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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 computationWed, 30 Dec 2009 15:25:00 -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/30/t1262211940yqjyxds0bio1xhs.htm/, Retrieved Mon, 29 Apr 2024 03:19:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71383, Retrieved Mon, 29 Apr 2024 03:19:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [acf d=D=0] [2009-12-30 22:25:00] [a315839f8c359622c3a1e6ed387dd5cd] [Current]
-   P     [(Partial) Autocorrelation Function] [acf wagens D=0 d=1] [2009-12-30 22:26:22] [bd8e774728cf1f2f4e6868fd314defe3]
-   P       [(Partial) Autocorrelation Function] [acf d=D=1] [2009-12-30 22:27:55] [bd8e774728cf1f2f4e6868fd314defe3]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971




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=71383&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=71383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71383&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
10.3145152.43620.008914
20.1307421.01270.157629
3-0.044693-0.34620.365206
4-0.218072-1.68920.048188
5-0.270914-2.09850.02004
6-0.516494-4.00078.8e-05
7-0.275589-2.13470.01844
8-0.144498-1.11930.133741
9-0.070928-0.54940.292384
100.0527360.40850.342184
110.2286161.77080.040832
120.7520325.82520
130.2247741.74110.043397
140.069820.54080.295315
15-0.070545-0.54640.293395
16-0.207459-1.6070.056656
17-0.231124-1.79030.039227
18-0.413482-3.20280.00109
19-0.199247-1.54340.064001
20-0.092208-0.71420.238923
21-0.057818-0.44790.327936
220.0265070.20530.419007
230.1624291.25820.106602
240.5477424.24283.9e-05
250.1990141.54160.06422
260.0758790.58780.27945
27-0.003605-0.02790.488908
28-0.139579-1.08120.141974
29-0.135038-1.0460.149878
30-0.270084-2.09210.020336
31-0.132285-1.02470.154816
32-0.050841-0.39380.347559
33-0.055267-0.42810.335057
340.0138320.10710.457516
350.0912320.70670.241251
360.3266152.52990.007026
370.128730.99710.161351
380.032080.24850.402302
39-0.009545-0.07390.470653
40-0.110778-0.85810.197132
41-0.0941-0.72890.23445
42-0.135488-1.04950.149081
43-0.054251-0.42020.33791
440.001260.00980.496122
45-0.002812-0.02180.491346
460.0044630.03460.48627
470.0283480.21960.413472
480.1233390.95540.17161
490.0335060.25950.398055
500.0013190.01020.495941
51-0.00867-0.06720.473339
52-0.059377-0.45990.323614
53-0.021768-0.16860.433332
54-0.023674-0.18340.427561
55-0.007768-0.06020.476111
560.0361850.28030.39011
570.0106360.08240.467307
580.0045390.03520.486036
590.0071120.05510.478127
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.314515 & 2.4362 & 0.008914 \tabularnewline
2 & 0.130742 & 1.0127 & 0.157629 \tabularnewline
3 & -0.044693 & -0.3462 & 0.365206 \tabularnewline
4 & -0.218072 & -1.6892 & 0.048188 \tabularnewline
5 & -0.270914 & -2.0985 & 0.02004 \tabularnewline
6 & -0.516494 & -4.0007 & 8.8e-05 \tabularnewline
7 & -0.275589 & -2.1347 & 0.01844 \tabularnewline
8 & -0.144498 & -1.1193 & 0.133741 \tabularnewline
9 & -0.070928 & -0.5494 & 0.292384 \tabularnewline
10 & 0.052736 & 0.4085 & 0.342184 \tabularnewline
11 & 0.228616 & 1.7708 & 0.040832 \tabularnewline
12 & 0.752032 & 5.8252 & 0 \tabularnewline
13 & 0.224774 & 1.7411 & 0.043397 \tabularnewline
14 & 0.06982 & 0.5408 & 0.295315 \tabularnewline
15 & -0.070545 & -0.5464 & 0.293395 \tabularnewline
16 & -0.207459 & -1.607 & 0.056656 \tabularnewline
17 & -0.231124 & -1.7903 & 0.039227 \tabularnewline
18 & -0.413482 & -3.2028 & 0.00109 \tabularnewline
19 & -0.199247 & -1.5434 & 0.064001 \tabularnewline
20 & -0.092208 & -0.7142 & 0.238923 \tabularnewline
21 & -0.057818 & -0.4479 & 0.327936 \tabularnewline
22 & 0.026507 & 0.2053 & 0.419007 \tabularnewline
23 & 0.162429 & 1.2582 & 0.106602 \tabularnewline
24 & 0.547742 & 4.2428 & 3.9e-05 \tabularnewline
25 & 0.199014 & 1.5416 & 0.06422 \tabularnewline
26 & 0.075879 & 0.5878 & 0.27945 \tabularnewline
27 & -0.003605 & -0.0279 & 0.488908 \tabularnewline
28 & -0.139579 & -1.0812 & 0.141974 \tabularnewline
29 & -0.135038 & -1.046 & 0.149878 \tabularnewline
30 & -0.270084 & -2.0921 & 0.020336 \tabularnewline
31 & -0.132285 & -1.0247 & 0.154816 \tabularnewline
32 & -0.050841 & -0.3938 & 0.347559 \tabularnewline
33 & -0.055267 & -0.4281 & 0.335057 \tabularnewline
34 & 0.013832 & 0.1071 & 0.457516 \tabularnewline
35 & 0.091232 & 0.7067 & 0.241251 \tabularnewline
36 & 0.326615 & 2.5299 & 0.007026 \tabularnewline
37 & 0.12873 & 0.9971 & 0.161351 \tabularnewline
38 & 0.03208 & 0.2485 & 0.402302 \tabularnewline
39 & -0.009545 & -0.0739 & 0.470653 \tabularnewline
40 & -0.110778 & -0.8581 & 0.197132 \tabularnewline
41 & -0.0941 & -0.7289 & 0.23445 \tabularnewline
42 & -0.135488 & -1.0495 & 0.149081 \tabularnewline
43 & -0.054251 & -0.4202 & 0.33791 \tabularnewline
44 & 0.00126 & 0.0098 & 0.496122 \tabularnewline
45 & -0.002812 & -0.0218 & 0.491346 \tabularnewline
46 & 0.004463 & 0.0346 & 0.48627 \tabularnewline
47 & 0.028348 & 0.2196 & 0.413472 \tabularnewline
48 & 0.123339 & 0.9554 & 0.17161 \tabularnewline
49 & 0.033506 & 0.2595 & 0.398055 \tabularnewline
50 & 0.001319 & 0.0102 & 0.495941 \tabularnewline
51 & -0.00867 & -0.0672 & 0.473339 \tabularnewline
52 & -0.059377 & -0.4599 & 0.323614 \tabularnewline
53 & -0.021768 & -0.1686 & 0.433332 \tabularnewline
54 & -0.023674 & -0.1834 & 0.427561 \tabularnewline
55 & -0.007768 & -0.0602 & 0.476111 \tabularnewline
56 & 0.036185 & 0.2803 & 0.39011 \tabularnewline
57 & 0.010636 & 0.0824 & 0.467307 \tabularnewline
58 & 0.004539 & 0.0352 & 0.486036 \tabularnewline
59 & 0.007112 & 0.0551 & 0.478127 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71383&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]0.314515[/C][C]2.4362[/C][C]0.008914[/C][/ROW]
[ROW][C]2[/C][C]0.130742[/C][C]1.0127[/C][C]0.157629[/C][/ROW]
[ROW][C]3[/C][C]-0.044693[/C][C]-0.3462[/C][C]0.365206[/C][/ROW]
[ROW][C]4[/C][C]-0.218072[/C][C]-1.6892[/C][C]0.048188[/C][/ROW]
[ROW][C]5[/C][C]-0.270914[/C][C]-2.0985[/C][C]0.02004[/C][/ROW]
[ROW][C]6[/C][C]-0.516494[/C][C]-4.0007[/C][C]8.8e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.275589[/C][C]-2.1347[/C][C]0.01844[/C][/ROW]
[ROW][C]8[/C][C]-0.144498[/C][C]-1.1193[/C][C]0.133741[/C][/ROW]
[ROW][C]9[/C][C]-0.070928[/C][C]-0.5494[/C][C]0.292384[/C][/ROW]
[ROW][C]10[/C][C]0.052736[/C][C]0.4085[/C][C]0.342184[/C][/ROW]
[ROW][C]11[/C][C]0.228616[/C][C]1.7708[/C][C]0.040832[/C][/ROW]
[ROW][C]12[/C][C]0.752032[/C][C]5.8252[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.224774[/C][C]1.7411[/C][C]0.043397[/C][/ROW]
[ROW][C]14[/C][C]0.06982[/C][C]0.5408[/C][C]0.295315[/C][/ROW]
[ROW][C]15[/C][C]-0.070545[/C][C]-0.5464[/C][C]0.293395[/C][/ROW]
[ROW][C]16[/C][C]-0.207459[/C][C]-1.607[/C][C]0.056656[/C][/ROW]
[ROW][C]17[/C][C]-0.231124[/C][C]-1.7903[/C][C]0.039227[/C][/ROW]
[ROW][C]18[/C][C]-0.413482[/C][C]-3.2028[/C][C]0.00109[/C][/ROW]
[ROW][C]19[/C][C]-0.199247[/C][C]-1.5434[/C][C]0.064001[/C][/ROW]
[ROW][C]20[/C][C]-0.092208[/C][C]-0.7142[/C][C]0.238923[/C][/ROW]
[ROW][C]21[/C][C]-0.057818[/C][C]-0.4479[/C][C]0.327936[/C][/ROW]
[ROW][C]22[/C][C]0.026507[/C][C]0.2053[/C][C]0.419007[/C][/ROW]
[ROW][C]23[/C][C]0.162429[/C][C]1.2582[/C][C]0.106602[/C][/ROW]
[ROW][C]24[/C][C]0.547742[/C][C]4.2428[/C][C]3.9e-05[/C][/ROW]
[ROW][C]25[/C][C]0.199014[/C][C]1.5416[/C][C]0.06422[/C][/ROW]
[ROW][C]26[/C][C]0.075879[/C][C]0.5878[/C][C]0.27945[/C][/ROW]
[ROW][C]27[/C][C]-0.003605[/C][C]-0.0279[/C][C]0.488908[/C][/ROW]
[ROW][C]28[/C][C]-0.139579[/C][C]-1.0812[/C][C]0.141974[/C][/ROW]
[ROW][C]29[/C][C]-0.135038[/C][C]-1.046[/C][C]0.149878[/C][/ROW]
[ROW][C]30[/C][C]-0.270084[/C][C]-2.0921[/C][C]0.020336[/C][/ROW]
[ROW][C]31[/C][C]-0.132285[/C][C]-1.0247[/C][C]0.154816[/C][/ROW]
[ROW][C]32[/C][C]-0.050841[/C][C]-0.3938[/C][C]0.347559[/C][/ROW]
[ROW][C]33[/C][C]-0.055267[/C][C]-0.4281[/C][C]0.335057[/C][/ROW]
[ROW][C]34[/C][C]0.013832[/C][C]0.1071[/C][C]0.457516[/C][/ROW]
[ROW][C]35[/C][C]0.091232[/C][C]0.7067[/C][C]0.241251[/C][/ROW]
[ROW][C]36[/C][C]0.326615[/C][C]2.5299[/C][C]0.007026[/C][/ROW]
[ROW][C]37[/C][C]0.12873[/C][C]0.9971[/C][C]0.161351[/C][/ROW]
[ROW][C]38[/C][C]0.03208[/C][C]0.2485[/C][C]0.402302[/C][/ROW]
[ROW][C]39[/C][C]-0.009545[/C][C]-0.0739[/C][C]0.470653[/C][/ROW]
[ROW][C]40[/C][C]-0.110778[/C][C]-0.8581[/C][C]0.197132[/C][/ROW]
[ROW][C]41[/C][C]-0.0941[/C][C]-0.7289[/C][C]0.23445[/C][/ROW]
[ROW][C]42[/C][C]-0.135488[/C][C]-1.0495[/C][C]0.149081[/C][/ROW]
[ROW][C]43[/C][C]-0.054251[/C][C]-0.4202[/C][C]0.33791[/C][/ROW]
[ROW][C]44[/C][C]0.00126[/C][C]0.0098[/C][C]0.496122[/C][/ROW]
[ROW][C]45[/C][C]-0.002812[/C][C]-0.0218[/C][C]0.491346[/C][/ROW]
[ROW][C]46[/C][C]0.004463[/C][C]0.0346[/C][C]0.48627[/C][/ROW]
[ROW][C]47[/C][C]0.028348[/C][C]0.2196[/C][C]0.413472[/C][/ROW]
[ROW][C]48[/C][C]0.123339[/C][C]0.9554[/C][C]0.17161[/C][/ROW]
[ROW][C]49[/C][C]0.033506[/C][C]0.2595[/C][C]0.398055[/C][/ROW]
[ROW][C]50[/C][C]0.001319[/C][C]0.0102[/C][C]0.495941[/C][/ROW]
[ROW][C]51[/C][C]-0.00867[/C][C]-0.0672[/C][C]0.473339[/C][/ROW]
[ROW][C]52[/C][C]-0.059377[/C][C]-0.4599[/C][C]0.323614[/C][/ROW]
[ROW][C]53[/C][C]-0.021768[/C][C]-0.1686[/C][C]0.433332[/C][/ROW]
[ROW][C]54[/C][C]-0.023674[/C][C]-0.1834[/C][C]0.427561[/C][/ROW]
[ROW][C]55[/C][C]-0.007768[/C][C]-0.0602[/C][C]0.476111[/C][/ROW]
[ROW][C]56[/C][C]0.036185[/C][C]0.2803[/C][C]0.39011[/C][/ROW]
[ROW][C]57[/C][C]0.010636[/C][C]0.0824[/C][C]0.467307[/C][/ROW]
[ROW][C]58[/C][C]0.004539[/C][C]0.0352[/C][C]0.486036[/C][/ROW]
[ROW][C]59[/C][C]0.007112[/C][C]0.0551[/C][C]0.478127[/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=71383&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71383&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
10.3145152.43620.008914
20.1307421.01270.157629
3-0.044693-0.34620.365206
4-0.218072-1.68920.048188
5-0.270914-2.09850.02004
6-0.516494-4.00078.8e-05
7-0.275589-2.13470.01844
8-0.144498-1.11930.133741
9-0.070928-0.54940.292384
100.0527360.40850.342184
110.2286161.77080.040832
120.7520325.82520
130.2247741.74110.043397
140.069820.54080.295315
15-0.070545-0.54640.293395
16-0.207459-1.6070.056656
17-0.231124-1.79030.039227
18-0.413482-3.20280.00109
19-0.199247-1.54340.064001
20-0.092208-0.71420.238923
21-0.057818-0.44790.327936
220.0265070.20530.419007
230.1624291.25820.106602
240.5477424.24283.9e-05
250.1990141.54160.06422
260.0758790.58780.27945
27-0.003605-0.02790.488908
28-0.139579-1.08120.141974
29-0.135038-1.0460.149878
30-0.270084-2.09210.020336
31-0.132285-1.02470.154816
32-0.050841-0.39380.347559
33-0.055267-0.42810.335057
340.0138320.10710.457516
350.0912320.70670.241251
360.3266152.52990.007026
370.128730.99710.161351
380.032080.24850.402302
39-0.009545-0.07390.470653
40-0.110778-0.85810.197132
41-0.0941-0.72890.23445
42-0.135488-1.04950.149081
43-0.054251-0.42020.33791
440.001260.00980.496122
45-0.002812-0.02180.491346
460.0044630.03460.48627
470.0283480.21960.413472
480.1233390.95540.17161
490.0335060.25950.398055
500.0013190.01020.495941
51-0.00867-0.06720.473339
52-0.059377-0.45990.323614
53-0.021768-0.16860.433332
54-0.023674-0.18340.427561
55-0.007768-0.06020.476111
560.0361850.28030.39011
570.0106360.08240.467307
580.0045390.03520.486036
590.0071120.05510.478127
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3145152.43620.008914
20.0353160.27360.392682
3-0.106081-0.82170.20725
4-0.202068-1.56520.061396
5-0.158961-1.23130.111507
6-0.435777-3.37550.000648
7-0.075229-0.58270.281132
8-0.100561-0.77890.219538
9-0.181959-1.40950.081932
10-0.175352-1.35830.089732
110.0253240.19620.422574
120.6433734.98353e-06
13-0.343963-2.66430.004947
14-0.209729-1.62460.05475
15-0.055575-0.43050.334194
160.0667020.51670.303643
17-0.079412-0.61510.2704
180.0761620.590.278719
19-0.046494-0.36010.360002
20-0.230455-1.78510.03965
21-0.026932-0.20860.417728
220.0552960.42830.334977
23-0.127353-0.98650.163932
24-0.188169-1.45760.075089
250.1426571.1050.136783
26-0.008313-0.06440.474435
27-0.014674-0.11370.454942
28-0.028659-0.2220.412539
290.0829380.64240.26152
30-0.041653-0.32260.374043
31-0.031639-0.24510.403617
320.068360.52950.2992
33-0.01735-0.13440.44677
340.0151490.11730.453488
35-0.024576-0.19040.424833
36-0.130414-1.01020.158232
37-0.066622-0.5160.303858
380.0092310.07150.471619
39-0.072366-0.56050.288599
40-0.027224-0.21090.416849
41-0.048576-0.37630.354022
420.0624470.48370.315176
430.0137180.10630.457865
440.0394370.30550.38053
450.0415530.32190.374336
46-0.134545-1.04220.150754
47-0.041821-0.32390.373553
48-0.070095-0.5430.294587
49-0.00026-0.0020.499201
500.0134530.10420.458678
510.0216050.16740.433829
52-0.055065-0.42650.335624
53-0.020809-0.16120.436244
54-0.073046-0.56580.286817
55-0.107448-0.83230.204274
560.0400760.31040.378656
57-0.045722-0.35420.362231
58-0.020493-0.15870.437205
590.049340.38220.351837
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.314515 & 2.4362 & 0.008914 \tabularnewline
2 & 0.035316 & 0.2736 & 0.392682 \tabularnewline
3 & -0.106081 & -0.8217 & 0.20725 \tabularnewline
4 & -0.202068 & -1.5652 & 0.061396 \tabularnewline
5 & -0.158961 & -1.2313 & 0.111507 \tabularnewline
6 & -0.435777 & -3.3755 & 0.000648 \tabularnewline
7 & -0.075229 & -0.5827 & 0.281132 \tabularnewline
8 & -0.100561 & -0.7789 & 0.219538 \tabularnewline
9 & -0.181959 & -1.4095 & 0.081932 \tabularnewline
10 & -0.175352 & -1.3583 & 0.089732 \tabularnewline
11 & 0.025324 & 0.1962 & 0.422574 \tabularnewline
12 & 0.643373 & 4.9835 & 3e-06 \tabularnewline
13 & -0.343963 & -2.6643 & 0.004947 \tabularnewline
14 & -0.209729 & -1.6246 & 0.05475 \tabularnewline
15 & -0.055575 & -0.4305 & 0.334194 \tabularnewline
16 & 0.066702 & 0.5167 & 0.303643 \tabularnewline
17 & -0.079412 & -0.6151 & 0.2704 \tabularnewline
18 & 0.076162 & 0.59 & 0.278719 \tabularnewline
19 & -0.046494 & -0.3601 & 0.360002 \tabularnewline
20 & -0.230455 & -1.7851 & 0.03965 \tabularnewline
21 & -0.026932 & -0.2086 & 0.417728 \tabularnewline
22 & 0.055296 & 0.4283 & 0.334977 \tabularnewline
23 & -0.127353 & -0.9865 & 0.163932 \tabularnewline
24 & -0.188169 & -1.4576 & 0.075089 \tabularnewline
25 & 0.142657 & 1.105 & 0.136783 \tabularnewline
26 & -0.008313 & -0.0644 & 0.474435 \tabularnewline
27 & -0.014674 & -0.1137 & 0.454942 \tabularnewline
28 & -0.028659 & -0.222 & 0.412539 \tabularnewline
29 & 0.082938 & 0.6424 & 0.26152 \tabularnewline
30 & -0.041653 & -0.3226 & 0.374043 \tabularnewline
31 & -0.031639 & -0.2451 & 0.403617 \tabularnewline
32 & 0.06836 & 0.5295 & 0.2992 \tabularnewline
33 & -0.01735 & -0.1344 & 0.44677 \tabularnewline
34 & 0.015149 & 0.1173 & 0.453488 \tabularnewline
35 & -0.024576 & -0.1904 & 0.424833 \tabularnewline
36 & -0.130414 & -1.0102 & 0.158232 \tabularnewline
37 & -0.066622 & -0.516 & 0.303858 \tabularnewline
38 & 0.009231 & 0.0715 & 0.471619 \tabularnewline
39 & -0.072366 & -0.5605 & 0.288599 \tabularnewline
40 & -0.027224 & -0.2109 & 0.416849 \tabularnewline
41 & -0.048576 & -0.3763 & 0.354022 \tabularnewline
42 & 0.062447 & 0.4837 & 0.315176 \tabularnewline
43 & 0.013718 & 0.1063 & 0.457865 \tabularnewline
44 & 0.039437 & 0.3055 & 0.38053 \tabularnewline
45 & 0.041553 & 0.3219 & 0.374336 \tabularnewline
46 & -0.134545 & -1.0422 & 0.150754 \tabularnewline
47 & -0.041821 & -0.3239 & 0.373553 \tabularnewline
48 & -0.070095 & -0.543 & 0.294587 \tabularnewline
49 & -0.00026 & -0.002 & 0.499201 \tabularnewline
50 & 0.013453 & 0.1042 & 0.458678 \tabularnewline
51 & 0.021605 & 0.1674 & 0.433829 \tabularnewline
52 & -0.055065 & -0.4265 & 0.335624 \tabularnewline
53 & -0.020809 & -0.1612 & 0.436244 \tabularnewline
54 & -0.073046 & -0.5658 & 0.286817 \tabularnewline
55 & -0.107448 & -0.8323 & 0.204274 \tabularnewline
56 & 0.040076 & 0.3104 & 0.378656 \tabularnewline
57 & -0.045722 & -0.3542 & 0.362231 \tabularnewline
58 & -0.020493 & -0.1587 & 0.437205 \tabularnewline
59 & 0.04934 & 0.3822 & 0.351837 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71383&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]0.314515[/C][C]2.4362[/C][C]0.008914[/C][/ROW]
[ROW][C]2[/C][C]0.035316[/C][C]0.2736[/C][C]0.392682[/C][/ROW]
[ROW][C]3[/C][C]-0.106081[/C][C]-0.8217[/C][C]0.20725[/C][/ROW]
[ROW][C]4[/C][C]-0.202068[/C][C]-1.5652[/C][C]0.061396[/C][/ROW]
[ROW][C]5[/C][C]-0.158961[/C][C]-1.2313[/C][C]0.111507[/C][/ROW]
[ROW][C]6[/C][C]-0.435777[/C][C]-3.3755[/C][C]0.000648[/C][/ROW]
[ROW][C]7[/C][C]-0.075229[/C][C]-0.5827[/C][C]0.281132[/C][/ROW]
[ROW][C]8[/C][C]-0.100561[/C][C]-0.7789[/C][C]0.219538[/C][/ROW]
[ROW][C]9[/C][C]-0.181959[/C][C]-1.4095[/C][C]0.081932[/C][/ROW]
[ROW][C]10[/C][C]-0.175352[/C][C]-1.3583[/C][C]0.089732[/C][/ROW]
[ROW][C]11[/C][C]0.025324[/C][C]0.1962[/C][C]0.422574[/C][/ROW]
[ROW][C]12[/C][C]0.643373[/C][C]4.9835[/C][C]3e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.343963[/C][C]-2.6643[/C][C]0.004947[/C][/ROW]
[ROW][C]14[/C][C]-0.209729[/C][C]-1.6246[/C][C]0.05475[/C][/ROW]
[ROW][C]15[/C][C]-0.055575[/C][C]-0.4305[/C][C]0.334194[/C][/ROW]
[ROW][C]16[/C][C]0.066702[/C][C]0.5167[/C][C]0.303643[/C][/ROW]
[ROW][C]17[/C][C]-0.079412[/C][C]-0.6151[/C][C]0.2704[/C][/ROW]
[ROW][C]18[/C][C]0.076162[/C][C]0.59[/C][C]0.278719[/C][/ROW]
[ROW][C]19[/C][C]-0.046494[/C][C]-0.3601[/C][C]0.360002[/C][/ROW]
[ROW][C]20[/C][C]-0.230455[/C][C]-1.7851[/C][C]0.03965[/C][/ROW]
[ROW][C]21[/C][C]-0.026932[/C][C]-0.2086[/C][C]0.417728[/C][/ROW]
[ROW][C]22[/C][C]0.055296[/C][C]0.4283[/C][C]0.334977[/C][/ROW]
[ROW][C]23[/C][C]-0.127353[/C][C]-0.9865[/C][C]0.163932[/C][/ROW]
[ROW][C]24[/C][C]-0.188169[/C][C]-1.4576[/C][C]0.075089[/C][/ROW]
[ROW][C]25[/C][C]0.142657[/C][C]1.105[/C][C]0.136783[/C][/ROW]
[ROW][C]26[/C][C]-0.008313[/C][C]-0.0644[/C][C]0.474435[/C][/ROW]
[ROW][C]27[/C][C]-0.014674[/C][C]-0.1137[/C][C]0.454942[/C][/ROW]
[ROW][C]28[/C][C]-0.028659[/C][C]-0.222[/C][C]0.412539[/C][/ROW]
[ROW][C]29[/C][C]0.082938[/C][C]0.6424[/C][C]0.26152[/C][/ROW]
[ROW][C]30[/C][C]-0.041653[/C][C]-0.3226[/C][C]0.374043[/C][/ROW]
[ROW][C]31[/C][C]-0.031639[/C][C]-0.2451[/C][C]0.403617[/C][/ROW]
[ROW][C]32[/C][C]0.06836[/C][C]0.5295[/C][C]0.2992[/C][/ROW]
[ROW][C]33[/C][C]-0.01735[/C][C]-0.1344[/C][C]0.44677[/C][/ROW]
[ROW][C]34[/C][C]0.015149[/C][C]0.1173[/C][C]0.453488[/C][/ROW]
[ROW][C]35[/C][C]-0.024576[/C][C]-0.1904[/C][C]0.424833[/C][/ROW]
[ROW][C]36[/C][C]-0.130414[/C][C]-1.0102[/C][C]0.158232[/C][/ROW]
[ROW][C]37[/C][C]-0.066622[/C][C]-0.516[/C][C]0.303858[/C][/ROW]
[ROW][C]38[/C][C]0.009231[/C][C]0.0715[/C][C]0.471619[/C][/ROW]
[ROW][C]39[/C][C]-0.072366[/C][C]-0.5605[/C][C]0.288599[/C][/ROW]
[ROW][C]40[/C][C]-0.027224[/C][C]-0.2109[/C][C]0.416849[/C][/ROW]
[ROW][C]41[/C][C]-0.048576[/C][C]-0.3763[/C][C]0.354022[/C][/ROW]
[ROW][C]42[/C][C]0.062447[/C][C]0.4837[/C][C]0.315176[/C][/ROW]
[ROW][C]43[/C][C]0.013718[/C][C]0.1063[/C][C]0.457865[/C][/ROW]
[ROW][C]44[/C][C]0.039437[/C][C]0.3055[/C][C]0.38053[/C][/ROW]
[ROW][C]45[/C][C]0.041553[/C][C]0.3219[/C][C]0.374336[/C][/ROW]
[ROW][C]46[/C][C]-0.134545[/C][C]-1.0422[/C][C]0.150754[/C][/ROW]
[ROW][C]47[/C][C]-0.041821[/C][C]-0.3239[/C][C]0.373553[/C][/ROW]
[ROW][C]48[/C][C]-0.070095[/C][C]-0.543[/C][C]0.294587[/C][/ROW]
[ROW][C]49[/C][C]-0.00026[/C][C]-0.002[/C][C]0.499201[/C][/ROW]
[ROW][C]50[/C][C]0.013453[/C][C]0.1042[/C][C]0.458678[/C][/ROW]
[ROW][C]51[/C][C]0.021605[/C][C]0.1674[/C][C]0.433829[/C][/ROW]
[ROW][C]52[/C][C]-0.055065[/C][C]-0.4265[/C][C]0.335624[/C][/ROW]
[ROW][C]53[/C][C]-0.020809[/C][C]-0.1612[/C][C]0.436244[/C][/ROW]
[ROW][C]54[/C][C]-0.073046[/C][C]-0.5658[/C][C]0.286817[/C][/ROW]
[ROW][C]55[/C][C]-0.107448[/C][C]-0.8323[/C][C]0.204274[/C][/ROW]
[ROW][C]56[/C][C]0.040076[/C][C]0.3104[/C][C]0.378656[/C][/ROW]
[ROW][C]57[/C][C]-0.045722[/C][C]-0.3542[/C][C]0.362231[/C][/ROW]
[ROW][C]58[/C][C]-0.020493[/C][C]-0.1587[/C][C]0.437205[/C][/ROW]
[ROW][C]59[/C][C]0.04934[/C][C]0.3822[/C][C]0.351837[/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=71383&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71383&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
10.3145152.43620.008914
20.0353160.27360.392682
3-0.106081-0.82170.20725
4-0.202068-1.56520.061396
5-0.158961-1.23130.111507
6-0.435777-3.37550.000648
7-0.075229-0.58270.281132
8-0.100561-0.77890.219538
9-0.181959-1.40950.081932
10-0.175352-1.35830.089732
110.0253240.19620.422574
120.6433734.98353e-06
13-0.343963-2.66430.004947
14-0.209729-1.62460.05475
15-0.055575-0.43050.334194
160.0667020.51670.303643
17-0.079412-0.61510.2704
180.0761620.590.278719
19-0.046494-0.36010.360002
20-0.230455-1.78510.03965
21-0.026932-0.20860.417728
220.0552960.42830.334977
23-0.127353-0.98650.163932
24-0.188169-1.45760.075089
250.1426571.1050.136783
26-0.008313-0.06440.474435
27-0.014674-0.11370.454942
28-0.028659-0.2220.412539
290.0829380.64240.26152
30-0.041653-0.32260.374043
31-0.031639-0.24510.403617
320.068360.52950.2992
33-0.01735-0.13440.44677
340.0151490.11730.453488
35-0.024576-0.19040.424833
36-0.130414-1.01020.158232
37-0.066622-0.5160.303858
380.0092310.07150.471619
39-0.072366-0.56050.288599
40-0.027224-0.21090.416849
41-0.048576-0.37630.354022
420.0624470.48370.315176
430.0137180.10630.457865
440.0394370.30550.38053
450.0415530.32190.374336
46-0.134545-1.04220.150754
47-0.041821-0.32390.373553
48-0.070095-0.5430.294587
49-0.00026-0.0020.499201
500.0134530.10420.458678
510.0216050.16740.433829
52-0.055065-0.42650.335624
53-0.020809-0.16120.436244
54-0.073046-0.56580.286817
55-0.107448-0.83230.204274
560.0400760.31040.378656
57-0.045722-0.35420.362231
58-0.020493-0.15870.437205
590.049340.38220.351837
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')