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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 computationTue, 04 Dec 2012 12:04:12 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/04/t13546406726yaavazukwy2hg5.htm/, Retrieved Fri, 29 Mar 2024 10:39:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196398, Retrieved Fri, 29 Mar 2024 10:39:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
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]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [autocorrelatiefun...] [2012-12-04 17:04:12] [86f0addf4b5362ca5a545029cdfac14b] [Current]
- RMP         [(Partial) Autocorrelation Function] [Paper2012: ARIMA] [2012-12-20 11:27:19] [f055db2f1c47e4197bf514e64f7886e5]
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Dataseries X:
46
62
66
59
58
61
41
27
58
70
49
59
44
36
72
45
56
54
53
35
61
52
47
51
52
63
74
45
51
64
36
30
55
64
39
40
63
45
59
55
40
64
27
28
45
57
45
69
60
56
58
50
51
53
37
22
55
70
62
58
39
49
58
47
42
62
39
40
72
70
54
65




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196398&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196398&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196398&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.511233-3.92690.000114
20.0887710.68190.248998
3-0.115485-0.88710.189325
40.0553880.42540.336031
5-0.042298-0.32490.373203
6-0.018663-0.14340.443251
70.0470630.36150.359508
80.0195150.14990.440678
9-0.060163-0.46210.322847
10-0.005453-0.04190.483366
110.3242652.49070.007791
12-0.417072-3.20360.001095
130.0908840.69810.24393
140.022930.17610.4304
150.0438430.33680.368746
16-0.015105-0.1160.454014
17-0.054574-0.41920.3383
180.0687670.52820.299667
19-0.002083-0.0160.493645
20-0.096202-0.73890.231437
210.0390320.29980.382686
220.1333711.02440.154905
23-0.086999-0.66830.253288
24-0.079588-0.61130.271666
250.2075281.59410.058134
26-0.239412-1.8390.035478
270.1449881.11370.134968
28-0.144962-1.11350.13501
290.2090921.60610.0568
30-0.108513-0.83350.203962
31-0.064239-0.49340.31177
320.1029690.79090.21608
330.0522260.40120.344878
34-0.085521-0.65690.256899
35-0.025547-0.19620.422551
360.0419650.32230.374168
37-0.130913-1.00560.159367
380.1658081.27360.1039
39-0.101437-0.77910.219503
400.1507421.15790.12579
41-0.177953-1.36690.088424
420.0729720.56050.288628
430.042910.32960.371436
44-0.010028-0.0770.469433
45-0.076522-0.58780.279463
46-0.004938-0.03790.484935
470.0565080.4340.332918
48-0.017645-0.13550.446326
490.0591930.45470.325509
50-0.056731-0.43580.332301
510.0450040.34570.365407
52-0.073088-0.56140.288326
530.0535230.41110.341238
54-0.016128-0.12390.450915
55-0.011643-0.08940.46452
56-0.009445-0.07250.471207
570.0437530.33610.369003
58-0.023426-0.17990.428907
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.511233 & -3.9269 & 0.000114 \tabularnewline
2 & 0.088771 & 0.6819 & 0.248998 \tabularnewline
3 & -0.115485 & -0.8871 & 0.189325 \tabularnewline
4 & 0.055388 & 0.4254 & 0.336031 \tabularnewline
5 & -0.042298 & -0.3249 & 0.373203 \tabularnewline
6 & -0.018663 & -0.1434 & 0.443251 \tabularnewline
7 & 0.047063 & 0.3615 & 0.359508 \tabularnewline
8 & 0.019515 & 0.1499 & 0.440678 \tabularnewline
9 & -0.060163 & -0.4621 & 0.322847 \tabularnewline
10 & -0.005453 & -0.0419 & 0.483366 \tabularnewline
11 & 0.324265 & 2.4907 & 0.007791 \tabularnewline
12 & -0.417072 & -3.2036 & 0.001095 \tabularnewline
13 & 0.090884 & 0.6981 & 0.24393 \tabularnewline
14 & 0.02293 & 0.1761 & 0.4304 \tabularnewline
15 & 0.043843 & 0.3368 & 0.368746 \tabularnewline
16 & -0.015105 & -0.116 & 0.454014 \tabularnewline
17 & -0.054574 & -0.4192 & 0.3383 \tabularnewline
18 & 0.068767 & 0.5282 & 0.299667 \tabularnewline
19 & -0.002083 & -0.016 & 0.493645 \tabularnewline
20 & -0.096202 & -0.7389 & 0.231437 \tabularnewline
21 & 0.039032 & 0.2998 & 0.382686 \tabularnewline
22 & 0.133371 & 1.0244 & 0.154905 \tabularnewline
23 & -0.086999 & -0.6683 & 0.253288 \tabularnewline
24 & -0.079588 & -0.6113 & 0.271666 \tabularnewline
25 & 0.207528 & 1.5941 & 0.058134 \tabularnewline
26 & -0.239412 & -1.839 & 0.035478 \tabularnewline
27 & 0.144988 & 1.1137 & 0.134968 \tabularnewline
28 & -0.144962 & -1.1135 & 0.13501 \tabularnewline
29 & 0.209092 & 1.6061 & 0.0568 \tabularnewline
30 & -0.108513 & -0.8335 & 0.203962 \tabularnewline
31 & -0.064239 & -0.4934 & 0.31177 \tabularnewline
32 & 0.102969 & 0.7909 & 0.21608 \tabularnewline
33 & 0.052226 & 0.4012 & 0.344878 \tabularnewline
34 & -0.085521 & -0.6569 & 0.256899 \tabularnewline
35 & -0.025547 & -0.1962 & 0.422551 \tabularnewline
36 & 0.041965 & 0.3223 & 0.374168 \tabularnewline
37 & -0.130913 & -1.0056 & 0.159367 \tabularnewline
38 & 0.165808 & 1.2736 & 0.1039 \tabularnewline
39 & -0.101437 & -0.7791 & 0.219503 \tabularnewline
40 & 0.150742 & 1.1579 & 0.12579 \tabularnewline
41 & -0.177953 & -1.3669 & 0.088424 \tabularnewline
42 & 0.072972 & 0.5605 & 0.288628 \tabularnewline
43 & 0.04291 & 0.3296 & 0.371436 \tabularnewline
44 & -0.010028 & -0.077 & 0.469433 \tabularnewline
45 & -0.076522 & -0.5878 & 0.279463 \tabularnewline
46 & -0.004938 & -0.0379 & 0.484935 \tabularnewline
47 & 0.056508 & 0.434 & 0.332918 \tabularnewline
48 & -0.017645 & -0.1355 & 0.446326 \tabularnewline
49 & 0.059193 & 0.4547 & 0.325509 \tabularnewline
50 & -0.056731 & -0.4358 & 0.332301 \tabularnewline
51 & 0.045004 & 0.3457 & 0.365407 \tabularnewline
52 & -0.073088 & -0.5614 & 0.288326 \tabularnewline
53 & 0.053523 & 0.4111 & 0.341238 \tabularnewline
54 & -0.016128 & -0.1239 & 0.450915 \tabularnewline
55 & -0.011643 & -0.0894 & 0.46452 \tabularnewline
56 & -0.009445 & -0.0725 & 0.471207 \tabularnewline
57 & 0.043753 & 0.3361 & 0.369003 \tabularnewline
58 & -0.023426 & -0.1799 & 0.428907 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196398&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]-0.511233[/C][C]-3.9269[/C][C]0.000114[/C][/ROW]
[ROW][C]2[/C][C]0.088771[/C][C]0.6819[/C][C]0.248998[/C][/ROW]
[ROW][C]3[/C][C]-0.115485[/C][C]-0.8871[/C][C]0.189325[/C][/ROW]
[ROW][C]4[/C][C]0.055388[/C][C]0.4254[/C][C]0.336031[/C][/ROW]
[ROW][C]5[/C][C]-0.042298[/C][C]-0.3249[/C][C]0.373203[/C][/ROW]
[ROW][C]6[/C][C]-0.018663[/C][C]-0.1434[/C][C]0.443251[/C][/ROW]
[ROW][C]7[/C][C]0.047063[/C][C]0.3615[/C][C]0.359508[/C][/ROW]
[ROW][C]8[/C][C]0.019515[/C][C]0.1499[/C][C]0.440678[/C][/ROW]
[ROW][C]9[/C][C]-0.060163[/C][C]-0.4621[/C][C]0.322847[/C][/ROW]
[ROW][C]10[/C][C]-0.005453[/C][C]-0.0419[/C][C]0.483366[/C][/ROW]
[ROW][C]11[/C][C]0.324265[/C][C]2.4907[/C][C]0.007791[/C][/ROW]
[ROW][C]12[/C][C]-0.417072[/C][C]-3.2036[/C][C]0.001095[/C][/ROW]
[ROW][C]13[/C][C]0.090884[/C][C]0.6981[/C][C]0.24393[/C][/ROW]
[ROW][C]14[/C][C]0.02293[/C][C]0.1761[/C][C]0.4304[/C][/ROW]
[ROW][C]15[/C][C]0.043843[/C][C]0.3368[/C][C]0.368746[/C][/ROW]
[ROW][C]16[/C][C]-0.015105[/C][C]-0.116[/C][C]0.454014[/C][/ROW]
[ROW][C]17[/C][C]-0.054574[/C][C]-0.4192[/C][C]0.3383[/C][/ROW]
[ROW][C]18[/C][C]0.068767[/C][C]0.5282[/C][C]0.299667[/C][/ROW]
[ROW][C]19[/C][C]-0.002083[/C][C]-0.016[/C][C]0.493645[/C][/ROW]
[ROW][C]20[/C][C]-0.096202[/C][C]-0.7389[/C][C]0.231437[/C][/ROW]
[ROW][C]21[/C][C]0.039032[/C][C]0.2998[/C][C]0.382686[/C][/ROW]
[ROW][C]22[/C][C]0.133371[/C][C]1.0244[/C][C]0.154905[/C][/ROW]
[ROW][C]23[/C][C]-0.086999[/C][C]-0.6683[/C][C]0.253288[/C][/ROW]
[ROW][C]24[/C][C]-0.079588[/C][C]-0.6113[/C][C]0.271666[/C][/ROW]
[ROW][C]25[/C][C]0.207528[/C][C]1.5941[/C][C]0.058134[/C][/ROW]
[ROW][C]26[/C][C]-0.239412[/C][C]-1.839[/C][C]0.035478[/C][/ROW]
[ROW][C]27[/C][C]0.144988[/C][C]1.1137[/C][C]0.134968[/C][/ROW]
[ROW][C]28[/C][C]-0.144962[/C][C]-1.1135[/C][C]0.13501[/C][/ROW]
[ROW][C]29[/C][C]0.209092[/C][C]1.6061[/C][C]0.0568[/C][/ROW]
[ROW][C]30[/C][C]-0.108513[/C][C]-0.8335[/C][C]0.203962[/C][/ROW]
[ROW][C]31[/C][C]-0.064239[/C][C]-0.4934[/C][C]0.31177[/C][/ROW]
[ROW][C]32[/C][C]0.102969[/C][C]0.7909[/C][C]0.21608[/C][/ROW]
[ROW][C]33[/C][C]0.052226[/C][C]0.4012[/C][C]0.344878[/C][/ROW]
[ROW][C]34[/C][C]-0.085521[/C][C]-0.6569[/C][C]0.256899[/C][/ROW]
[ROW][C]35[/C][C]-0.025547[/C][C]-0.1962[/C][C]0.422551[/C][/ROW]
[ROW][C]36[/C][C]0.041965[/C][C]0.3223[/C][C]0.374168[/C][/ROW]
[ROW][C]37[/C][C]-0.130913[/C][C]-1.0056[/C][C]0.159367[/C][/ROW]
[ROW][C]38[/C][C]0.165808[/C][C]1.2736[/C][C]0.1039[/C][/ROW]
[ROW][C]39[/C][C]-0.101437[/C][C]-0.7791[/C][C]0.219503[/C][/ROW]
[ROW][C]40[/C][C]0.150742[/C][C]1.1579[/C][C]0.12579[/C][/ROW]
[ROW][C]41[/C][C]-0.177953[/C][C]-1.3669[/C][C]0.088424[/C][/ROW]
[ROW][C]42[/C][C]0.072972[/C][C]0.5605[/C][C]0.288628[/C][/ROW]
[ROW][C]43[/C][C]0.04291[/C][C]0.3296[/C][C]0.371436[/C][/ROW]
[ROW][C]44[/C][C]-0.010028[/C][C]-0.077[/C][C]0.469433[/C][/ROW]
[ROW][C]45[/C][C]-0.076522[/C][C]-0.5878[/C][C]0.279463[/C][/ROW]
[ROW][C]46[/C][C]-0.004938[/C][C]-0.0379[/C][C]0.484935[/C][/ROW]
[ROW][C]47[/C][C]0.056508[/C][C]0.434[/C][C]0.332918[/C][/ROW]
[ROW][C]48[/C][C]-0.017645[/C][C]-0.1355[/C][C]0.446326[/C][/ROW]
[ROW][C]49[/C][C]0.059193[/C][C]0.4547[/C][C]0.325509[/C][/ROW]
[ROW][C]50[/C][C]-0.056731[/C][C]-0.4358[/C][C]0.332301[/C][/ROW]
[ROW][C]51[/C][C]0.045004[/C][C]0.3457[/C][C]0.365407[/C][/ROW]
[ROW][C]52[/C][C]-0.073088[/C][C]-0.5614[/C][C]0.288326[/C][/ROW]
[ROW][C]53[/C][C]0.053523[/C][C]0.4111[/C][C]0.341238[/C][/ROW]
[ROW][C]54[/C][C]-0.016128[/C][C]-0.1239[/C][C]0.450915[/C][/ROW]
[ROW][C]55[/C][C]-0.011643[/C][C]-0.0894[/C][C]0.46452[/C][/ROW]
[ROW][C]56[/C][C]-0.009445[/C][C]-0.0725[/C][C]0.471207[/C][/ROW]
[ROW][C]57[/C][C]0.043753[/C][C]0.3361[/C][C]0.369003[/C][/ROW]
[ROW][C]58[/C][C]-0.023426[/C][C]-0.1799[/C][C]0.428907[/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=196398&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196398&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
1-0.511233-3.92690.000114
20.0887710.68190.248998
3-0.115485-0.88710.189325
40.0553880.42540.336031
5-0.042298-0.32490.373203
6-0.018663-0.14340.443251
70.0470630.36150.359508
80.0195150.14990.440678
9-0.060163-0.46210.322847
10-0.005453-0.04190.483366
110.3242652.49070.007791
12-0.417072-3.20360.001095
130.0908840.69810.24393
140.022930.17610.4304
150.0438430.33680.368746
16-0.015105-0.1160.454014
17-0.054574-0.41920.3383
180.0687670.52820.299667
19-0.002083-0.0160.493645
20-0.096202-0.73890.231437
210.0390320.29980.382686
220.1333711.02440.154905
23-0.086999-0.66830.253288
24-0.079588-0.61130.271666
250.2075281.59410.058134
26-0.239412-1.8390.035478
270.1449881.11370.134968
28-0.144962-1.11350.13501
290.2090921.60610.0568
30-0.108513-0.83350.203962
31-0.064239-0.49340.31177
320.1029690.79090.21608
330.0522260.40120.344878
34-0.085521-0.65690.256899
35-0.025547-0.19620.422551
360.0419650.32230.374168
37-0.130913-1.00560.159367
380.1658081.27360.1039
39-0.101437-0.77910.219503
400.1507421.15790.12579
41-0.177953-1.36690.088424
420.0729720.56050.288628
430.042910.32960.371436
44-0.010028-0.0770.469433
45-0.076522-0.58780.279463
46-0.004938-0.03790.484935
470.0565080.4340.332918
48-0.017645-0.13550.446326
490.0591930.45470.325509
50-0.056731-0.43580.332301
510.0450040.34570.365407
52-0.073088-0.56140.288326
530.0535230.41110.341238
54-0.016128-0.12390.450915
55-0.011643-0.08940.46452
56-0.009445-0.07250.471207
570.0437530.33610.369003
58-0.023426-0.17990.428907
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.511233-3.92690.000114
2-0.233657-1.79480.038908
3-0.256263-1.96840.026864
4-0.184354-1.4160.081009
5-0.183561-1.410.0819
6-0.231754-1.78010.040101
7-0.172939-1.32840.094586
8-0.107066-0.82240.207084
9-0.182652-1.4030.082932
10-0.245783-1.88790.03198
110.3380652.59670.005931
12-0.021801-0.16750.43379
13-0.192832-1.48120.071941
14-0.023784-0.18270.427833
15-0.020807-0.15980.436783
16-0.018186-0.13970.44469
17-0.107145-0.8230.206912
18-0.133437-1.0250.154785
19-0.068288-0.52450.300939
20-0.160527-1.2330.111227
21-0.341173-2.62060.005572
22-0.228632-1.75620.042126
230.1823121.40040.08332
24-0.153807-1.18140.121089
250.0661940.50840.306517
26-0.102879-0.79020.216279
270.001170.0090.49643
28-0.032504-0.24970.401856
290.0293840.22570.411106
300.024050.18470.427035
31-0.049991-0.3840.351185
32-0.043589-0.33480.369475
33-0.123506-0.94870.17333
340.0453260.34820.364482
350.1960451.50580.068721
36-0.036125-0.27750.391191
37-0.054987-0.42240.337149
380.0012720.00980.496119
390.0266530.20470.419245
400.0095520.07340.47088
41-0.055058-0.42290.336951
420.0836570.64260.261493
430.1026890.78880.216703
44-0.000785-0.0060.497606
45-0.118126-0.90730.183959
46-0.006589-0.05060.479903
470.1160810.89160.188106
48-0.028806-0.22130.412826
490.0188790.1450.442597
50-0.004551-0.0350.486117
510.1016290.78060.219072
52-0.028972-0.22250.412333
530.0359090.27580.391824
54-0.002828-0.02170.491371
550.0097170.07460.470379
56-0.0412-0.31650.376384
57-0.111947-0.85990.196668
58-0.08379-0.64360.261163
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.511233 & -3.9269 & 0.000114 \tabularnewline
2 & -0.233657 & -1.7948 & 0.038908 \tabularnewline
3 & -0.256263 & -1.9684 & 0.026864 \tabularnewline
4 & -0.184354 & -1.416 & 0.081009 \tabularnewline
5 & -0.183561 & -1.41 & 0.0819 \tabularnewline
6 & -0.231754 & -1.7801 & 0.040101 \tabularnewline
7 & -0.172939 & -1.3284 & 0.094586 \tabularnewline
8 & -0.107066 & -0.8224 & 0.207084 \tabularnewline
9 & -0.182652 & -1.403 & 0.082932 \tabularnewline
10 & -0.245783 & -1.8879 & 0.03198 \tabularnewline
11 & 0.338065 & 2.5967 & 0.005931 \tabularnewline
12 & -0.021801 & -0.1675 & 0.43379 \tabularnewline
13 & -0.192832 & -1.4812 & 0.071941 \tabularnewline
14 & -0.023784 & -0.1827 & 0.427833 \tabularnewline
15 & -0.020807 & -0.1598 & 0.436783 \tabularnewline
16 & -0.018186 & -0.1397 & 0.44469 \tabularnewline
17 & -0.107145 & -0.823 & 0.206912 \tabularnewline
18 & -0.133437 & -1.025 & 0.154785 \tabularnewline
19 & -0.068288 & -0.5245 & 0.300939 \tabularnewline
20 & -0.160527 & -1.233 & 0.111227 \tabularnewline
21 & -0.341173 & -2.6206 & 0.005572 \tabularnewline
22 & -0.228632 & -1.7562 & 0.042126 \tabularnewline
23 & 0.182312 & 1.4004 & 0.08332 \tabularnewline
24 & -0.153807 & -1.1814 & 0.121089 \tabularnewline
25 & 0.066194 & 0.5084 & 0.306517 \tabularnewline
26 & -0.102879 & -0.7902 & 0.216279 \tabularnewline
27 & 0.00117 & 0.009 & 0.49643 \tabularnewline
28 & -0.032504 & -0.2497 & 0.401856 \tabularnewline
29 & 0.029384 & 0.2257 & 0.411106 \tabularnewline
30 & 0.02405 & 0.1847 & 0.427035 \tabularnewline
31 & -0.049991 & -0.384 & 0.351185 \tabularnewline
32 & -0.043589 & -0.3348 & 0.369475 \tabularnewline
33 & -0.123506 & -0.9487 & 0.17333 \tabularnewline
34 & 0.045326 & 0.3482 & 0.364482 \tabularnewline
35 & 0.196045 & 1.5058 & 0.068721 \tabularnewline
36 & -0.036125 & -0.2775 & 0.391191 \tabularnewline
37 & -0.054987 & -0.4224 & 0.337149 \tabularnewline
38 & 0.001272 & 0.0098 & 0.496119 \tabularnewline
39 & 0.026653 & 0.2047 & 0.419245 \tabularnewline
40 & 0.009552 & 0.0734 & 0.47088 \tabularnewline
41 & -0.055058 & -0.4229 & 0.336951 \tabularnewline
42 & 0.083657 & 0.6426 & 0.261493 \tabularnewline
43 & 0.102689 & 0.7888 & 0.216703 \tabularnewline
44 & -0.000785 & -0.006 & 0.497606 \tabularnewline
45 & -0.118126 & -0.9073 & 0.183959 \tabularnewline
46 & -0.006589 & -0.0506 & 0.479903 \tabularnewline
47 & 0.116081 & 0.8916 & 0.188106 \tabularnewline
48 & -0.028806 & -0.2213 & 0.412826 \tabularnewline
49 & 0.018879 & 0.145 & 0.442597 \tabularnewline
50 & -0.004551 & -0.035 & 0.486117 \tabularnewline
51 & 0.101629 & 0.7806 & 0.219072 \tabularnewline
52 & -0.028972 & -0.2225 & 0.412333 \tabularnewline
53 & 0.035909 & 0.2758 & 0.391824 \tabularnewline
54 & -0.002828 & -0.0217 & 0.491371 \tabularnewline
55 & 0.009717 & 0.0746 & 0.470379 \tabularnewline
56 & -0.0412 & -0.3165 & 0.376384 \tabularnewline
57 & -0.111947 & -0.8599 & 0.196668 \tabularnewline
58 & -0.08379 & -0.6436 & 0.261163 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196398&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]-0.511233[/C][C]-3.9269[/C][C]0.000114[/C][/ROW]
[ROW][C]2[/C][C]-0.233657[/C][C]-1.7948[/C][C]0.038908[/C][/ROW]
[ROW][C]3[/C][C]-0.256263[/C][C]-1.9684[/C][C]0.026864[/C][/ROW]
[ROW][C]4[/C][C]-0.184354[/C][C]-1.416[/C][C]0.081009[/C][/ROW]
[ROW][C]5[/C][C]-0.183561[/C][C]-1.41[/C][C]0.0819[/C][/ROW]
[ROW][C]6[/C][C]-0.231754[/C][C]-1.7801[/C][C]0.040101[/C][/ROW]
[ROW][C]7[/C][C]-0.172939[/C][C]-1.3284[/C][C]0.094586[/C][/ROW]
[ROW][C]8[/C][C]-0.107066[/C][C]-0.8224[/C][C]0.207084[/C][/ROW]
[ROW][C]9[/C][C]-0.182652[/C][C]-1.403[/C][C]0.082932[/C][/ROW]
[ROW][C]10[/C][C]-0.245783[/C][C]-1.8879[/C][C]0.03198[/C][/ROW]
[ROW][C]11[/C][C]0.338065[/C][C]2.5967[/C][C]0.005931[/C][/ROW]
[ROW][C]12[/C][C]-0.021801[/C][C]-0.1675[/C][C]0.43379[/C][/ROW]
[ROW][C]13[/C][C]-0.192832[/C][C]-1.4812[/C][C]0.071941[/C][/ROW]
[ROW][C]14[/C][C]-0.023784[/C][C]-0.1827[/C][C]0.427833[/C][/ROW]
[ROW][C]15[/C][C]-0.020807[/C][C]-0.1598[/C][C]0.436783[/C][/ROW]
[ROW][C]16[/C][C]-0.018186[/C][C]-0.1397[/C][C]0.44469[/C][/ROW]
[ROW][C]17[/C][C]-0.107145[/C][C]-0.823[/C][C]0.206912[/C][/ROW]
[ROW][C]18[/C][C]-0.133437[/C][C]-1.025[/C][C]0.154785[/C][/ROW]
[ROW][C]19[/C][C]-0.068288[/C][C]-0.5245[/C][C]0.300939[/C][/ROW]
[ROW][C]20[/C][C]-0.160527[/C][C]-1.233[/C][C]0.111227[/C][/ROW]
[ROW][C]21[/C][C]-0.341173[/C][C]-2.6206[/C][C]0.005572[/C][/ROW]
[ROW][C]22[/C][C]-0.228632[/C][C]-1.7562[/C][C]0.042126[/C][/ROW]
[ROW][C]23[/C][C]0.182312[/C][C]1.4004[/C][C]0.08332[/C][/ROW]
[ROW][C]24[/C][C]-0.153807[/C][C]-1.1814[/C][C]0.121089[/C][/ROW]
[ROW][C]25[/C][C]0.066194[/C][C]0.5084[/C][C]0.306517[/C][/ROW]
[ROW][C]26[/C][C]-0.102879[/C][C]-0.7902[/C][C]0.216279[/C][/ROW]
[ROW][C]27[/C][C]0.00117[/C][C]0.009[/C][C]0.49643[/C][/ROW]
[ROW][C]28[/C][C]-0.032504[/C][C]-0.2497[/C][C]0.401856[/C][/ROW]
[ROW][C]29[/C][C]0.029384[/C][C]0.2257[/C][C]0.411106[/C][/ROW]
[ROW][C]30[/C][C]0.02405[/C][C]0.1847[/C][C]0.427035[/C][/ROW]
[ROW][C]31[/C][C]-0.049991[/C][C]-0.384[/C][C]0.351185[/C][/ROW]
[ROW][C]32[/C][C]-0.043589[/C][C]-0.3348[/C][C]0.369475[/C][/ROW]
[ROW][C]33[/C][C]-0.123506[/C][C]-0.9487[/C][C]0.17333[/C][/ROW]
[ROW][C]34[/C][C]0.045326[/C][C]0.3482[/C][C]0.364482[/C][/ROW]
[ROW][C]35[/C][C]0.196045[/C][C]1.5058[/C][C]0.068721[/C][/ROW]
[ROW][C]36[/C][C]-0.036125[/C][C]-0.2775[/C][C]0.391191[/C][/ROW]
[ROW][C]37[/C][C]-0.054987[/C][C]-0.4224[/C][C]0.337149[/C][/ROW]
[ROW][C]38[/C][C]0.001272[/C][C]0.0098[/C][C]0.496119[/C][/ROW]
[ROW][C]39[/C][C]0.026653[/C][C]0.2047[/C][C]0.419245[/C][/ROW]
[ROW][C]40[/C][C]0.009552[/C][C]0.0734[/C][C]0.47088[/C][/ROW]
[ROW][C]41[/C][C]-0.055058[/C][C]-0.4229[/C][C]0.336951[/C][/ROW]
[ROW][C]42[/C][C]0.083657[/C][C]0.6426[/C][C]0.261493[/C][/ROW]
[ROW][C]43[/C][C]0.102689[/C][C]0.7888[/C][C]0.216703[/C][/ROW]
[ROW][C]44[/C][C]-0.000785[/C][C]-0.006[/C][C]0.497606[/C][/ROW]
[ROW][C]45[/C][C]-0.118126[/C][C]-0.9073[/C][C]0.183959[/C][/ROW]
[ROW][C]46[/C][C]-0.006589[/C][C]-0.0506[/C][C]0.479903[/C][/ROW]
[ROW][C]47[/C][C]0.116081[/C][C]0.8916[/C][C]0.188106[/C][/ROW]
[ROW][C]48[/C][C]-0.028806[/C][C]-0.2213[/C][C]0.412826[/C][/ROW]
[ROW][C]49[/C][C]0.018879[/C][C]0.145[/C][C]0.442597[/C][/ROW]
[ROW][C]50[/C][C]-0.004551[/C][C]-0.035[/C][C]0.486117[/C][/ROW]
[ROW][C]51[/C][C]0.101629[/C][C]0.7806[/C][C]0.219072[/C][/ROW]
[ROW][C]52[/C][C]-0.028972[/C][C]-0.2225[/C][C]0.412333[/C][/ROW]
[ROW][C]53[/C][C]0.035909[/C][C]0.2758[/C][C]0.391824[/C][/ROW]
[ROW][C]54[/C][C]-0.002828[/C][C]-0.0217[/C][C]0.491371[/C][/ROW]
[ROW][C]55[/C][C]0.009717[/C][C]0.0746[/C][C]0.470379[/C][/ROW]
[ROW][C]56[/C][C]-0.0412[/C][C]-0.3165[/C][C]0.376384[/C][/ROW]
[ROW][C]57[/C][C]-0.111947[/C][C]-0.8599[/C][C]0.196668[/C][/ROW]
[ROW][C]58[/C][C]-0.08379[/C][C]-0.6436[/C][C]0.261163[/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=196398&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196398&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
1-0.511233-3.92690.000114
2-0.233657-1.79480.038908
3-0.256263-1.96840.026864
4-0.184354-1.4160.081009
5-0.183561-1.410.0819
6-0.231754-1.78010.040101
7-0.172939-1.32840.094586
8-0.107066-0.82240.207084
9-0.182652-1.4030.082932
10-0.245783-1.88790.03198
110.3380652.59670.005931
12-0.021801-0.16750.43379
13-0.192832-1.48120.071941
14-0.023784-0.18270.427833
15-0.020807-0.15980.436783
16-0.018186-0.13970.44469
17-0.107145-0.8230.206912
18-0.133437-1.0250.154785
19-0.068288-0.52450.300939
20-0.160527-1.2330.111227
21-0.341173-2.62060.005572
22-0.228632-1.75620.042126
230.1823121.40040.08332
24-0.153807-1.18140.121089
250.0661940.50840.306517
26-0.102879-0.79020.216279
270.001170.0090.49643
28-0.032504-0.24970.401856
290.0293840.22570.411106
300.024050.18470.427035
31-0.049991-0.3840.351185
32-0.043589-0.33480.369475
33-0.123506-0.94870.17333
340.0453260.34820.364482
350.1960451.50580.068721
36-0.036125-0.27750.391191
37-0.054987-0.42240.337149
380.0012720.00980.496119
390.0266530.20470.419245
400.0095520.07340.47088
41-0.055058-0.42290.336951
420.0836570.64260.261493
430.1026890.78880.216703
44-0.000785-0.0060.497606
45-0.118126-0.90730.183959
46-0.006589-0.05060.479903
470.1160810.89160.188106
48-0.028806-0.22130.412826
490.0188790.1450.442597
50-0.004551-0.0350.486117
510.1016290.78060.219072
52-0.028972-0.22250.412333
530.0359090.27580.391824
54-0.002828-0.02170.491371
550.0097170.07460.470379
56-0.0412-0.31650.376384
57-0.111947-0.85990.196668
58-0.08379-0.64360.261163
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')