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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 18 Dec 2009 05:59:19 -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/18/t1261141182vk5054zs6nzk7gt.htm/, Retrieved Sat, 27 Apr 2024 06:15:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69298, Retrieved Sat, 27 Apr 2024 06:15:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-12-18 12:59:19] [02cb93c9d037d32bf77dfc632a3a9fbe] [Current]
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Dataseries X:
100.00
110.08
123.28
106.30
114.60
110.22
117.82
138.84
131.13
153.26
148.76
110.75
132.00
138.55
126.50
119.47
152.49
152.46
134.08
162.33
130.46
142.83
148.39
122.88
125.86
133.31
140.97
110.30
123.04
125.99
112.24
136.10
111.86
109.63
135.75
114.39
121.79
101.33
147.01
113.01
101.89
117.85
128.68
117.27
121.55
109.18
127.88
104.92
100.93
116.79
107.50
109.18
128.31
83.80
93.16
103.99
106.33
97.55
111.71
105.43
103.62




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=69298&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=69298&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69298&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
1-0.495808-3.84050.000149
2-0.122583-0.94950.173081
30.24651.90940.030499
4-0.078106-0.6050.273729
5-0.045509-0.35250.362846
6-0.006124-0.04740.481162
70.0599460.46430.322043
8-0.025838-0.20010.421024
90.0039870.03090.487731
100.1741731.34910.091181
11-0.365391-2.83030.003159
120.278192.15480.017599
13-0.039009-0.30220.381786
14-0.040387-0.31280.377744
15-0.004217-0.03270.487025
16-0.026946-0.20870.417686
170.0792890.61420.270712
18-0.016239-0.12580.450161
19-0.048708-0.37730.353645
20-0.026028-0.20160.420451
210.0494990.38340.351383
220.0692930.53670.296715
23-0.17688-1.37010.08788
240.0947270.73380.232978
250.0128470.09950.460533
26-0.007293-0.05650.477568
270.0257910.19980.421166
28-0.101426-0.78560.217583
290.0706070.54690.29323
300.084080.65130.258676
31-0.144888-1.12230.133103
320.0078250.06060.475935
330.0896540.69450.245037
34-0.027355-0.21190.416456
35-0.078414-0.60740.27294
360.1021820.79150.215885
370.0017870.01380.494502
38-0.133671-1.03540.152315
390.1083360.83920.202354
400.0112520.08720.465417
41-0.14201-1.10.137861
420.1592111.23320.111148
43-0.019155-0.14840.441274
44-0.069437-0.53790.296333
450.0466860.36160.359449
46-0.032342-0.25050.401521
47-0.027733-0.21480.415318
480.0287650.22280.412219
49-0.009711-0.07520.470146
500.0318560.24680.402971
51-0.011714-0.09070.464002
52-0.022777-0.17640.430275
53-0.001312-0.01020.495962
540.0206480.15990.436735
55-0.018615-0.14420.442916
560.0093350.07230.471298
570.004430.03430.486371
58-0.004344-0.03370.486634
59-0.000924-0.00720.497156
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.495808 & -3.8405 & 0.000149 \tabularnewline
2 & -0.122583 & -0.9495 & 0.173081 \tabularnewline
3 & 0.2465 & 1.9094 & 0.030499 \tabularnewline
4 & -0.078106 & -0.605 & 0.273729 \tabularnewline
5 & -0.045509 & -0.3525 & 0.362846 \tabularnewline
6 & -0.006124 & -0.0474 & 0.481162 \tabularnewline
7 & 0.059946 & 0.4643 & 0.322043 \tabularnewline
8 & -0.025838 & -0.2001 & 0.421024 \tabularnewline
9 & 0.003987 & 0.0309 & 0.487731 \tabularnewline
10 & 0.174173 & 1.3491 & 0.091181 \tabularnewline
11 & -0.365391 & -2.8303 & 0.003159 \tabularnewline
12 & 0.27819 & 2.1548 & 0.017599 \tabularnewline
13 & -0.039009 & -0.3022 & 0.381786 \tabularnewline
14 & -0.040387 & -0.3128 & 0.377744 \tabularnewline
15 & -0.004217 & -0.0327 & 0.487025 \tabularnewline
16 & -0.026946 & -0.2087 & 0.417686 \tabularnewline
17 & 0.079289 & 0.6142 & 0.270712 \tabularnewline
18 & -0.016239 & -0.1258 & 0.450161 \tabularnewline
19 & -0.048708 & -0.3773 & 0.353645 \tabularnewline
20 & -0.026028 & -0.2016 & 0.420451 \tabularnewline
21 & 0.049499 & 0.3834 & 0.351383 \tabularnewline
22 & 0.069293 & 0.5367 & 0.296715 \tabularnewline
23 & -0.17688 & -1.3701 & 0.08788 \tabularnewline
24 & 0.094727 & 0.7338 & 0.232978 \tabularnewline
25 & 0.012847 & 0.0995 & 0.460533 \tabularnewline
26 & -0.007293 & -0.0565 & 0.477568 \tabularnewline
27 & 0.025791 & 0.1998 & 0.421166 \tabularnewline
28 & -0.101426 & -0.7856 & 0.217583 \tabularnewline
29 & 0.070607 & 0.5469 & 0.29323 \tabularnewline
30 & 0.08408 & 0.6513 & 0.258676 \tabularnewline
31 & -0.144888 & -1.1223 & 0.133103 \tabularnewline
32 & 0.007825 & 0.0606 & 0.475935 \tabularnewline
33 & 0.089654 & 0.6945 & 0.245037 \tabularnewline
34 & -0.027355 & -0.2119 & 0.416456 \tabularnewline
35 & -0.078414 & -0.6074 & 0.27294 \tabularnewline
36 & 0.102182 & 0.7915 & 0.215885 \tabularnewline
37 & 0.001787 & 0.0138 & 0.494502 \tabularnewline
38 & -0.133671 & -1.0354 & 0.152315 \tabularnewline
39 & 0.108336 & 0.8392 & 0.202354 \tabularnewline
40 & 0.011252 & 0.0872 & 0.465417 \tabularnewline
41 & -0.14201 & -1.1 & 0.137861 \tabularnewline
42 & 0.159211 & 1.2332 & 0.111148 \tabularnewline
43 & -0.019155 & -0.1484 & 0.441274 \tabularnewline
44 & -0.069437 & -0.5379 & 0.296333 \tabularnewline
45 & 0.046686 & 0.3616 & 0.359449 \tabularnewline
46 & -0.032342 & -0.2505 & 0.401521 \tabularnewline
47 & -0.027733 & -0.2148 & 0.415318 \tabularnewline
48 & 0.028765 & 0.2228 & 0.412219 \tabularnewline
49 & -0.009711 & -0.0752 & 0.470146 \tabularnewline
50 & 0.031856 & 0.2468 & 0.402971 \tabularnewline
51 & -0.011714 & -0.0907 & 0.464002 \tabularnewline
52 & -0.022777 & -0.1764 & 0.430275 \tabularnewline
53 & -0.001312 & -0.0102 & 0.495962 \tabularnewline
54 & 0.020648 & 0.1599 & 0.436735 \tabularnewline
55 & -0.018615 & -0.1442 & 0.442916 \tabularnewline
56 & 0.009335 & 0.0723 & 0.471298 \tabularnewline
57 & 0.00443 & 0.0343 & 0.486371 \tabularnewline
58 & -0.004344 & -0.0337 & 0.486634 \tabularnewline
59 & -0.000924 & -0.0072 & 0.497156 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69298&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]-0.495808[/C][C]-3.8405[/C][C]0.000149[/C][/ROW]
[ROW][C]2[/C][C]-0.122583[/C][C]-0.9495[/C][C]0.173081[/C][/ROW]
[ROW][C]3[/C][C]0.2465[/C][C]1.9094[/C][C]0.030499[/C][/ROW]
[ROW][C]4[/C][C]-0.078106[/C][C]-0.605[/C][C]0.273729[/C][/ROW]
[ROW][C]5[/C][C]-0.045509[/C][C]-0.3525[/C][C]0.362846[/C][/ROW]
[ROW][C]6[/C][C]-0.006124[/C][C]-0.0474[/C][C]0.481162[/C][/ROW]
[ROW][C]7[/C][C]0.059946[/C][C]0.4643[/C][C]0.322043[/C][/ROW]
[ROW][C]8[/C][C]-0.025838[/C][C]-0.2001[/C][C]0.421024[/C][/ROW]
[ROW][C]9[/C][C]0.003987[/C][C]0.0309[/C][C]0.487731[/C][/ROW]
[ROW][C]10[/C][C]0.174173[/C][C]1.3491[/C][C]0.091181[/C][/ROW]
[ROW][C]11[/C][C]-0.365391[/C][C]-2.8303[/C][C]0.003159[/C][/ROW]
[ROW][C]12[/C][C]0.27819[/C][C]2.1548[/C][C]0.017599[/C][/ROW]
[ROW][C]13[/C][C]-0.039009[/C][C]-0.3022[/C][C]0.381786[/C][/ROW]
[ROW][C]14[/C][C]-0.040387[/C][C]-0.3128[/C][C]0.377744[/C][/ROW]
[ROW][C]15[/C][C]-0.004217[/C][C]-0.0327[/C][C]0.487025[/C][/ROW]
[ROW][C]16[/C][C]-0.026946[/C][C]-0.2087[/C][C]0.417686[/C][/ROW]
[ROW][C]17[/C][C]0.079289[/C][C]0.6142[/C][C]0.270712[/C][/ROW]
[ROW][C]18[/C][C]-0.016239[/C][C]-0.1258[/C][C]0.450161[/C][/ROW]
[ROW][C]19[/C][C]-0.048708[/C][C]-0.3773[/C][C]0.353645[/C][/ROW]
[ROW][C]20[/C][C]-0.026028[/C][C]-0.2016[/C][C]0.420451[/C][/ROW]
[ROW][C]21[/C][C]0.049499[/C][C]0.3834[/C][C]0.351383[/C][/ROW]
[ROW][C]22[/C][C]0.069293[/C][C]0.5367[/C][C]0.296715[/C][/ROW]
[ROW][C]23[/C][C]-0.17688[/C][C]-1.3701[/C][C]0.08788[/C][/ROW]
[ROW][C]24[/C][C]0.094727[/C][C]0.7338[/C][C]0.232978[/C][/ROW]
[ROW][C]25[/C][C]0.012847[/C][C]0.0995[/C][C]0.460533[/C][/ROW]
[ROW][C]26[/C][C]-0.007293[/C][C]-0.0565[/C][C]0.477568[/C][/ROW]
[ROW][C]27[/C][C]0.025791[/C][C]0.1998[/C][C]0.421166[/C][/ROW]
[ROW][C]28[/C][C]-0.101426[/C][C]-0.7856[/C][C]0.217583[/C][/ROW]
[ROW][C]29[/C][C]0.070607[/C][C]0.5469[/C][C]0.29323[/C][/ROW]
[ROW][C]30[/C][C]0.08408[/C][C]0.6513[/C][C]0.258676[/C][/ROW]
[ROW][C]31[/C][C]-0.144888[/C][C]-1.1223[/C][C]0.133103[/C][/ROW]
[ROW][C]32[/C][C]0.007825[/C][C]0.0606[/C][C]0.475935[/C][/ROW]
[ROW][C]33[/C][C]0.089654[/C][C]0.6945[/C][C]0.245037[/C][/ROW]
[ROW][C]34[/C][C]-0.027355[/C][C]-0.2119[/C][C]0.416456[/C][/ROW]
[ROW][C]35[/C][C]-0.078414[/C][C]-0.6074[/C][C]0.27294[/C][/ROW]
[ROW][C]36[/C][C]0.102182[/C][C]0.7915[/C][C]0.215885[/C][/ROW]
[ROW][C]37[/C][C]0.001787[/C][C]0.0138[/C][C]0.494502[/C][/ROW]
[ROW][C]38[/C][C]-0.133671[/C][C]-1.0354[/C][C]0.152315[/C][/ROW]
[ROW][C]39[/C][C]0.108336[/C][C]0.8392[/C][C]0.202354[/C][/ROW]
[ROW][C]40[/C][C]0.011252[/C][C]0.0872[/C][C]0.465417[/C][/ROW]
[ROW][C]41[/C][C]-0.14201[/C][C]-1.1[/C][C]0.137861[/C][/ROW]
[ROW][C]42[/C][C]0.159211[/C][C]1.2332[/C][C]0.111148[/C][/ROW]
[ROW][C]43[/C][C]-0.019155[/C][C]-0.1484[/C][C]0.441274[/C][/ROW]
[ROW][C]44[/C][C]-0.069437[/C][C]-0.5379[/C][C]0.296333[/C][/ROW]
[ROW][C]45[/C][C]0.046686[/C][C]0.3616[/C][C]0.359449[/C][/ROW]
[ROW][C]46[/C][C]-0.032342[/C][C]-0.2505[/C][C]0.401521[/C][/ROW]
[ROW][C]47[/C][C]-0.027733[/C][C]-0.2148[/C][C]0.415318[/C][/ROW]
[ROW][C]48[/C][C]0.028765[/C][C]0.2228[/C][C]0.412219[/C][/ROW]
[ROW][C]49[/C][C]-0.009711[/C][C]-0.0752[/C][C]0.470146[/C][/ROW]
[ROW][C]50[/C][C]0.031856[/C][C]0.2468[/C][C]0.402971[/C][/ROW]
[ROW][C]51[/C][C]-0.011714[/C][C]-0.0907[/C][C]0.464002[/C][/ROW]
[ROW][C]52[/C][C]-0.022777[/C][C]-0.1764[/C][C]0.430275[/C][/ROW]
[ROW][C]53[/C][C]-0.001312[/C][C]-0.0102[/C][C]0.495962[/C][/ROW]
[ROW][C]54[/C][C]0.020648[/C][C]0.1599[/C][C]0.436735[/C][/ROW]
[ROW][C]55[/C][C]-0.018615[/C][C]-0.1442[/C][C]0.442916[/C][/ROW]
[ROW][C]56[/C][C]0.009335[/C][C]0.0723[/C][C]0.471298[/C][/ROW]
[ROW][C]57[/C][C]0.00443[/C][C]0.0343[/C][C]0.486371[/C][/ROW]
[ROW][C]58[/C][C]-0.004344[/C][C]-0.0337[/C][C]0.486634[/C][/ROW]
[ROW][C]59[/C][C]-0.000924[/C][C]-0.0072[/C][C]0.497156[/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=69298&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69298&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
1-0.495808-3.84050.000149
2-0.122583-0.94950.173081
30.24651.90940.030499
4-0.078106-0.6050.273729
5-0.045509-0.35250.362846
6-0.006124-0.04740.481162
70.0599460.46430.322043
8-0.025838-0.20010.421024
90.0039870.03090.487731
100.1741731.34910.091181
11-0.365391-2.83030.003159
120.278192.15480.017599
13-0.039009-0.30220.381786
14-0.040387-0.31280.377744
15-0.004217-0.03270.487025
16-0.026946-0.20870.417686
170.0792890.61420.270712
18-0.016239-0.12580.450161
19-0.048708-0.37730.353645
20-0.026028-0.20160.420451
210.0494990.38340.351383
220.0692930.53670.296715
23-0.17688-1.37010.08788
240.0947270.73380.232978
250.0128470.09950.460533
26-0.007293-0.05650.477568
270.0257910.19980.421166
28-0.101426-0.78560.217583
290.0706070.54690.29323
300.084080.65130.258676
31-0.144888-1.12230.133103
320.0078250.06060.475935
330.0896540.69450.245037
34-0.027355-0.21190.416456
35-0.078414-0.60740.27294
360.1021820.79150.215885
370.0017870.01380.494502
38-0.133671-1.03540.152315
390.1083360.83920.202354
400.0112520.08720.465417
41-0.14201-1.10.137861
420.1592111.23320.111148
43-0.019155-0.14840.441274
44-0.069437-0.53790.296333
450.0466860.36160.359449
46-0.032342-0.25050.401521
47-0.027733-0.21480.415318
480.0287650.22280.412219
49-0.009711-0.07520.470146
500.0318560.24680.402971
51-0.011714-0.09070.464002
52-0.022777-0.17640.430275
53-0.001312-0.01020.495962
540.0206480.15990.436735
55-0.018615-0.14420.442916
560.0093350.07230.471298
570.004430.03430.486371
58-0.004344-0.03370.486634
59-0.000924-0.00720.497156
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.495808-3.84050.000149
2-0.488494-3.78390.000179
3-0.150062-1.16240.124843
4-0.046281-0.35850.360617
5-0.001455-0.01130.495524
6-0.093605-0.72510.235616
7-0.035521-0.27510.392074
8-0.01219-0.09440.462544
90.0483710.37470.354611
100.3432782.6590.005017
11-0.138149-1.07010.144431
120.0319640.24760.402649
13-0.076604-0.59340.277581
140.1589841.23150.111474
150.0430950.33380.369843
16-0.07914-0.6130.271091
17-0.098404-0.76220.224454
180.0291840.22610.410964
190.0701420.54330.294463
20-0.11098-0.85960.196702
21-0.039227-0.30380.381148
22-0.077873-0.60320.274323
23-0.021114-0.16350.435319
24-0.066655-0.51630.303769
25-0.030079-0.2330.408282
26-0.018958-0.14690.441871
270.0713170.55240.291356
28-0.031295-0.24240.404645
29-0.007018-0.05440.478413
300.1479151.14570.128226
31-0.027128-0.21010.417138
32-0.038215-0.2960.384121
330.008420.06520.474107
340.0203320.15750.437695
35-0.078735-0.60990.272124
360.0118290.09160.463648
370.1019920.790.216311
38-0.068547-0.5310.298702
39-0.151523-1.17370.122579
40-0.071634-0.55490.290521
41-0.035624-0.27590.39177
420.0347270.2690.39443
43-0.021493-0.16650.434167
44-0.005035-0.0390.484509
450.060790.47090.319719
46-0.057509-0.44550.328793
47-0.115471-0.89440.187331
48-0.036022-0.2790.390591
49-0.056341-0.43640.33205
500.0551730.42740.33532
510.038460.29790.3834
52-0.060142-0.46590.321503
53-0.002851-0.02210.491227
54-0.039929-0.30930.379087
550.019570.15160.440009
560.0942740.73020.234042
570.0107790.08350.466869
58-0.07388-0.57230.284638
59-0.014543-0.11260.455342
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.495808 & -3.8405 & 0.000149 \tabularnewline
2 & -0.488494 & -3.7839 & 0.000179 \tabularnewline
3 & -0.150062 & -1.1624 & 0.124843 \tabularnewline
4 & -0.046281 & -0.3585 & 0.360617 \tabularnewline
5 & -0.001455 & -0.0113 & 0.495524 \tabularnewline
6 & -0.093605 & -0.7251 & 0.235616 \tabularnewline
7 & -0.035521 & -0.2751 & 0.392074 \tabularnewline
8 & -0.01219 & -0.0944 & 0.462544 \tabularnewline
9 & 0.048371 & 0.3747 & 0.354611 \tabularnewline
10 & 0.343278 & 2.659 & 0.005017 \tabularnewline
11 & -0.138149 & -1.0701 & 0.144431 \tabularnewline
12 & 0.031964 & 0.2476 & 0.402649 \tabularnewline
13 & -0.076604 & -0.5934 & 0.277581 \tabularnewline
14 & 0.158984 & 1.2315 & 0.111474 \tabularnewline
15 & 0.043095 & 0.3338 & 0.369843 \tabularnewline
16 & -0.07914 & -0.613 & 0.271091 \tabularnewline
17 & -0.098404 & -0.7622 & 0.224454 \tabularnewline
18 & 0.029184 & 0.2261 & 0.410964 \tabularnewline
19 & 0.070142 & 0.5433 & 0.294463 \tabularnewline
20 & -0.11098 & -0.8596 & 0.196702 \tabularnewline
21 & -0.039227 & -0.3038 & 0.381148 \tabularnewline
22 & -0.077873 & -0.6032 & 0.274323 \tabularnewline
23 & -0.021114 & -0.1635 & 0.435319 \tabularnewline
24 & -0.066655 & -0.5163 & 0.303769 \tabularnewline
25 & -0.030079 & -0.233 & 0.408282 \tabularnewline
26 & -0.018958 & -0.1469 & 0.441871 \tabularnewline
27 & 0.071317 & 0.5524 & 0.291356 \tabularnewline
28 & -0.031295 & -0.2424 & 0.404645 \tabularnewline
29 & -0.007018 & -0.0544 & 0.478413 \tabularnewline
30 & 0.147915 & 1.1457 & 0.128226 \tabularnewline
31 & -0.027128 & -0.2101 & 0.417138 \tabularnewline
32 & -0.038215 & -0.296 & 0.384121 \tabularnewline
33 & 0.00842 & 0.0652 & 0.474107 \tabularnewline
34 & 0.020332 & 0.1575 & 0.437695 \tabularnewline
35 & -0.078735 & -0.6099 & 0.272124 \tabularnewline
36 & 0.011829 & 0.0916 & 0.463648 \tabularnewline
37 & 0.101992 & 0.79 & 0.216311 \tabularnewline
38 & -0.068547 & -0.531 & 0.298702 \tabularnewline
39 & -0.151523 & -1.1737 & 0.122579 \tabularnewline
40 & -0.071634 & -0.5549 & 0.290521 \tabularnewline
41 & -0.035624 & -0.2759 & 0.39177 \tabularnewline
42 & 0.034727 & 0.269 & 0.39443 \tabularnewline
43 & -0.021493 & -0.1665 & 0.434167 \tabularnewline
44 & -0.005035 & -0.039 & 0.484509 \tabularnewline
45 & 0.06079 & 0.4709 & 0.319719 \tabularnewline
46 & -0.057509 & -0.4455 & 0.328793 \tabularnewline
47 & -0.115471 & -0.8944 & 0.187331 \tabularnewline
48 & -0.036022 & -0.279 & 0.390591 \tabularnewline
49 & -0.056341 & -0.4364 & 0.33205 \tabularnewline
50 & 0.055173 & 0.4274 & 0.33532 \tabularnewline
51 & 0.03846 & 0.2979 & 0.3834 \tabularnewline
52 & -0.060142 & -0.4659 & 0.321503 \tabularnewline
53 & -0.002851 & -0.0221 & 0.491227 \tabularnewline
54 & -0.039929 & -0.3093 & 0.379087 \tabularnewline
55 & 0.01957 & 0.1516 & 0.440009 \tabularnewline
56 & 0.094274 & 0.7302 & 0.234042 \tabularnewline
57 & 0.010779 & 0.0835 & 0.466869 \tabularnewline
58 & -0.07388 & -0.5723 & 0.284638 \tabularnewline
59 & -0.014543 & -0.1126 & 0.455342 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69298&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]-0.495808[/C][C]-3.8405[/C][C]0.000149[/C][/ROW]
[ROW][C]2[/C][C]-0.488494[/C][C]-3.7839[/C][C]0.000179[/C][/ROW]
[ROW][C]3[/C][C]-0.150062[/C][C]-1.1624[/C][C]0.124843[/C][/ROW]
[ROW][C]4[/C][C]-0.046281[/C][C]-0.3585[/C][C]0.360617[/C][/ROW]
[ROW][C]5[/C][C]-0.001455[/C][C]-0.0113[/C][C]0.495524[/C][/ROW]
[ROW][C]6[/C][C]-0.093605[/C][C]-0.7251[/C][C]0.235616[/C][/ROW]
[ROW][C]7[/C][C]-0.035521[/C][C]-0.2751[/C][C]0.392074[/C][/ROW]
[ROW][C]8[/C][C]-0.01219[/C][C]-0.0944[/C][C]0.462544[/C][/ROW]
[ROW][C]9[/C][C]0.048371[/C][C]0.3747[/C][C]0.354611[/C][/ROW]
[ROW][C]10[/C][C]0.343278[/C][C]2.659[/C][C]0.005017[/C][/ROW]
[ROW][C]11[/C][C]-0.138149[/C][C]-1.0701[/C][C]0.144431[/C][/ROW]
[ROW][C]12[/C][C]0.031964[/C][C]0.2476[/C][C]0.402649[/C][/ROW]
[ROW][C]13[/C][C]-0.076604[/C][C]-0.5934[/C][C]0.277581[/C][/ROW]
[ROW][C]14[/C][C]0.158984[/C][C]1.2315[/C][C]0.111474[/C][/ROW]
[ROW][C]15[/C][C]0.043095[/C][C]0.3338[/C][C]0.369843[/C][/ROW]
[ROW][C]16[/C][C]-0.07914[/C][C]-0.613[/C][C]0.271091[/C][/ROW]
[ROW][C]17[/C][C]-0.098404[/C][C]-0.7622[/C][C]0.224454[/C][/ROW]
[ROW][C]18[/C][C]0.029184[/C][C]0.2261[/C][C]0.410964[/C][/ROW]
[ROW][C]19[/C][C]0.070142[/C][C]0.5433[/C][C]0.294463[/C][/ROW]
[ROW][C]20[/C][C]-0.11098[/C][C]-0.8596[/C][C]0.196702[/C][/ROW]
[ROW][C]21[/C][C]-0.039227[/C][C]-0.3038[/C][C]0.381148[/C][/ROW]
[ROW][C]22[/C][C]-0.077873[/C][C]-0.6032[/C][C]0.274323[/C][/ROW]
[ROW][C]23[/C][C]-0.021114[/C][C]-0.1635[/C][C]0.435319[/C][/ROW]
[ROW][C]24[/C][C]-0.066655[/C][C]-0.5163[/C][C]0.303769[/C][/ROW]
[ROW][C]25[/C][C]-0.030079[/C][C]-0.233[/C][C]0.408282[/C][/ROW]
[ROW][C]26[/C][C]-0.018958[/C][C]-0.1469[/C][C]0.441871[/C][/ROW]
[ROW][C]27[/C][C]0.071317[/C][C]0.5524[/C][C]0.291356[/C][/ROW]
[ROW][C]28[/C][C]-0.031295[/C][C]-0.2424[/C][C]0.404645[/C][/ROW]
[ROW][C]29[/C][C]-0.007018[/C][C]-0.0544[/C][C]0.478413[/C][/ROW]
[ROW][C]30[/C][C]0.147915[/C][C]1.1457[/C][C]0.128226[/C][/ROW]
[ROW][C]31[/C][C]-0.027128[/C][C]-0.2101[/C][C]0.417138[/C][/ROW]
[ROW][C]32[/C][C]-0.038215[/C][C]-0.296[/C][C]0.384121[/C][/ROW]
[ROW][C]33[/C][C]0.00842[/C][C]0.0652[/C][C]0.474107[/C][/ROW]
[ROW][C]34[/C][C]0.020332[/C][C]0.1575[/C][C]0.437695[/C][/ROW]
[ROW][C]35[/C][C]-0.078735[/C][C]-0.6099[/C][C]0.272124[/C][/ROW]
[ROW][C]36[/C][C]0.011829[/C][C]0.0916[/C][C]0.463648[/C][/ROW]
[ROW][C]37[/C][C]0.101992[/C][C]0.79[/C][C]0.216311[/C][/ROW]
[ROW][C]38[/C][C]-0.068547[/C][C]-0.531[/C][C]0.298702[/C][/ROW]
[ROW][C]39[/C][C]-0.151523[/C][C]-1.1737[/C][C]0.122579[/C][/ROW]
[ROW][C]40[/C][C]-0.071634[/C][C]-0.5549[/C][C]0.290521[/C][/ROW]
[ROW][C]41[/C][C]-0.035624[/C][C]-0.2759[/C][C]0.39177[/C][/ROW]
[ROW][C]42[/C][C]0.034727[/C][C]0.269[/C][C]0.39443[/C][/ROW]
[ROW][C]43[/C][C]-0.021493[/C][C]-0.1665[/C][C]0.434167[/C][/ROW]
[ROW][C]44[/C][C]-0.005035[/C][C]-0.039[/C][C]0.484509[/C][/ROW]
[ROW][C]45[/C][C]0.06079[/C][C]0.4709[/C][C]0.319719[/C][/ROW]
[ROW][C]46[/C][C]-0.057509[/C][C]-0.4455[/C][C]0.328793[/C][/ROW]
[ROW][C]47[/C][C]-0.115471[/C][C]-0.8944[/C][C]0.187331[/C][/ROW]
[ROW][C]48[/C][C]-0.036022[/C][C]-0.279[/C][C]0.390591[/C][/ROW]
[ROW][C]49[/C][C]-0.056341[/C][C]-0.4364[/C][C]0.33205[/C][/ROW]
[ROW][C]50[/C][C]0.055173[/C][C]0.4274[/C][C]0.33532[/C][/ROW]
[ROW][C]51[/C][C]0.03846[/C][C]0.2979[/C][C]0.3834[/C][/ROW]
[ROW][C]52[/C][C]-0.060142[/C][C]-0.4659[/C][C]0.321503[/C][/ROW]
[ROW][C]53[/C][C]-0.002851[/C][C]-0.0221[/C][C]0.491227[/C][/ROW]
[ROW][C]54[/C][C]-0.039929[/C][C]-0.3093[/C][C]0.379087[/C][/ROW]
[ROW][C]55[/C][C]0.01957[/C][C]0.1516[/C][C]0.440009[/C][/ROW]
[ROW][C]56[/C][C]0.094274[/C][C]0.7302[/C][C]0.234042[/C][/ROW]
[ROW][C]57[/C][C]0.010779[/C][C]0.0835[/C][C]0.466869[/C][/ROW]
[ROW][C]58[/C][C]-0.07388[/C][C]-0.5723[/C][C]0.284638[/C][/ROW]
[ROW][C]59[/C][C]-0.014543[/C][C]-0.1126[/C][C]0.455342[/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=69298&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69298&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
1-0.495808-3.84050.000149
2-0.488494-3.78390.000179
3-0.150062-1.16240.124843
4-0.046281-0.35850.360617
5-0.001455-0.01130.495524
6-0.093605-0.72510.235616
7-0.035521-0.27510.392074
8-0.01219-0.09440.462544
90.0483710.37470.354611
100.3432782.6590.005017
11-0.138149-1.07010.144431
120.0319640.24760.402649
13-0.076604-0.59340.277581
140.1589841.23150.111474
150.0430950.33380.369843
16-0.07914-0.6130.271091
17-0.098404-0.76220.224454
180.0291840.22610.410964
190.0701420.54330.294463
20-0.11098-0.85960.196702
21-0.039227-0.30380.381148
22-0.077873-0.60320.274323
23-0.021114-0.16350.435319
24-0.066655-0.51630.303769
25-0.030079-0.2330.408282
26-0.018958-0.14690.441871
270.0713170.55240.291356
28-0.031295-0.24240.404645
29-0.007018-0.05440.478413
300.1479151.14570.128226
31-0.027128-0.21010.417138
32-0.038215-0.2960.384121
330.008420.06520.474107
340.0203320.15750.437695
35-0.078735-0.60990.272124
360.0118290.09160.463648
370.1019920.790.216311
38-0.068547-0.5310.298702
39-0.151523-1.17370.122579
40-0.071634-0.55490.290521
41-0.035624-0.27590.39177
420.0347270.2690.39443
43-0.021493-0.16650.434167
44-0.005035-0.0390.484509
450.060790.47090.319719
46-0.057509-0.44550.328793
47-0.115471-0.89440.187331
48-0.036022-0.2790.390591
49-0.056341-0.43640.33205
500.0551730.42740.33532
510.038460.29790.3834
52-0.060142-0.46590.321503
53-0.002851-0.02210.491227
54-0.039929-0.30930.379087
550.019570.15160.440009
560.0942740.73020.234042
570.0107790.08350.466869
58-0.07388-0.57230.284638
59-0.014543-0.11260.455342
60NANANA



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