071794 & -0.5515 & 0.2917 \tabularnewline
57 & -0.094079 & -0.7226 & 0.236379 \tabularnewline
58 & -0.009879 & -0.0759 & 0.469884 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35182&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]-0.233547[/C][C]-1.7939[/C][C]0.038976[/C][/ROW]
[ROW][C]2[/C][C]-0.222618[/C][C]-1.71[/C][C]0.046264[/C][/ROW]
[ROW][C]3[/C][C]-0.044188[/C][C]-0.3394[/C][C]0.36775[/C][/ROW]
[ROW][C]4[/C][C]-0.318329[/C][C]-2.4451[/C][C]0.008742[/C][/ROW]
[ROW][C]5[/C][C]-0.108066[/C][C]-0.8301[/C][C]0.204922[/C][/ROW]
[ROW][C]6[/C][C]-0.111856[/C][C]-0.8592[/C][C]0.196859[/C][/ROW]
[ROW][C]7[/C][C]0.064259[/C][C]0.4936[/C][C]0.311717[/C][/ROW]
[ROW][C]8[/C][C]-0.206984[/C][C]-1.5899[/C][C]0.058604[/C][/ROW]
[ROW][C]9[/C][C]-0.067882[/C][C]-0.5214[/C][C]0.302016[/C][/ROW]
[ROW][C]10[/C][C]-0.16693[/C][C]-1.2822[/C][C]0.102391[/C][/ROW]
[ROW][C]11[/C][C]-0.248949[/C][C]-1.9122[/C][C]0.030354[/C][/ROW]
[ROW][C]12[/C][C]-0.118572[/C][C]-0.9108[/C][C]0.183063[/C][/ROW]
[ROW][C]13[/C][C]-0.047965[/C][C]-0.3684[/C][C]0.356937[/C][/ROW]
[ROW][C]14[/C][C]-0.070634[/C][C]-0.5425[/C][C]0.294742[/C][/ROW]
[ROW][C]15[/C][C]-0.05626[/C][C]-0.4321[/C][C]0.333608[/C][/ROW]
[ROW][C]16[/C][C]-0.08564[/C][C]-0.6578[/C][C]0.256609[/C][/ROW]
[ROW][C]17[/C][C]-0.090546[/C][C]-0.6955[/C][C]0.244738[/C][/ROW]
[ROW][C]18[/C][C]-0.077125[/C][C]-0.5924[/C][C]0.277919[/C][/ROW]
[ROW][C]19[/C][C]0.060174[/C][C]0.4622[/C][C]0.322818[/C][/ROW]
[ROW][C]20[/C][C]-0.079602[/C][C]-0.6114[/C][C]0.27163[/C][/ROW]
[ROW][C]21[/C][C]-0.022215[/C][C]-0.1706[/C][C]0.432547[/C][/ROW]
[ROW][C]22[/C][C]-0.198167[/C][C]-1.5221[/C][C]0.066657[/C][/ROW]
[ROW][C]23[/C][C]-0.016399[/C][C]-0.126[/C][C]0.450095[/C][/ROW]
[ROW][C]24[/C][C]-0.082275[/C][C]-0.632[/C][C]0.264925[/C][/ROW]
[ROW][C]25[/C][C]-0.058008[/C][C]-0.4456[/C][C]0.328769[/C][/ROW]
[ROW][C]26[/C][C]-0.037028[/C][C]-0.2844[/C][C]0.388542[/C][/ROW]
[ROW][C]27[/C][C]-0.032506[/C][C]-0.2497[/C][C]0.401851[/C][/ROW]
[ROW][C]28[/C][C]-0.05997[/C][C]-0.4606[/C][C]0.323376[/C][/ROW]
[ROW][C]29[/C][C]-0.04987[/C][C]-0.3831[/C][C]0.351527[/C][/ROW]
[ROW][C]30[/C][C]-0.176978[/C][C]-1.3594[/C][C]0.089598[/C][/ROW]
[ROW][C]31[/C][C]0.191725[/C][C]1.4727[/C][C]0.073078[/C][/ROW]
[ROW][C]32[/C][C]-0.088439[/C][C]-0.6793[/C][C]0.249799[/C][/ROW]
[ROW][C]33[/C][C]0.145574[/C][C]1.1182[/C][C]0.134012[/C][/ROW]
[ROW][C]34[/C][C]0.024422[/C][C]0.1876[/C][C]0.42592[/C][/ROW]
[ROW][C]35[/C][C]-0.044693[/C][C]-0.3433[/C][C]0.366298[/C][/ROW]
[ROW][C]36[/C][C]-0.05978[/C][C]-0.4592[/C][C]0.323897[/C][/ROW]
[ROW][C]37[/C][C]0.025065[/C][C]0.1925[/C][C]0.423994[/C][/ROW]
[ROW][C]38[/C][C]-0.034938[/C][C]-0.2684[/C][C]0.394677[/C][/ROW]
[ROW][C]39[/C][C]-0.07141[/C][C]-0.5485[/C][C]0.292706[/C][/ROW]
[ROW][C]40[/C][C]-0.063677[/C][C]-0.4891[/C][C]0.313287[/C][/ROW]
[ROW][C]41[/C][C]0.046569[/C][C]0.3577[/C][C]0.36092[/C][/ROW]
[ROW][C]42[/C][C]0.102533[/C][C]0.7876[/C][C]0.21705[/C][/ROW]
[ROW][C]43[/C][C]-0.029588[/C][C]-0.2273[/C][C]0.410501[/C][/ROW]
[ROW][C]44[/C][C]-0.036928[/C][C]-0.2836[/C][C]0.388836[/C][/ROW]
[ROW][C]45[/C][C]-0.047177[/C][C]-0.3624[/C][C]0.359183[/C][/ROW]
[ROW][C]46[/C][C]-0.114896[/C][C]-0.8825[/C][C]0.190534[/C][/ROW]
[ROW][C]47[/C][C]-0.029325[/C][C]-0.2253[/C][C]0.411281[/C][/ROW]
[ROW][C]48[/C][C]-0.023746[/C][C]-0.1824[/C][C]0.427949[/C][/ROW]
[ROW][C]49[/C][C]0.005606[/C][C]0.0431[/C][C]0.4829[/C][/ROW]
[ROW][C]50[/C][C]-0.103917[/C][C]-0.7982[/C][C]0.213978[/C][/ROW]
[ROW][C]51[/C][C]0.019659[/C][C]0.151[/C][C]0.440243[/C][/ROW]
[ROW][C]52[/C][C]-0.071535[/C][C]-0.5495[/C][C]0.292379[/C][/ROW]
[ROW][C]53[/C][C]0.075055[/C][C]0.5765[/C][C]0.283233[/C][/ROW]
[ROW][C]54[/C][C]-0.066073[/C][C]-0.5075[/C][C]0.306842[/C][/ROW]
[ROW][C]55[/C][C]-0.001623[/C][C]-0.0125[/C][C]0.495046[/C][/ROW]
[ROW][C]56[/C][C]-0.071794[/C][C]-0.5515[/C][C]0.2917[/C][/ROW]
[ROW][C]57[/C][C]-0.094079[/C][C]-0.7226[/C][C]0.236379[/C][/ROW]
[ROW][C]58[/C][C]-0.009879[/C][C]-0.0759[/C][C]0.469884[/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=35182&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35182&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
1-0.233547-1.79390.038976
2-0.222618-1.710.046264
3-0.044188-0.33940.36775
4-0.318329-2.44510.008742
5-0.108066-0.83010.204922
6-0.111856-0.85920.196859
70.0642590.49360.311717
8-0.206984-1.58990.058604
9-0.067882-0.52140.302016
10-0.16693-1.28220.102391
11-0.248949-1.91220.030354
12-0.118572-0.91080.183063
13-0.047965-0.36840.356937
14-0.070634-0.54250.294742
15-0.05626-0.43210.333608
16-0.08564-0.65780.256609
17-0.090546-0.69550.244738
18-0.077125-0.59240.277919
190.0601740.46220.322818
20-0.079602-0.61140.27163
21-0.022215-0.17060.432547
22-0.198167-1.52210.066657
23-0.016399-0.1260.450095
24-0.082275-0.6320.264925
25-0.058008-0.44560.328769
26-0.037028-0.28440.388542
27-0.032506-0.24970.401851
28-0.05997-0.46060.323376
29-0.04987-0.38310.351527
30-0.176978-1.35940.089598
310.1917251.47270.073078
32-0.088439-0.67930.249799
330.1455741.11820.134012
340.0244220.18760.42592
35-0.044693-0.34330.366298
36-0.05978-0.45920.323897
370.0250650.19250.423994
38-0.034938-0.26840.394677
39-0.07141-0.54850.292706
40-0.063677-0.48910.313287
410.0465690.35770.36092
420.1025330.78760.21705
43-0.029588-0.22730.410501
44-0.036928-0.28360.388836
45-0.047177-0.36240.359183
46-0.114896-0.88250.190534
47-0.029325-0.22530.411281
48-0.023746-0.18240.427949
490.0056060.04310.4829
50-0.103917-0.79820.213978
510.0196590.1510.440243
52-0.071535-0.54950.292379
530.0750550.57650.283233
54-0.066073-0.50750.306842
55-0.001623-0.01250.495046
56-0.071794-0.55150.2917
57-0.094079-0.72260.236379
58-0.009879-0.07590.469884
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 2 ; 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')