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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, 11 Dec 2009 07:11:12 -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/11/t1260540884jps71oklhikay29.htm/, Retrieved Sun, 28 Apr 2024 20:58:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66215, Retrieved Sun, 28 Apr 2024 20:58:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbhschhwsstpaper
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [shw-ws4p1] [2009-10-28 17:17:04] [2663058f2a5dda519058ac6b2228468f]
- RMPD    [(Partial) Autocorrelation Function] [Paper: ACF & PACF] [2009-12-11 14:11:12] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
128.6
128.9
129.06
129.23
129.27
129.33
129.35
129.31
129.4
129.49
129.47
129.46
129.45
129.28
129.2
129.25
129.14
129.11
129.02
129.08
128.99
129.11
129.08
129.19
129.23
129.25
129.31
129.33
129.39
129.55
129.43
129.45
129.57
129.76
129.92
130.08
130.41
130.84
131.24
131.49
131.74
132.34
133.5
134.43
136.5
137.41
138.02
138.15
138.24
138.2
138.31
138.65
139.3
139.8
140.52
141.57
141.77
141.66
141.36
141.17




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=66215&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=66215&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66215&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
10.9566467.41020
20.9052677.01220
30.8458846.55220
40.7819736.05710
50.7166385.55110
60.6569025.08832e-06
70.5999224.6479e-06
80.5433164.20854.4e-05
90.4879093.77930.000182
100.4312333.34030.000722
110.3710192.87390.0028
120.3064592.37380.010412
130.239971.85880.033981
140.1721271.33330.093738
150.1077820.83490.20355
160.0496980.3850.350815
170.0058750.04550.481926
18-0.031998-0.24790.402546
19-0.062531-0.48440.314945
20-0.089152-0.69060.246249
21-0.11465-0.88810.189024
22-0.138269-1.0710.144223
23-0.159152-1.23280.111233
24-0.176745-1.36910.088041
25-0.191587-1.4840.071519
26-0.20507-1.58850.058719
27-0.217061-1.68130.048947
28-0.227567-1.76270.041519
29-0.236829-1.83450.035772
30-0.245364-1.90060.031082
31-0.25501-1.97530.02642
32-0.263291-2.03940.022908
33-0.270796-2.09760.020082
34-0.277711-2.15110.017751
35-0.283898-2.19910.01587
36-0.289682-2.24390.014272
37-0.29447-2.2810.013058
38-0.297234-2.30240.0124
39-0.299103-2.31680.011972
40-0.29956-2.32040.011869
41-0.300368-2.32660.011689
42-0.299471-2.31970.011889
43-0.29613-2.29380.012659
44-0.290847-2.25290.013968
45-0.280262-2.17090.016953
46-0.26674-2.06620.021569
47-0.252099-1.95280.027759
48-0.238466-1.84720.034829
49-0.224713-1.74060.043438
50-0.211363-1.63720.053411
51-0.198104-1.53450.065081
52-0.183481-1.42120.080213
53-0.166518-1.28980.101028
54-0.148602-1.15110.127136
55-0.128524-0.99550.161735
56-0.104679-0.81080.210332
57-0.079812-0.61820.269385
58-0.053936-0.41780.338798
59-0.027776-0.21520.415189
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.956646 & 7.4102 & 0 \tabularnewline
2 & 0.905267 & 7.0122 & 0 \tabularnewline
3 & 0.845884 & 6.5522 & 0 \tabularnewline
4 & 0.781973 & 6.0571 & 0 \tabularnewline
5 & 0.716638 & 5.5511 & 0 \tabularnewline
6 & 0.656902 & 5.0883 & 2e-06 \tabularnewline
7 & 0.599922 & 4.647 & 9e-06 \tabularnewline
8 & 0.543316 & 4.2085 & 4.4e-05 \tabularnewline
9 & 0.487909 & 3.7793 & 0.000182 \tabularnewline
10 & 0.431233 & 3.3403 & 0.000722 \tabularnewline
11 & 0.371019 & 2.8739 & 0.0028 \tabularnewline
12 & 0.306459 & 2.3738 & 0.010412 \tabularnewline
13 & 0.23997 & 1.8588 & 0.033981 \tabularnewline
14 & 0.172127 & 1.3333 & 0.093738 \tabularnewline
15 & 0.107782 & 0.8349 & 0.20355 \tabularnewline
16 & 0.049698 & 0.385 & 0.350815 \tabularnewline
17 & 0.005875 & 0.0455 & 0.481926 \tabularnewline
18 & -0.031998 & -0.2479 & 0.402546 \tabularnewline
19 & -0.062531 & -0.4844 & 0.314945 \tabularnewline
20 & -0.089152 & -0.6906 & 0.246249 \tabularnewline
21 & -0.11465 & -0.8881 & 0.189024 \tabularnewline
22 & -0.138269 & -1.071 & 0.144223 \tabularnewline
23 & -0.159152 & -1.2328 & 0.111233 \tabularnewline
24 & -0.176745 & -1.3691 & 0.088041 \tabularnewline
25 & -0.191587 & -1.484 & 0.071519 \tabularnewline
26 & -0.20507 & -1.5885 & 0.058719 \tabularnewline
27 & -0.217061 & -1.6813 & 0.048947 \tabularnewline
28 & -0.227567 & -1.7627 & 0.041519 \tabularnewline
29 & -0.236829 & -1.8345 & 0.035772 \tabularnewline
30 & -0.245364 & -1.9006 & 0.031082 \tabularnewline
31 & -0.25501 & -1.9753 & 0.02642 \tabularnewline
32 & -0.263291 & -2.0394 & 0.022908 \tabularnewline
33 & -0.270796 & -2.0976 & 0.020082 \tabularnewline
34 & -0.277711 & -2.1511 & 0.017751 \tabularnewline
35 & -0.283898 & -2.1991 & 0.01587 \tabularnewline
36 & -0.289682 & -2.2439 & 0.014272 \tabularnewline
37 & -0.29447 & -2.281 & 0.013058 \tabularnewline
38 & -0.297234 & -2.3024 & 0.0124 \tabularnewline
39 & -0.299103 & -2.3168 & 0.011972 \tabularnewline
40 & -0.29956 & -2.3204 & 0.011869 \tabularnewline
41 & -0.300368 & -2.3266 & 0.011689 \tabularnewline
42 & -0.299471 & -2.3197 & 0.011889 \tabularnewline
43 & -0.29613 & -2.2938 & 0.012659 \tabularnewline
44 & -0.290847 & -2.2529 & 0.013968 \tabularnewline
45 & -0.280262 & -2.1709 & 0.016953 \tabularnewline
46 & -0.26674 & -2.0662 & 0.021569 \tabularnewline
47 & -0.252099 & -1.9528 & 0.027759 \tabularnewline
48 & -0.238466 & -1.8472 & 0.034829 \tabularnewline
49 & -0.224713 & -1.7406 & 0.043438 \tabularnewline
50 & -0.211363 & -1.6372 & 0.053411 \tabularnewline
51 & -0.198104 & -1.5345 & 0.065081 \tabularnewline
52 & -0.183481 & -1.4212 & 0.080213 \tabularnewline
53 & -0.166518 & -1.2898 & 0.101028 \tabularnewline
54 & -0.148602 & -1.1511 & 0.127136 \tabularnewline
55 & -0.128524 & -0.9955 & 0.161735 \tabularnewline
56 & -0.104679 & -0.8108 & 0.210332 \tabularnewline
57 & -0.079812 & -0.6182 & 0.269385 \tabularnewline
58 & -0.053936 & -0.4178 & 0.338798 \tabularnewline
59 & -0.027776 & -0.2152 & 0.415189 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66215&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]0.956646[/C][C]7.4102[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.905267[/C][C]7.0122[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.845884[/C][C]6.5522[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.781973[/C][C]6.0571[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.716638[/C][C]5.5511[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.656902[/C][C]5.0883[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.599922[/C][C]4.647[/C][C]9e-06[/C][/ROW]
[ROW][C]8[/C][C]0.543316[/C][C]4.2085[/C][C]4.4e-05[/C][/ROW]
[ROW][C]9[/C][C]0.487909[/C][C]3.7793[/C][C]0.000182[/C][/ROW]
[ROW][C]10[/C][C]0.431233[/C][C]3.3403[/C][C]0.000722[/C][/ROW]
[ROW][C]11[/C][C]0.371019[/C][C]2.8739[/C][C]0.0028[/C][/ROW]
[ROW][C]12[/C][C]0.306459[/C][C]2.3738[/C][C]0.010412[/C][/ROW]
[ROW][C]13[/C][C]0.23997[/C][C]1.8588[/C][C]0.033981[/C][/ROW]
[ROW][C]14[/C][C]0.172127[/C][C]1.3333[/C][C]0.093738[/C][/ROW]
[ROW][C]15[/C][C]0.107782[/C][C]0.8349[/C][C]0.20355[/C][/ROW]
[ROW][C]16[/C][C]0.049698[/C][C]0.385[/C][C]0.350815[/C][/ROW]
[ROW][C]17[/C][C]0.005875[/C][C]0.0455[/C][C]0.481926[/C][/ROW]
[ROW][C]18[/C][C]-0.031998[/C][C]-0.2479[/C][C]0.402546[/C][/ROW]
[ROW][C]19[/C][C]-0.062531[/C][C]-0.4844[/C][C]0.314945[/C][/ROW]
[ROW][C]20[/C][C]-0.089152[/C][C]-0.6906[/C][C]0.246249[/C][/ROW]
[ROW][C]21[/C][C]-0.11465[/C][C]-0.8881[/C][C]0.189024[/C][/ROW]
[ROW][C]22[/C][C]-0.138269[/C][C]-1.071[/C][C]0.144223[/C][/ROW]
[ROW][C]23[/C][C]-0.159152[/C][C]-1.2328[/C][C]0.111233[/C][/ROW]
[ROW][C]24[/C][C]-0.176745[/C][C]-1.3691[/C][C]0.088041[/C][/ROW]
[ROW][C]25[/C][C]-0.191587[/C][C]-1.484[/C][C]0.071519[/C][/ROW]
[ROW][C]26[/C][C]-0.20507[/C][C]-1.5885[/C][C]0.058719[/C][/ROW]
[ROW][C]27[/C][C]-0.217061[/C][C]-1.6813[/C][C]0.048947[/C][/ROW]
[ROW][C]28[/C][C]-0.227567[/C][C]-1.7627[/C][C]0.041519[/C][/ROW]
[ROW][C]29[/C][C]-0.236829[/C][C]-1.8345[/C][C]0.035772[/C][/ROW]
[ROW][C]30[/C][C]-0.245364[/C][C]-1.9006[/C][C]0.031082[/C][/ROW]
[ROW][C]31[/C][C]-0.25501[/C][C]-1.9753[/C][C]0.02642[/C][/ROW]
[ROW][C]32[/C][C]-0.263291[/C][C]-2.0394[/C][C]0.022908[/C][/ROW]
[ROW][C]33[/C][C]-0.270796[/C][C]-2.0976[/C][C]0.020082[/C][/ROW]
[ROW][C]34[/C][C]-0.277711[/C][C]-2.1511[/C][C]0.017751[/C][/ROW]
[ROW][C]35[/C][C]-0.283898[/C][C]-2.1991[/C][C]0.01587[/C][/ROW]
[ROW][C]36[/C][C]-0.289682[/C][C]-2.2439[/C][C]0.014272[/C][/ROW]
[ROW][C]37[/C][C]-0.29447[/C][C]-2.281[/C][C]0.013058[/C][/ROW]
[ROW][C]38[/C][C]-0.297234[/C][C]-2.3024[/C][C]0.0124[/C][/ROW]
[ROW][C]39[/C][C]-0.299103[/C][C]-2.3168[/C][C]0.011972[/C][/ROW]
[ROW][C]40[/C][C]-0.29956[/C][C]-2.3204[/C][C]0.011869[/C][/ROW]
[ROW][C]41[/C][C]-0.300368[/C][C]-2.3266[/C][C]0.011689[/C][/ROW]
[ROW][C]42[/C][C]-0.299471[/C][C]-2.3197[/C][C]0.011889[/C][/ROW]
[ROW][C]43[/C][C]-0.29613[/C][C]-2.2938[/C][C]0.012659[/C][/ROW]
[ROW][C]44[/C][C]-0.290847[/C][C]-2.2529[/C][C]0.013968[/C][/ROW]
[ROW][C]45[/C][C]-0.280262[/C][C]-2.1709[/C][C]0.016953[/C][/ROW]
[ROW][C]46[/C][C]-0.26674[/C][C]-2.0662[/C][C]0.021569[/C][/ROW]
[ROW][C]47[/C][C]-0.252099[/C][C]-1.9528[/C][C]0.027759[/C][/ROW]
[ROW][C]48[/C][C]-0.238466[/C][C]-1.8472[/C][C]0.034829[/C][/ROW]
[ROW][C]49[/C][C]-0.224713[/C][C]-1.7406[/C][C]0.043438[/C][/ROW]
[ROW][C]50[/C][C]-0.211363[/C][C]-1.6372[/C][C]0.053411[/C][/ROW]
[ROW][C]51[/C][C]-0.198104[/C][C]-1.5345[/C][C]0.065081[/C][/ROW]
[ROW][C]52[/C][C]-0.183481[/C][C]-1.4212[/C][C]0.080213[/C][/ROW]
[ROW][C]53[/C][C]-0.166518[/C][C]-1.2898[/C][C]0.101028[/C][/ROW]
[ROW][C]54[/C][C]-0.148602[/C][C]-1.1511[/C][C]0.127136[/C][/ROW]
[ROW][C]55[/C][C]-0.128524[/C][C]-0.9955[/C][C]0.161735[/C][/ROW]
[ROW][C]56[/C][C]-0.104679[/C][C]-0.8108[/C][C]0.210332[/C][/ROW]
[ROW][C]57[/C][C]-0.079812[/C][C]-0.6182[/C][C]0.269385[/C][/ROW]
[ROW][C]58[/C][C]-0.053936[/C][C]-0.4178[/C][C]0.338798[/C][/ROW]
[ROW][C]59[/C][C]-0.027776[/C][C]-0.2152[/C][C]0.415189[/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=66215&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66215&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
10.9566467.41020
20.9052677.01220
30.8458846.55220
40.7819736.05710
50.7166385.55110
60.6569025.08832e-06
70.5999224.6479e-06
80.5433164.20854.4e-05
90.4879093.77930.000182
100.4312333.34030.000722
110.3710192.87390.0028
120.3064592.37380.010412
130.239971.85880.033981
140.1721271.33330.093738
150.1077820.83490.20355
160.0496980.3850.350815
170.0058750.04550.481926
18-0.031998-0.24790.402546
19-0.062531-0.48440.314945
20-0.089152-0.69060.246249
21-0.11465-0.88810.189024
22-0.138269-1.0710.144223
23-0.159152-1.23280.111233
24-0.176745-1.36910.088041
25-0.191587-1.4840.071519
26-0.20507-1.58850.058719
27-0.217061-1.68130.048947
28-0.227567-1.76270.041519
29-0.236829-1.83450.035772
30-0.245364-1.90060.031082
31-0.25501-1.97530.02642
32-0.263291-2.03940.022908
33-0.270796-2.09760.020082
34-0.277711-2.15110.017751
35-0.283898-2.19910.01587
36-0.289682-2.24390.014272
37-0.29447-2.2810.013058
38-0.297234-2.30240.0124
39-0.299103-2.31680.011972
40-0.29956-2.32040.011869
41-0.300368-2.32660.011689
42-0.299471-2.31970.011889
43-0.29613-2.29380.012659
44-0.290847-2.25290.013968
45-0.280262-2.17090.016953
46-0.26674-2.06620.021569
47-0.252099-1.95280.027759
48-0.238466-1.84720.034829
49-0.224713-1.74060.043438
50-0.211363-1.63720.053411
51-0.198104-1.53450.065081
52-0.183481-1.42120.080213
53-0.166518-1.28980.101028
54-0.148602-1.15110.127136
55-0.128524-0.99550.161735
56-0.104679-0.81080.210332
57-0.079812-0.61820.269385
58-0.053936-0.41780.338798
59-0.027776-0.21520.415189
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9566467.41020
2-0.116769-0.90450.184678
3-0.114184-0.88450.189988
4-0.071972-0.55750.289632
5-0.038772-0.30030.382484
60.0388230.30070.382334
7-0.009506-0.07360.470774
8-0.046356-0.35910.3604
9-0.033214-0.25730.398924
10-0.058479-0.4530.326099
11-0.07792-0.60360.274203
12-0.086007-0.66620.253915
13-0.059087-0.45770.324416
14-0.05572-0.43160.333788
15-0.006661-0.05160.479512
160.012680.09820.461042
170.1000420.77490.220714
18-0.011397-0.08830.464975
190.0059480.04610.481701
20-0.020356-0.15770.437619
21-0.036938-0.28610.387887
22-0.003088-0.02390.4905
230.0046190.03580.485789
240.007390.05720.47727
25-0.005097-0.03950.484319
26-0.039132-0.30310.381427
27-0.040221-0.31160.378231
28-0.038861-0.3010.382221
29-0.034265-0.26540.395799
30-0.03568-0.27640.391606
31-0.045951-0.35590.361568
32-0.00634-0.04910.480498
33-0.002577-0.020.492071
34-0.018915-0.14650.442004
35-0.017811-0.1380.445366
36-0.031094-0.24090.405244
37-0.020202-0.15650.438088
380.0026260.02030.49192
39-0.010191-0.07890.46867
40-0.000389-0.0030.498804
41-0.02587-0.20040.420926
42-0.006123-0.04740.481163
430.0034020.02640.489532
44-0.007727-0.05990.476236
450.0343270.26590.395615
460.0031330.02430.49036
47-0.019457-0.15070.440353
48-0.033173-0.2570.399046
49-0.016585-0.12850.449105
50-0.012806-0.09920.460656
51-0.008204-0.06350.474771
520.0028540.02210.491218
530.0137190.10630.457861
54-0.001515-0.01170.495338
550.010570.08190.46751
560.0358540.27770.39109
570.0019260.01490.494072
580.0135960.10530.458238
590.0142470.11040.456248
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.956646 & 7.4102 & 0 \tabularnewline
2 & -0.116769 & -0.9045 & 0.184678 \tabularnewline
3 & -0.114184 & -0.8845 & 0.189988 \tabularnewline
4 & -0.071972 & -0.5575 & 0.289632 \tabularnewline
5 & -0.038772 & -0.3003 & 0.382484 \tabularnewline
6 & 0.038823 & 0.3007 & 0.382334 \tabularnewline
7 & -0.009506 & -0.0736 & 0.470774 \tabularnewline
8 & -0.046356 & -0.3591 & 0.3604 \tabularnewline
9 & -0.033214 & -0.2573 & 0.398924 \tabularnewline
10 & -0.058479 & -0.453 & 0.326099 \tabularnewline
11 & -0.07792 & -0.6036 & 0.274203 \tabularnewline
12 & -0.086007 & -0.6662 & 0.253915 \tabularnewline
13 & -0.059087 & -0.4577 & 0.324416 \tabularnewline
14 & -0.05572 & -0.4316 & 0.333788 \tabularnewline
15 & -0.006661 & -0.0516 & 0.479512 \tabularnewline
16 & 0.01268 & 0.0982 & 0.461042 \tabularnewline
17 & 0.100042 & 0.7749 & 0.220714 \tabularnewline
18 & -0.011397 & -0.0883 & 0.464975 \tabularnewline
19 & 0.005948 & 0.0461 & 0.481701 \tabularnewline
20 & -0.020356 & -0.1577 & 0.437619 \tabularnewline
21 & -0.036938 & -0.2861 & 0.387887 \tabularnewline
22 & -0.003088 & -0.0239 & 0.4905 \tabularnewline
23 & 0.004619 & 0.0358 & 0.485789 \tabularnewline
24 & 0.00739 & 0.0572 & 0.47727 \tabularnewline
25 & -0.005097 & -0.0395 & 0.484319 \tabularnewline
26 & -0.039132 & -0.3031 & 0.381427 \tabularnewline
27 & -0.040221 & -0.3116 & 0.378231 \tabularnewline
28 & -0.038861 & -0.301 & 0.382221 \tabularnewline
29 & -0.034265 & -0.2654 & 0.395799 \tabularnewline
30 & -0.03568 & -0.2764 & 0.391606 \tabularnewline
31 & -0.045951 & -0.3559 & 0.361568 \tabularnewline
32 & -0.00634 & -0.0491 & 0.480498 \tabularnewline
33 & -0.002577 & -0.02 & 0.492071 \tabularnewline
34 & -0.018915 & -0.1465 & 0.442004 \tabularnewline
35 & -0.017811 & -0.138 & 0.445366 \tabularnewline
36 & -0.031094 & -0.2409 & 0.405244 \tabularnewline
37 & -0.020202 & -0.1565 & 0.438088 \tabularnewline
38 & 0.002626 & 0.0203 & 0.49192 \tabularnewline
39 & -0.010191 & -0.0789 & 0.46867 \tabularnewline
40 & -0.000389 & -0.003 & 0.498804 \tabularnewline
41 & -0.02587 & -0.2004 & 0.420926 \tabularnewline
42 & -0.006123 & -0.0474 & 0.481163 \tabularnewline
43 & 0.003402 & 0.0264 & 0.489532 \tabularnewline
44 & -0.007727 & -0.0599 & 0.476236 \tabularnewline
45 & 0.034327 & 0.2659 & 0.395615 \tabularnewline
46 & 0.003133 & 0.0243 & 0.49036 \tabularnewline
47 & -0.019457 & -0.1507 & 0.440353 \tabularnewline
48 & -0.033173 & -0.257 & 0.399046 \tabularnewline
49 & -0.016585 & -0.1285 & 0.449105 \tabularnewline
50 & -0.012806 & -0.0992 & 0.460656 \tabularnewline
51 & -0.008204 & -0.0635 & 0.474771 \tabularnewline
52 & 0.002854 & 0.0221 & 0.491218 \tabularnewline
53 & 0.013719 & 0.1063 & 0.457861 \tabularnewline
54 & -0.001515 & -0.0117 & 0.495338 \tabularnewline
55 & 0.01057 & 0.0819 & 0.46751 \tabularnewline
56 & 0.035854 & 0.2777 & 0.39109 \tabularnewline
57 & 0.001926 & 0.0149 & 0.494072 \tabularnewline
58 & 0.013596 & 0.1053 & 0.458238 \tabularnewline
59 & 0.014247 & 0.1104 & 0.456248 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66215&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]0.956646[/C][C]7.4102[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.116769[/C][C]-0.9045[/C][C]0.184678[/C][/ROW]
[ROW][C]3[/C][C]-0.114184[/C][C]-0.8845[/C][C]0.189988[/C][/ROW]
[ROW][C]4[/C][C]-0.071972[/C][C]-0.5575[/C][C]0.289632[/C][/ROW]
[ROW][C]5[/C][C]-0.038772[/C][C]-0.3003[/C][C]0.382484[/C][/ROW]
[ROW][C]6[/C][C]0.038823[/C][C]0.3007[/C][C]0.382334[/C][/ROW]
[ROW][C]7[/C][C]-0.009506[/C][C]-0.0736[/C][C]0.470774[/C][/ROW]
[ROW][C]8[/C][C]-0.046356[/C][C]-0.3591[/C][C]0.3604[/C][/ROW]
[ROW][C]9[/C][C]-0.033214[/C][C]-0.2573[/C][C]0.398924[/C][/ROW]
[ROW][C]10[/C][C]-0.058479[/C][C]-0.453[/C][C]0.326099[/C][/ROW]
[ROW][C]11[/C][C]-0.07792[/C][C]-0.6036[/C][C]0.274203[/C][/ROW]
[ROW][C]12[/C][C]-0.086007[/C][C]-0.6662[/C][C]0.253915[/C][/ROW]
[ROW][C]13[/C][C]-0.059087[/C][C]-0.4577[/C][C]0.324416[/C][/ROW]
[ROW][C]14[/C][C]-0.05572[/C][C]-0.4316[/C][C]0.333788[/C][/ROW]
[ROW][C]15[/C][C]-0.006661[/C][C]-0.0516[/C][C]0.479512[/C][/ROW]
[ROW][C]16[/C][C]0.01268[/C][C]0.0982[/C][C]0.461042[/C][/ROW]
[ROW][C]17[/C][C]0.100042[/C][C]0.7749[/C][C]0.220714[/C][/ROW]
[ROW][C]18[/C][C]-0.011397[/C][C]-0.0883[/C][C]0.464975[/C][/ROW]
[ROW][C]19[/C][C]0.005948[/C][C]0.0461[/C][C]0.481701[/C][/ROW]
[ROW][C]20[/C][C]-0.020356[/C][C]-0.1577[/C][C]0.437619[/C][/ROW]
[ROW][C]21[/C][C]-0.036938[/C][C]-0.2861[/C][C]0.387887[/C][/ROW]
[ROW][C]22[/C][C]-0.003088[/C][C]-0.0239[/C][C]0.4905[/C][/ROW]
[ROW][C]23[/C][C]0.004619[/C][C]0.0358[/C][C]0.485789[/C][/ROW]
[ROW][C]24[/C][C]0.00739[/C][C]0.0572[/C][C]0.47727[/C][/ROW]
[ROW][C]25[/C][C]-0.005097[/C][C]-0.0395[/C][C]0.484319[/C][/ROW]
[ROW][C]26[/C][C]-0.039132[/C][C]-0.3031[/C][C]0.381427[/C][/ROW]
[ROW][C]27[/C][C]-0.040221[/C][C]-0.3116[/C][C]0.378231[/C][/ROW]
[ROW][C]28[/C][C]-0.038861[/C][C]-0.301[/C][C]0.382221[/C][/ROW]
[ROW][C]29[/C][C]-0.034265[/C][C]-0.2654[/C][C]0.395799[/C][/ROW]
[ROW][C]30[/C][C]-0.03568[/C][C]-0.2764[/C][C]0.391606[/C][/ROW]
[ROW][C]31[/C][C]-0.045951[/C][C]-0.3559[/C][C]0.361568[/C][/ROW]
[ROW][C]32[/C][C]-0.00634[/C][C]-0.0491[/C][C]0.480498[/C][/ROW]
[ROW][C]33[/C][C]-0.002577[/C][C]-0.02[/C][C]0.492071[/C][/ROW]
[ROW][C]34[/C][C]-0.018915[/C][C]-0.1465[/C][C]0.442004[/C][/ROW]
[ROW][C]35[/C][C]-0.017811[/C][C]-0.138[/C][C]0.445366[/C][/ROW]
[ROW][C]36[/C][C]-0.031094[/C][C]-0.2409[/C][C]0.405244[/C][/ROW]
[ROW][C]37[/C][C]-0.020202[/C][C]-0.1565[/C][C]0.438088[/C][/ROW]
[ROW][C]38[/C][C]0.002626[/C][C]0.0203[/C][C]0.49192[/C][/ROW]
[ROW][C]39[/C][C]-0.010191[/C][C]-0.0789[/C][C]0.46867[/C][/ROW]
[ROW][C]40[/C][C]-0.000389[/C][C]-0.003[/C][C]0.498804[/C][/ROW]
[ROW][C]41[/C][C]-0.02587[/C][C]-0.2004[/C][C]0.420926[/C][/ROW]
[ROW][C]42[/C][C]-0.006123[/C][C]-0.0474[/C][C]0.481163[/C][/ROW]
[ROW][C]43[/C][C]0.003402[/C][C]0.0264[/C][C]0.489532[/C][/ROW]
[ROW][C]44[/C][C]-0.007727[/C][C]-0.0599[/C][C]0.476236[/C][/ROW]
[ROW][C]45[/C][C]0.034327[/C][C]0.2659[/C][C]0.395615[/C][/ROW]
[ROW][C]46[/C][C]0.003133[/C][C]0.0243[/C][C]0.49036[/C][/ROW]
[ROW][C]47[/C][C]-0.019457[/C][C]-0.1507[/C][C]0.440353[/C][/ROW]
[ROW][C]48[/C][C]-0.033173[/C][C]-0.257[/C][C]0.399046[/C][/ROW]
[ROW][C]49[/C][C]-0.016585[/C][C]-0.1285[/C][C]0.449105[/C][/ROW]
[ROW][C]50[/C][C]-0.012806[/C][C]-0.0992[/C][C]0.460656[/C][/ROW]
[ROW][C]51[/C][C]-0.008204[/C][C]-0.0635[/C][C]0.474771[/C][/ROW]
[ROW][C]52[/C][C]0.002854[/C][C]0.0221[/C][C]0.491218[/C][/ROW]
[ROW][C]53[/C][C]0.013719[/C][C]0.1063[/C][C]0.457861[/C][/ROW]
[ROW][C]54[/C][C]-0.001515[/C][C]-0.0117[/C][C]0.495338[/C][/ROW]
[ROW][C]55[/C][C]0.01057[/C][C]0.0819[/C][C]0.46751[/C][/ROW]
[ROW][C]56[/C][C]0.035854[/C][C]0.2777[/C][C]0.39109[/C][/ROW]
[ROW][C]57[/C][C]0.001926[/C][C]0.0149[/C][C]0.494072[/C][/ROW]
[ROW][C]58[/C][C]0.013596[/C][C]0.1053[/C][C]0.458238[/C][/ROW]
[ROW][C]59[/C][C]0.014247[/C][C]0.1104[/C][C]0.456248[/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=66215&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66215&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
10.9566467.41020
2-0.116769-0.90450.184678
3-0.114184-0.88450.189988
4-0.071972-0.55750.289632
5-0.038772-0.30030.382484
60.0388230.30070.382334
7-0.009506-0.07360.470774
8-0.046356-0.35910.3604
9-0.033214-0.25730.398924
10-0.058479-0.4530.326099
11-0.07792-0.60360.274203
12-0.086007-0.66620.253915
13-0.059087-0.45770.324416
14-0.05572-0.43160.333788
15-0.006661-0.05160.479512
160.012680.09820.461042
170.1000420.77490.220714
18-0.011397-0.08830.464975
190.0059480.04610.481701
20-0.020356-0.15770.437619
21-0.036938-0.28610.387887
22-0.003088-0.02390.4905
230.0046190.03580.485789
240.007390.05720.47727
25-0.005097-0.03950.484319
26-0.039132-0.30310.381427
27-0.040221-0.31160.378231
28-0.038861-0.3010.382221
29-0.034265-0.26540.395799
30-0.03568-0.27640.391606
31-0.045951-0.35590.361568
32-0.00634-0.04910.480498
33-0.002577-0.020.492071
34-0.018915-0.14650.442004
35-0.017811-0.1380.445366
36-0.031094-0.24090.405244
37-0.020202-0.15650.438088
380.0026260.02030.49192
39-0.010191-0.07890.46867
40-0.000389-0.0030.498804
41-0.02587-0.20040.420926
42-0.006123-0.04740.481163
430.0034020.02640.489532
44-0.007727-0.05990.476236
450.0343270.26590.395615
460.0031330.02430.49036
47-0.019457-0.15070.440353
48-0.033173-0.2570.399046
49-0.016585-0.12850.449105
50-0.012806-0.09920.460656
51-0.008204-0.06350.474771
520.0028540.02210.491218
530.0137190.10630.457861
54-0.001515-0.01170.495338
550.010570.08190.46751
560.0358540.27770.39109
570.0019260.01490.494072
580.0135960.10530.458238
590.0142470.11040.456248
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')