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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 10 Dec 2007 12:56:20 -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/2007/Dec/10/t1197315788xowfyhcavcqvfwm.htm/, Retrieved Mon, 06 May 2024 18:10:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3030, Retrieved Mon, 06 May 2024 18:10:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsLise Swinnen
Estimated Impact223
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [paper (acf/vrm 3)] [2007-12-10 19:56:20] [a526d213baffe7453818dd375c9a7100] [Current]
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Dataseries X:
0,007850049
0,008671912
0,008391986
0,008691954
0,008724839
0,008949762
0,009344295
0,009971514
0,010388067
0,008884599
0,01000981
0,012393539
0,007933519
0,008087396
0,008120881
0,008147148
0,00917087
0,009668358
0,009897495
0,011217878
0,010190084
0,009560637
0,011200671
0,013546776
0,008524882
0,009142143
0,008793047
0,009296235
0,009974995
0,009692013
0,010120046
0,011004981
0,010328492
0,009428406
0,011114429
0,011798579
0,008997058
0,008803914
0,007974159
0,008460945
0,009917747
0,009604284
0,011028851
0,011162991
0,010420855
0,009897095
0,010715298
0,012461041
0,008754735
0,009381664
0,008843755
0,009235122
0,009973356
0,009146341
0,011038445
0,010830104
0,010585414
0,010560523
0,010897526
0,014012667




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3030&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3030&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3030&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
016.92820
10.301492.08880.021027
20.3466392.40160.010122
30.1687451.16910.124069
40.1011960.70110.24331
50.1100230.76230.224818
60.0500650.34690.365107
7-0.065753-0.45560.674617
8-0.056593-0.39210.651635
9-0.007477-0.05180.520549
10-0.244823-1.69620.951836
11-0.241912-1.6760.949881
12-0.393321-2.7250.995527
13-0.312086-2.16220.982191
14-0.172771-1.1970.881406
15-0.065192-0.45170.673227
16-0.262328-1.81750.962304
170.0132930.09210.463502
18-0.055315-0.38320.64838
19-0.057408-0.39770.653706
200.0215690.14940.440919
21-0.06458-0.44740.671708
220.0001067e-040.499707
230.1199090.83080.205114
240.0055910.03870.48463
250.0703150.48720.314182
260.0692030.47950.316896
27-0.049052-0.33980.63227
28-0.007071-0.0490.519436
29-0.048554-0.33640.630978
30-0.060705-0.42060.662028
310.0305990.2120.416505
320.061780.4280.335273
330.0674930.46760.321092
340.0314840.21810.414128
350.0155650.10780.457287
36-0.02951-0.20450.580567
37-0.00763-0.05290.52097
380.0406320.28150.389766
39-0.002565-0.01780.507052
400.1364790.94560.174555
410.0569710.39470.347405
420.0422340.29260.385543
430.0123290.08540.466142
44-0.069026-0.47820.682669
45-0.035258-0.24430.595972
46-0.054903-0.38040.647328
47-0.009878-0.06840.52714

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 6.9282 & 0 \tabularnewline
1 & 0.30149 & 2.0888 & 0.021027 \tabularnewline
2 & 0.346639 & 2.4016 & 0.010122 \tabularnewline
3 & 0.168745 & 1.1691 & 0.124069 \tabularnewline
4 & 0.101196 & 0.7011 & 0.24331 \tabularnewline
5 & 0.110023 & 0.7623 & 0.224818 \tabularnewline
6 & 0.050065 & 0.3469 & 0.365107 \tabularnewline
7 & -0.065753 & -0.4556 & 0.674617 \tabularnewline
8 & -0.056593 & -0.3921 & 0.651635 \tabularnewline
9 & -0.007477 & -0.0518 & 0.520549 \tabularnewline
10 & -0.244823 & -1.6962 & 0.951836 \tabularnewline
11 & -0.241912 & -1.676 & 0.949881 \tabularnewline
12 & -0.393321 & -2.725 & 0.995527 \tabularnewline
13 & -0.312086 & -2.1622 & 0.982191 \tabularnewline
14 & -0.172771 & -1.197 & 0.881406 \tabularnewline
15 & -0.065192 & -0.4517 & 0.673227 \tabularnewline
16 & -0.262328 & -1.8175 & 0.962304 \tabularnewline
17 & 0.013293 & 0.0921 & 0.463502 \tabularnewline
18 & -0.055315 & -0.3832 & 0.64838 \tabularnewline
19 & -0.057408 & -0.3977 & 0.653706 \tabularnewline
20 & 0.021569 & 0.1494 & 0.440919 \tabularnewline
21 & -0.06458 & -0.4474 & 0.671708 \tabularnewline
22 & 0.000106 & 7e-04 & 0.499707 \tabularnewline
23 & 0.119909 & 0.8308 & 0.205114 \tabularnewline
24 & 0.005591 & 0.0387 & 0.48463 \tabularnewline
25 & 0.070315 & 0.4872 & 0.314182 \tabularnewline
26 & 0.069203 & 0.4795 & 0.316896 \tabularnewline
27 & -0.049052 & -0.3398 & 0.63227 \tabularnewline
28 & -0.007071 & -0.049 & 0.519436 \tabularnewline
29 & -0.048554 & -0.3364 & 0.630978 \tabularnewline
30 & -0.060705 & -0.4206 & 0.662028 \tabularnewline
31 & 0.030599 & 0.212 & 0.416505 \tabularnewline
32 & 0.06178 & 0.428 & 0.335273 \tabularnewline
33 & 0.067493 & 0.4676 & 0.321092 \tabularnewline
34 & 0.031484 & 0.2181 & 0.414128 \tabularnewline
35 & 0.015565 & 0.1078 & 0.457287 \tabularnewline
36 & -0.02951 & -0.2045 & 0.580567 \tabularnewline
37 & -0.00763 & -0.0529 & 0.52097 \tabularnewline
38 & 0.040632 & 0.2815 & 0.389766 \tabularnewline
39 & -0.002565 & -0.0178 & 0.507052 \tabularnewline
40 & 0.136479 & 0.9456 & 0.174555 \tabularnewline
41 & 0.056971 & 0.3947 & 0.347405 \tabularnewline
42 & 0.042234 & 0.2926 & 0.385543 \tabularnewline
43 & 0.012329 & 0.0854 & 0.466142 \tabularnewline
44 & -0.069026 & -0.4782 & 0.682669 \tabularnewline
45 & -0.035258 & -0.2443 & 0.595972 \tabularnewline
46 & -0.054903 & -0.3804 & 0.647328 \tabularnewline
47 & -0.009878 & -0.0684 & 0.52714 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3030&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]0[/C][C]1[/C][C]6.9282[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.30149[/C][C]2.0888[/C][C]0.021027[/C][/ROW]
[ROW][C]2[/C][C]0.346639[/C][C]2.4016[/C][C]0.010122[/C][/ROW]
[ROW][C]3[/C][C]0.168745[/C][C]1.1691[/C][C]0.124069[/C][/ROW]
[ROW][C]4[/C][C]0.101196[/C][C]0.7011[/C][C]0.24331[/C][/ROW]
[ROW][C]5[/C][C]0.110023[/C][C]0.7623[/C][C]0.224818[/C][/ROW]
[ROW][C]6[/C][C]0.050065[/C][C]0.3469[/C][C]0.365107[/C][/ROW]
[ROW][C]7[/C][C]-0.065753[/C][C]-0.4556[/C][C]0.674617[/C][/ROW]
[ROW][C]8[/C][C]-0.056593[/C][C]-0.3921[/C][C]0.651635[/C][/ROW]
[ROW][C]9[/C][C]-0.007477[/C][C]-0.0518[/C][C]0.520549[/C][/ROW]
[ROW][C]10[/C][C]-0.244823[/C][C]-1.6962[/C][C]0.951836[/C][/ROW]
[ROW][C]11[/C][C]-0.241912[/C][C]-1.676[/C][C]0.949881[/C][/ROW]
[ROW][C]12[/C][C]-0.393321[/C][C]-2.725[/C][C]0.995527[/C][/ROW]
[ROW][C]13[/C][C]-0.312086[/C][C]-2.1622[/C][C]0.982191[/C][/ROW]
[ROW][C]14[/C][C]-0.172771[/C][C]-1.197[/C][C]0.881406[/C][/ROW]
[ROW][C]15[/C][C]-0.065192[/C][C]-0.4517[/C][C]0.673227[/C][/ROW]
[ROW][C]16[/C][C]-0.262328[/C][C]-1.8175[/C][C]0.962304[/C][/ROW]
[ROW][C]17[/C][C]0.013293[/C][C]0.0921[/C][C]0.463502[/C][/ROW]
[ROW][C]18[/C][C]-0.055315[/C][C]-0.3832[/C][C]0.64838[/C][/ROW]
[ROW][C]19[/C][C]-0.057408[/C][C]-0.3977[/C][C]0.653706[/C][/ROW]
[ROW][C]20[/C][C]0.021569[/C][C]0.1494[/C][C]0.440919[/C][/ROW]
[ROW][C]21[/C][C]-0.06458[/C][C]-0.4474[/C][C]0.671708[/C][/ROW]
[ROW][C]22[/C][C]0.000106[/C][C]7e-04[/C][C]0.499707[/C][/ROW]
[ROW][C]23[/C][C]0.119909[/C][C]0.8308[/C][C]0.205114[/C][/ROW]
[ROW][C]24[/C][C]0.005591[/C][C]0.0387[/C][C]0.48463[/C][/ROW]
[ROW][C]25[/C][C]0.070315[/C][C]0.4872[/C][C]0.314182[/C][/ROW]
[ROW][C]26[/C][C]0.069203[/C][C]0.4795[/C][C]0.316896[/C][/ROW]
[ROW][C]27[/C][C]-0.049052[/C][C]-0.3398[/C][C]0.63227[/C][/ROW]
[ROW][C]28[/C][C]-0.007071[/C][C]-0.049[/C][C]0.519436[/C][/ROW]
[ROW][C]29[/C][C]-0.048554[/C][C]-0.3364[/C][C]0.630978[/C][/ROW]
[ROW][C]30[/C][C]-0.060705[/C][C]-0.4206[/C][C]0.662028[/C][/ROW]
[ROW][C]31[/C][C]0.030599[/C][C]0.212[/C][C]0.416505[/C][/ROW]
[ROW][C]32[/C][C]0.06178[/C][C]0.428[/C][C]0.335273[/C][/ROW]
[ROW][C]33[/C][C]0.067493[/C][C]0.4676[/C][C]0.321092[/C][/ROW]
[ROW][C]34[/C][C]0.031484[/C][C]0.2181[/C][C]0.414128[/C][/ROW]
[ROW][C]35[/C][C]0.015565[/C][C]0.1078[/C][C]0.457287[/C][/ROW]
[ROW][C]36[/C][C]-0.02951[/C][C]-0.2045[/C][C]0.580567[/C][/ROW]
[ROW][C]37[/C][C]-0.00763[/C][C]-0.0529[/C][C]0.52097[/C][/ROW]
[ROW][C]38[/C][C]0.040632[/C][C]0.2815[/C][C]0.389766[/C][/ROW]
[ROW][C]39[/C][C]-0.002565[/C][C]-0.0178[/C][C]0.507052[/C][/ROW]
[ROW][C]40[/C][C]0.136479[/C][C]0.9456[/C][C]0.174555[/C][/ROW]
[ROW][C]41[/C][C]0.056971[/C][C]0.3947[/C][C]0.347405[/C][/ROW]
[ROW][C]42[/C][C]0.042234[/C][C]0.2926[/C][C]0.385543[/C][/ROW]
[ROW][C]43[/C][C]0.012329[/C][C]0.0854[/C][C]0.466142[/C][/ROW]
[ROW][C]44[/C][C]-0.069026[/C][C]-0.4782[/C][C]0.682669[/C][/ROW]
[ROW][C]45[/C][C]-0.035258[/C][C]-0.2443[/C][C]0.595972[/C][/ROW]
[ROW][C]46[/C][C]-0.054903[/C][C]-0.3804[/C][C]0.647328[/C][/ROW]
[ROW][C]47[/C][C]-0.009878[/C][C]-0.0684[/C][C]0.52714[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3030&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3030&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
016.92820
10.301492.08880.021027
20.3466392.40160.010122
30.1687451.16910.124069
40.1011960.70110.24331
50.1100230.76230.224818
60.0500650.34690.365107
7-0.065753-0.45560.674617
8-0.056593-0.39210.651635
9-0.007477-0.05180.520549
10-0.244823-1.69620.951836
11-0.241912-1.6760.949881
12-0.393321-2.7250.995527
13-0.312086-2.16220.982191
14-0.172771-1.1970.881406
15-0.065192-0.45170.673227
16-0.262328-1.81750.962304
170.0132930.09210.463502
18-0.055315-0.38320.64838
19-0.057408-0.39770.653706
200.0215690.14940.440919
21-0.06458-0.44740.671708
220.0001067e-040.499707
230.1199090.83080.205114
240.0055910.03870.48463
250.0703150.48720.314182
260.0692030.47950.316896
27-0.049052-0.33980.63227
28-0.007071-0.0490.519436
29-0.048554-0.33640.630978
30-0.060705-0.42060.662028
310.0305990.2120.416505
320.061780.4280.335273
330.0674930.46760.321092
340.0314840.21810.414128
350.0155650.10780.457287
36-0.02951-0.20450.580567
37-0.00763-0.05290.52097
380.0406320.28150.389766
39-0.002565-0.01780.507052
400.1364790.94560.174555
410.0569710.39470.347405
420.0422340.29260.385543
430.0123290.08540.466142
44-0.069026-0.47820.682669
45-0.035258-0.24430.595972
46-0.054903-0.38040.647328
47-0.009878-0.06840.52714







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.301492.08880.021027
10.2813131.9490.028577
20.0105390.0730.471049
3-0.041533-0.28780.612612
40.0539750.3740.355044
5-0.001854-0.01280.505099
6-0.141913-0.98320.834782
7-0.042759-0.29620.615838
80.088610.61390.271087
9-0.267844-1.85570.965177
10-0.205048-1.42060.919054
11-0.206282-1.42920.920284
12-0.067806-0.46980.679678
130.0804870.55760.289845
140.1580851.09520.139437
15-0.248299-1.72030.954087
160.1275220.88350.190686
170.0717270.49690.310751
18-0.14077-0.97530.832846
19-0.036136-0.25040.59831
202.8e-052e-040.499922
21-0.122135-0.84620.799173
22-0.040806-0.28270.610695
23-0.181812-1.25960.893054
240.0479330.33210.370633
250.0035140.02430.490339
26-0.109176-0.75640.773444
27-0.133884-0.92760.820865
28-0.042482-0.29430.61511
290.0361490.25040.401655
300.0861440.59680.276715
31-0.098709-0.68390.751329
320.1497651.03760.152327
33-0.090922-0.62990.734135
34-0.143708-0.99560.837791
35-0.046766-0.3240.626329
36-0.064326-0.44570.671077
370.0376020.26050.397791
38-0.020206-0.140.555373
39-0.109978-0.76190.77509
400.039520.27380.392706
41-0.019454-0.13480.553325
42-0.05799-0.40180.65518
43-0.057362-0.39740.653589
440.0248710.17230.431959
45-0.07249-0.50220.691096
46-0.006165-0.04270.516946
47NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.30149 & 2.0888 & 0.021027 \tabularnewline
1 & 0.281313 & 1.949 & 0.028577 \tabularnewline
2 & 0.010539 & 0.073 & 0.471049 \tabularnewline
3 & -0.041533 & -0.2878 & 0.612612 \tabularnewline
4 & 0.053975 & 0.374 & 0.355044 \tabularnewline
5 & -0.001854 & -0.0128 & 0.505099 \tabularnewline
6 & -0.141913 & -0.9832 & 0.834782 \tabularnewline
7 & -0.042759 & -0.2962 & 0.615838 \tabularnewline
8 & 0.08861 & 0.6139 & 0.271087 \tabularnewline
9 & -0.267844 & -1.8557 & 0.965177 \tabularnewline
10 & -0.205048 & -1.4206 & 0.919054 \tabularnewline
11 & -0.206282 & -1.4292 & 0.920284 \tabularnewline
12 & -0.067806 & -0.4698 & 0.679678 \tabularnewline
13 & 0.080487 & 0.5576 & 0.289845 \tabularnewline
14 & 0.158085 & 1.0952 & 0.139437 \tabularnewline
15 & -0.248299 & -1.7203 & 0.954087 \tabularnewline
16 & 0.127522 & 0.8835 & 0.190686 \tabularnewline
17 & 0.071727 & 0.4969 & 0.310751 \tabularnewline
18 & -0.14077 & -0.9753 & 0.832846 \tabularnewline
19 & -0.036136 & -0.2504 & 0.59831 \tabularnewline
20 & 2.8e-05 & 2e-04 & 0.499922 \tabularnewline
21 & -0.122135 & -0.8462 & 0.799173 \tabularnewline
22 & -0.040806 & -0.2827 & 0.610695 \tabularnewline
23 & -0.181812 & -1.2596 & 0.893054 \tabularnewline
24 & 0.047933 & 0.3321 & 0.370633 \tabularnewline
25 & 0.003514 & 0.0243 & 0.490339 \tabularnewline
26 & -0.109176 & -0.7564 & 0.773444 \tabularnewline
27 & -0.133884 & -0.9276 & 0.820865 \tabularnewline
28 & -0.042482 & -0.2943 & 0.61511 \tabularnewline
29 & 0.036149 & 0.2504 & 0.401655 \tabularnewline
30 & 0.086144 & 0.5968 & 0.276715 \tabularnewline
31 & -0.098709 & -0.6839 & 0.751329 \tabularnewline
32 & 0.149765 & 1.0376 & 0.152327 \tabularnewline
33 & -0.090922 & -0.6299 & 0.734135 \tabularnewline
34 & -0.143708 & -0.9956 & 0.837791 \tabularnewline
35 & -0.046766 & -0.324 & 0.626329 \tabularnewline
36 & -0.064326 & -0.4457 & 0.671077 \tabularnewline
37 & 0.037602 & 0.2605 & 0.397791 \tabularnewline
38 & -0.020206 & -0.14 & 0.555373 \tabularnewline
39 & -0.109978 & -0.7619 & 0.77509 \tabularnewline
40 & 0.03952 & 0.2738 & 0.392706 \tabularnewline
41 & -0.019454 & -0.1348 & 0.553325 \tabularnewline
42 & -0.05799 & -0.4018 & 0.65518 \tabularnewline
43 & -0.057362 & -0.3974 & 0.653589 \tabularnewline
44 & 0.024871 & 0.1723 & 0.431959 \tabularnewline
45 & -0.07249 & -0.5022 & 0.691096 \tabularnewline
46 & -0.006165 & -0.0427 & 0.516946 \tabularnewline
47 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3030&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]0[/C][C]0.30149[/C][C]2.0888[/C][C]0.021027[/C][/ROW]
[ROW][C]1[/C][C]0.281313[/C][C]1.949[/C][C]0.028577[/C][/ROW]
[ROW][C]2[/C][C]0.010539[/C][C]0.073[/C][C]0.471049[/C][/ROW]
[ROW][C]3[/C][C]-0.041533[/C][C]-0.2878[/C][C]0.612612[/C][/ROW]
[ROW][C]4[/C][C]0.053975[/C][C]0.374[/C][C]0.355044[/C][/ROW]
[ROW][C]5[/C][C]-0.001854[/C][C]-0.0128[/C][C]0.505099[/C][/ROW]
[ROW][C]6[/C][C]-0.141913[/C][C]-0.9832[/C][C]0.834782[/C][/ROW]
[ROW][C]7[/C][C]-0.042759[/C][C]-0.2962[/C][C]0.615838[/C][/ROW]
[ROW][C]8[/C][C]0.08861[/C][C]0.6139[/C][C]0.271087[/C][/ROW]
[ROW][C]9[/C][C]-0.267844[/C][C]-1.8557[/C][C]0.965177[/C][/ROW]
[ROW][C]10[/C][C]-0.205048[/C][C]-1.4206[/C][C]0.919054[/C][/ROW]
[ROW][C]11[/C][C]-0.206282[/C][C]-1.4292[/C][C]0.920284[/C][/ROW]
[ROW][C]12[/C][C]-0.067806[/C][C]-0.4698[/C][C]0.679678[/C][/ROW]
[ROW][C]13[/C][C]0.080487[/C][C]0.5576[/C][C]0.289845[/C][/ROW]
[ROW][C]14[/C][C]0.158085[/C][C]1.0952[/C][C]0.139437[/C][/ROW]
[ROW][C]15[/C][C]-0.248299[/C][C]-1.7203[/C][C]0.954087[/C][/ROW]
[ROW][C]16[/C][C]0.127522[/C][C]0.8835[/C][C]0.190686[/C][/ROW]
[ROW][C]17[/C][C]0.071727[/C][C]0.4969[/C][C]0.310751[/C][/ROW]
[ROW][C]18[/C][C]-0.14077[/C][C]-0.9753[/C][C]0.832846[/C][/ROW]
[ROW][C]19[/C][C]-0.036136[/C][C]-0.2504[/C][C]0.59831[/C][/ROW]
[ROW][C]20[/C][C]2.8e-05[/C][C]2e-04[/C][C]0.499922[/C][/ROW]
[ROW][C]21[/C][C]-0.122135[/C][C]-0.8462[/C][C]0.799173[/C][/ROW]
[ROW][C]22[/C][C]-0.040806[/C][C]-0.2827[/C][C]0.610695[/C][/ROW]
[ROW][C]23[/C][C]-0.181812[/C][C]-1.2596[/C][C]0.893054[/C][/ROW]
[ROW][C]24[/C][C]0.047933[/C][C]0.3321[/C][C]0.370633[/C][/ROW]
[ROW][C]25[/C][C]0.003514[/C][C]0.0243[/C][C]0.490339[/C][/ROW]
[ROW][C]26[/C][C]-0.109176[/C][C]-0.7564[/C][C]0.773444[/C][/ROW]
[ROW][C]27[/C][C]-0.133884[/C][C]-0.9276[/C][C]0.820865[/C][/ROW]
[ROW][C]28[/C][C]-0.042482[/C][C]-0.2943[/C][C]0.61511[/C][/ROW]
[ROW][C]29[/C][C]0.036149[/C][C]0.2504[/C][C]0.401655[/C][/ROW]
[ROW][C]30[/C][C]0.086144[/C][C]0.5968[/C][C]0.276715[/C][/ROW]
[ROW][C]31[/C][C]-0.098709[/C][C]-0.6839[/C][C]0.751329[/C][/ROW]
[ROW][C]32[/C][C]0.149765[/C][C]1.0376[/C][C]0.152327[/C][/ROW]
[ROW][C]33[/C][C]-0.090922[/C][C]-0.6299[/C][C]0.734135[/C][/ROW]
[ROW][C]34[/C][C]-0.143708[/C][C]-0.9956[/C][C]0.837791[/C][/ROW]
[ROW][C]35[/C][C]-0.046766[/C][C]-0.324[/C][C]0.626329[/C][/ROW]
[ROW][C]36[/C][C]-0.064326[/C][C]-0.4457[/C][C]0.671077[/C][/ROW]
[ROW][C]37[/C][C]0.037602[/C][C]0.2605[/C][C]0.397791[/C][/ROW]
[ROW][C]38[/C][C]-0.020206[/C][C]-0.14[/C][C]0.555373[/C][/ROW]
[ROW][C]39[/C][C]-0.109978[/C][C]-0.7619[/C][C]0.77509[/C][/ROW]
[ROW][C]40[/C][C]0.03952[/C][C]0.2738[/C][C]0.392706[/C][/ROW]
[ROW][C]41[/C][C]-0.019454[/C][C]-0.1348[/C][C]0.553325[/C][/ROW]
[ROW][C]42[/C][C]-0.05799[/C][C]-0.4018[/C][C]0.65518[/C][/ROW]
[ROW][C]43[/C][C]-0.057362[/C][C]-0.3974[/C][C]0.653589[/C][/ROW]
[ROW][C]44[/C][C]0.024871[/C][C]0.1723[/C][C]0.431959[/C][/ROW]
[ROW][C]45[/C][C]-0.07249[/C][C]-0.5022[/C][C]0.691096[/C][/ROW]
[ROW][C]46[/C][C]-0.006165[/C][C]-0.0427[/C][C]0.516946[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3030&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3030&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
00.301492.08880.021027
10.2813131.9490.028577
20.0105390.0730.471049
3-0.041533-0.28780.612612
40.0539750.3740.355044
5-0.001854-0.01280.505099
6-0.141913-0.98320.834782
7-0.042759-0.29620.615838
80.088610.61390.271087
9-0.267844-1.85570.965177
10-0.205048-1.42060.919054
11-0.206282-1.42920.920284
12-0.067806-0.46980.679678
130.0804870.55760.289845
140.1580851.09520.139437
15-0.248299-1.72030.954087
160.1275220.88350.190686
170.0717270.49690.310751
18-0.14077-0.97530.832846
19-0.036136-0.25040.59831
202.8e-052e-040.499922
21-0.122135-0.84620.799173
22-0.040806-0.28270.610695
23-0.181812-1.25960.893054
240.0479330.33210.370633
250.0035140.02430.490339
26-0.109176-0.75640.773444
27-0.133884-0.92760.820865
28-0.042482-0.29430.61511
290.0361490.25040.401655
300.0861440.59680.276715
31-0.098709-0.68390.751329
320.1497651.03760.152327
33-0.090922-0.62990.734135
34-0.143708-0.99560.837791
35-0.046766-0.3240.626329
36-0.064326-0.44570.671077
370.0376020.26050.397791
38-0.020206-0.140.555373
39-0.109978-0.76190.77509
400.039520.27380.392706
41-0.019454-0.13480.553325
42-0.05799-0.40180.65518
43-0.057362-0.39740.653589
440.0248710.17230.431959
45-0.07249-0.50220.691096
46-0.006165-0.04270.516946
47NANANA



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')