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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, 07 Dec 2016 15:46:19 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/07/t1481122027oxqv52gd6sx7rc1.htm/, Retrieved Tue, 07 May 2024 20:13:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298162, Retrieved Tue, 07 May 2024 20:13:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact41
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [N1895] [2016-12-07 14:46:19] [85f5800284aab30c091766186b093bb4] [Current]
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Dataseries X:
5550
5530
6070
6120
5840
6360
6300
6400
5490
5630
5580
5780
5670
6030
6760
6050
5910
6510
6360
6460
5710
5910
5680
5690
5360
5380
6000
5950
5960
6440
6190
6550
5780
5800
5720
5730
5530
5650
6750
6370
6500
7050
6570
6710
5570
5610
5430
5910
5510
5790
6420
6020
5870
6210
6430
6920
5710
5800
5690
5880
5560
5860
6510
6460
6360
6530
6840
7110
5860
5960
5770
5810
5580
5750
6440
6260
6250
6660
6820
7090
6030
6190
5980
5830
5620
5690
6500
6200
6250
6970
6950
7240
6050
6190
6050
5990
5730
5920
6350
6190
6080
6710
6780
7120
6010
6020
5890
5960
5690
5620
5980
6320
6340
6670
6790
7120
6120
6160
5840
6260
5650
5730
6250
6000
6160
6910




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298162&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298162&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298162&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.106138-1.12830.130799
2-0.129008-1.37140.086489
3-0.091305-0.97060.166914
4-0.103869-1.10410.135939
5-0.112946-1.20060.116202
6-0.046216-0.49130.31209
70.1124281.19510.11727
80.0921820.97990.164613
90.1150621.22310.111913
10-0.01821-0.19360.423426
110.0144640.15380.43904
12-0.328963-3.49690.000337
13-0.076896-0.81740.207705
140.0759210.80710.210666
150.0397230.42230.336818
16-0.09192-0.97710.165298
170.0419220.44560.328358
180.0654790.69610.243912
19-0.017777-0.1890.425228
200.10021.06510.144541
21-0.073543-0.78180.217992
220.0235790.25070.401269
230.0095420.10140.459692
24-0.126506-1.34480.090696
250.067490.71740.237294
260.0524160.55720.289251
270.14141.50310.067801
280.0508930.5410.294788
29-0.04855-0.51610.303397
30-0.033526-0.35640.361108
31-0.005549-0.0590.476535
32-0.151123-1.60650.055482
330.0202380.21510.415026
340.0368760.3920.3479
350.0903670.96060.1694
36-0.015628-0.16610.434177
370.0015970.0170.493242
38-0.074467-0.79160.215127
39-0.0567-0.60270.273949
40-0.033649-0.35770.360622
410.0369090.39230.347771
420.0790090.83990.201374
43-0.051564-0.54810.292341
440.0114560.12180.451644
45-0.001382-0.01470.494152
46-0.065531-0.69660.24374
47-0.013606-0.14460.442629
480.0855910.90980.182421

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.106138 & -1.1283 & 0.130799 \tabularnewline
2 & -0.129008 & -1.3714 & 0.086489 \tabularnewline
3 & -0.091305 & -0.9706 & 0.166914 \tabularnewline
4 & -0.103869 & -1.1041 & 0.135939 \tabularnewline
5 & -0.112946 & -1.2006 & 0.116202 \tabularnewline
6 & -0.046216 & -0.4913 & 0.31209 \tabularnewline
7 & 0.112428 & 1.1951 & 0.11727 \tabularnewline
8 & 0.092182 & 0.9799 & 0.164613 \tabularnewline
9 & 0.115062 & 1.2231 & 0.111913 \tabularnewline
10 & -0.01821 & -0.1936 & 0.423426 \tabularnewline
11 & 0.014464 & 0.1538 & 0.43904 \tabularnewline
12 & -0.328963 & -3.4969 & 0.000337 \tabularnewline
13 & -0.076896 & -0.8174 & 0.207705 \tabularnewline
14 & 0.075921 & 0.8071 & 0.210666 \tabularnewline
15 & 0.039723 & 0.4223 & 0.336818 \tabularnewline
16 & -0.09192 & -0.9771 & 0.165298 \tabularnewline
17 & 0.041922 & 0.4456 & 0.328358 \tabularnewline
18 & 0.065479 & 0.6961 & 0.243912 \tabularnewline
19 & -0.017777 & -0.189 & 0.425228 \tabularnewline
20 & 0.1002 & 1.0651 & 0.144541 \tabularnewline
21 & -0.073543 & -0.7818 & 0.217992 \tabularnewline
22 & 0.023579 & 0.2507 & 0.401269 \tabularnewline
23 & 0.009542 & 0.1014 & 0.459692 \tabularnewline
24 & -0.126506 & -1.3448 & 0.090696 \tabularnewline
25 & 0.06749 & 0.7174 & 0.237294 \tabularnewline
26 & 0.052416 & 0.5572 & 0.289251 \tabularnewline
27 & 0.1414 & 1.5031 & 0.067801 \tabularnewline
28 & 0.050893 & 0.541 & 0.294788 \tabularnewline
29 & -0.04855 & -0.5161 & 0.303397 \tabularnewline
30 & -0.033526 & -0.3564 & 0.361108 \tabularnewline
31 & -0.005549 & -0.059 & 0.476535 \tabularnewline
32 & -0.151123 & -1.6065 & 0.055482 \tabularnewline
33 & 0.020238 & 0.2151 & 0.415026 \tabularnewline
34 & 0.036876 & 0.392 & 0.3479 \tabularnewline
35 & 0.090367 & 0.9606 & 0.1694 \tabularnewline
36 & -0.015628 & -0.1661 & 0.434177 \tabularnewline
37 & 0.001597 & 0.017 & 0.493242 \tabularnewline
38 & -0.074467 & -0.7916 & 0.215127 \tabularnewline
39 & -0.0567 & -0.6027 & 0.273949 \tabularnewline
40 & -0.033649 & -0.3577 & 0.360622 \tabularnewline
41 & 0.036909 & 0.3923 & 0.347771 \tabularnewline
42 & 0.079009 & 0.8399 & 0.201374 \tabularnewline
43 & -0.051564 & -0.5481 & 0.292341 \tabularnewline
44 & 0.011456 & 0.1218 & 0.451644 \tabularnewline
45 & -0.001382 & -0.0147 & 0.494152 \tabularnewline
46 & -0.065531 & -0.6966 & 0.24374 \tabularnewline
47 & -0.013606 & -0.1446 & 0.442629 \tabularnewline
48 & 0.085591 & 0.9098 & 0.182421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298162&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]-0.106138[/C][C]-1.1283[/C][C]0.130799[/C][/ROW]
[ROW][C]2[/C][C]-0.129008[/C][C]-1.3714[/C][C]0.086489[/C][/ROW]
[ROW][C]3[/C][C]-0.091305[/C][C]-0.9706[/C][C]0.166914[/C][/ROW]
[ROW][C]4[/C][C]-0.103869[/C][C]-1.1041[/C][C]0.135939[/C][/ROW]
[ROW][C]5[/C][C]-0.112946[/C][C]-1.2006[/C][C]0.116202[/C][/ROW]
[ROW][C]6[/C][C]-0.046216[/C][C]-0.4913[/C][C]0.31209[/C][/ROW]
[ROW][C]7[/C][C]0.112428[/C][C]1.1951[/C][C]0.11727[/C][/ROW]
[ROW][C]8[/C][C]0.092182[/C][C]0.9799[/C][C]0.164613[/C][/ROW]
[ROW][C]9[/C][C]0.115062[/C][C]1.2231[/C][C]0.111913[/C][/ROW]
[ROW][C]10[/C][C]-0.01821[/C][C]-0.1936[/C][C]0.423426[/C][/ROW]
[ROW][C]11[/C][C]0.014464[/C][C]0.1538[/C][C]0.43904[/C][/ROW]
[ROW][C]12[/C][C]-0.328963[/C][C]-3.4969[/C][C]0.000337[/C][/ROW]
[ROW][C]13[/C][C]-0.076896[/C][C]-0.8174[/C][C]0.207705[/C][/ROW]
[ROW][C]14[/C][C]0.075921[/C][C]0.8071[/C][C]0.210666[/C][/ROW]
[ROW][C]15[/C][C]0.039723[/C][C]0.4223[/C][C]0.336818[/C][/ROW]
[ROW][C]16[/C][C]-0.09192[/C][C]-0.9771[/C][C]0.165298[/C][/ROW]
[ROW][C]17[/C][C]0.041922[/C][C]0.4456[/C][C]0.328358[/C][/ROW]
[ROW][C]18[/C][C]0.065479[/C][C]0.6961[/C][C]0.243912[/C][/ROW]
[ROW][C]19[/C][C]-0.017777[/C][C]-0.189[/C][C]0.425228[/C][/ROW]
[ROW][C]20[/C][C]0.1002[/C][C]1.0651[/C][C]0.144541[/C][/ROW]
[ROW][C]21[/C][C]-0.073543[/C][C]-0.7818[/C][C]0.217992[/C][/ROW]
[ROW][C]22[/C][C]0.023579[/C][C]0.2507[/C][C]0.401269[/C][/ROW]
[ROW][C]23[/C][C]0.009542[/C][C]0.1014[/C][C]0.459692[/C][/ROW]
[ROW][C]24[/C][C]-0.126506[/C][C]-1.3448[/C][C]0.090696[/C][/ROW]
[ROW][C]25[/C][C]0.06749[/C][C]0.7174[/C][C]0.237294[/C][/ROW]
[ROW][C]26[/C][C]0.052416[/C][C]0.5572[/C][C]0.289251[/C][/ROW]
[ROW][C]27[/C][C]0.1414[/C][C]1.5031[/C][C]0.067801[/C][/ROW]
[ROW][C]28[/C][C]0.050893[/C][C]0.541[/C][C]0.294788[/C][/ROW]
[ROW][C]29[/C][C]-0.04855[/C][C]-0.5161[/C][C]0.303397[/C][/ROW]
[ROW][C]30[/C][C]-0.033526[/C][C]-0.3564[/C][C]0.361108[/C][/ROW]
[ROW][C]31[/C][C]-0.005549[/C][C]-0.059[/C][C]0.476535[/C][/ROW]
[ROW][C]32[/C][C]-0.151123[/C][C]-1.6065[/C][C]0.055482[/C][/ROW]
[ROW][C]33[/C][C]0.020238[/C][C]0.2151[/C][C]0.415026[/C][/ROW]
[ROW][C]34[/C][C]0.036876[/C][C]0.392[/C][C]0.3479[/C][/ROW]
[ROW][C]35[/C][C]0.090367[/C][C]0.9606[/C][C]0.1694[/C][/ROW]
[ROW][C]36[/C][C]-0.015628[/C][C]-0.1661[/C][C]0.434177[/C][/ROW]
[ROW][C]37[/C][C]0.001597[/C][C]0.017[/C][C]0.493242[/C][/ROW]
[ROW][C]38[/C][C]-0.074467[/C][C]-0.7916[/C][C]0.215127[/C][/ROW]
[ROW][C]39[/C][C]-0.0567[/C][C]-0.6027[/C][C]0.273949[/C][/ROW]
[ROW][C]40[/C][C]-0.033649[/C][C]-0.3577[/C][C]0.360622[/C][/ROW]
[ROW][C]41[/C][C]0.036909[/C][C]0.3923[/C][C]0.347771[/C][/ROW]
[ROW][C]42[/C][C]0.079009[/C][C]0.8399[/C][C]0.201374[/C][/ROW]
[ROW][C]43[/C][C]-0.051564[/C][C]-0.5481[/C][C]0.292341[/C][/ROW]
[ROW][C]44[/C][C]0.011456[/C][C]0.1218[/C][C]0.451644[/C][/ROW]
[ROW][C]45[/C][C]-0.001382[/C][C]-0.0147[/C][C]0.494152[/C][/ROW]
[ROW][C]46[/C][C]-0.065531[/C][C]-0.6966[/C][C]0.24374[/C][/ROW]
[ROW][C]47[/C][C]-0.013606[/C][C]-0.1446[/C][C]0.442629[/C][/ROW]
[ROW][C]48[/C][C]0.085591[/C][C]0.9098[/C][C]0.182421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298162&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298162&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
1-0.106138-1.12830.130799
2-0.129008-1.37140.086489
3-0.091305-0.97060.166914
4-0.103869-1.10410.135939
5-0.112946-1.20060.116202
6-0.046216-0.49130.31209
70.1124281.19510.11727
80.0921820.97990.164613
90.1150621.22310.111913
10-0.01821-0.19360.423426
110.0144640.15380.43904
12-0.328963-3.49690.000337
13-0.076896-0.81740.207705
140.0759210.80710.210666
150.0397230.42230.336818
16-0.09192-0.97710.165298
170.0419220.44560.328358
180.0654790.69610.243912
19-0.017777-0.1890.425228
200.10021.06510.144541
21-0.073543-0.78180.217992
220.0235790.25070.401269
230.0095420.10140.459692
24-0.126506-1.34480.090696
250.067490.71740.237294
260.0524160.55720.289251
270.14141.50310.067801
280.0508930.5410.294788
29-0.04855-0.51610.303397
30-0.033526-0.35640.361108
31-0.005549-0.0590.476535
32-0.151123-1.60650.055482
330.0202380.21510.415026
340.0368760.3920.3479
350.0903670.96060.1694
36-0.015628-0.16610.434177
370.0015970.0170.493242
38-0.074467-0.79160.215127
39-0.0567-0.60270.273949
40-0.033649-0.35770.360622
410.0369090.39230.347771
420.0790090.83990.201374
43-0.051564-0.54810.292341
440.0114560.12180.451644
45-0.001382-0.01470.494152
46-0.065531-0.69660.24374
47-0.013606-0.14460.442629
480.0855910.90980.182421







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.106138-1.12830.130799
2-0.141871-1.50810.067159
3-0.125922-1.33860.091698
4-0.157532-1.67460.048391
5-0.195577-2.0790.01994
6-0.169275-1.79940.037311
7-0.017704-0.18820.425531
80.0142770.15180.439821
90.1017821.0820.140787
100.0246250.26180.396987
110.0878280.93360.176244
12-0.27745-2.94930.001936
13-0.140658-1.49520.068823
14-0.048803-0.51880.302465
15-0.067182-0.71420.238302
16-0.263331-2.79920.003013
17-0.204028-2.16890.016095
18-0.184453-1.96080.026184
19-0.142324-1.51290.066545
200.0532380.56590.286282
21-0.034567-0.36750.356984
220.0156260.16610.434185
230.0659690.70130.242291
24-0.218923-2.32720.010868
25-0.063429-0.67430.250761
26-0.028833-0.30650.379894
270.1258281.33760.091861
28-0.018476-0.19640.422323
29-0.134942-1.43440.077103
30-0.066417-0.7060.240814
310.0369880.39320.347462
32-0.048981-0.52070.301806
330.0375450.39910.345282
34-0.029595-0.31460.376823
350.1054691.12110.132301
36-0.11448-1.21690.113081
37-0.01591-0.16910.433
38-0.029739-0.31610.376242
390.1327221.41090.080518
40-0.049877-0.53020.298509
410.0062040.0660.473767
420.0500130.53160.298006
430.0732910.77910.218776
440.0159980.17010.432635
45-0.015577-0.16560.434387
46-0.10513-1.11760.133065
470.0211840.22520.41112
48-0.079629-0.84650.199541

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.106138 & -1.1283 & 0.130799 \tabularnewline
2 & -0.141871 & -1.5081 & 0.067159 \tabularnewline
3 & -0.125922 & -1.3386 & 0.091698 \tabularnewline
4 & -0.157532 & -1.6746 & 0.048391 \tabularnewline
5 & -0.195577 & -2.079 & 0.01994 \tabularnewline
6 & -0.169275 & -1.7994 & 0.037311 \tabularnewline
7 & -0.017704 & -0.1882 & 0.425531 \tabularnewline
8 & 0.014277 & 0.1518 & 0.439821 \tabularnewline
9 & 0.101782 & 1.082 & 0.140787 \tabularnewline
10 & 0.024625 & 0.2618 & 0.396987 \tabularnewline
11 & 0.087828 & 0.9336 & 0.176244 \tabularnewline
12 & -0.27745 & -2.9493 & 0.001936 \tabularnewline
13 & -0.140658 & -1.4952 & 0.068823 \tabularnewline
14 & -0.048803 & -0.5188 & 0.302465 \tabularnewline
15 & -0.067182 & -0.7142 & 0.238302 \tabularnewline
16 & -0.263331 & -2.7992 & 0.003013 \tabularnewline
17 & -0.204028 & -2.1689 & 0.016095 \tabularnewline
18 & -0.184453 & -1.9608 & 0.026184 \tabularnewline
19 & -0.142324 & -1.5129 & 0.066545 \tabularnewline
20 & 0.053238 & 0.5659 & 0.286282 \tabularnewline
21 & -0.034567 & -0.3675 & 0.356984 \tabularnewline
22 & 0.015626 & 0.1661 & 0.434185 \tabularnewline
23 & 0.065969 & 0.7013 & 0.242291 \tabularnewline
24 & -0.218923 & -2.3272 & 0.010868 \tabularnewline
25 & -0.063429 & -0.6743 & 0.250761 \tabularnewline
26 & -0.028833 & -0.3065 & 0.379894 \tabularnewline
27 & 0.125828 & 1.3376 & 0.091861 \tabularnewline
28 & -0.018476 & -0.1964 & 0.422323 \tabularnewline
29 & -0.134942 & -1.4344 & 0.077103 \tabularnewline
30 & -0.066417 & -0.706 & 0.240814 \tabularnewline
31 & 0.036988 & 0.3932 & 0.347462 \tabularnewline
32 & -0.048981 & -0.5207 & 0.301806 \tabularnewline
33 & 0.037545 & 0.3991 & 0.345282 \tabularnewline
34 & -0.029595 & -0.3146 & 0.376823 \tabularnewline
35 & 0.105469 & 1.1211 & 0.132301 \tabularnewline
36 & -0.11448 & -1.2169 & 0.113081 \tabularnewline
37 & -0.01591 & -0.1691 & 0.433 \tabularnewline
38 & -0.029739 & -0.3161 & 0.376242 \tabularnewline
39 & 0.132722 & 1.4109 & 0.080518 \tabularnewline
40 & -0.049877 & -0.5302 & 0.298509 \tabularnewline
41 & 0.006204 & 0.066 & 0.473767 \tabularnewline
42 & 0.050013 & 0.5316 & 0.298006 \tabularnewline
43 & 0.073291 & 0.7791 & 0.218776 \tabularnewline
44 & 0.015998 & 0.1701 & 0.432635 \tabularnewline
45 & -0.015577 & -0.1656 & 0.434387 \tabularnewline
46 & -0.10513 & -1.1176 & 0.133065 \tabularnewline
47 & 0.021184 & 0.2252 & 0.41112 \tabularnewline
48 & -0.079629 & -0.8465 & 0.199541 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298162&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]-0.106138[/C][C]-1.1283[/C][C]0.130799[/C][/ROW]
[ROW][C]2[/C][C]-0.141871[/C][C]-1.5081[/C][C]0.067159[/C][/ROW]
[ROW][C]3[/C][C]-0.125922[/C][C]-1.3386[/C][C]0.091698[/C][/ROW]
[ROW][C]4[/C][C]-0.157532[/C][C]-1.6746[/C][C]0.048391[/C][/ROW]
[ROW][C]5[/C][C]-0.195577[/C][C]-2.079[/C][C]0.01994[/C][/ROW]
[ROW][C]6[/C][C]-0.169275[/C][C]-1.7994[/C][C]0.037311[/C][/ROW]
[ROW][C]7[/C][C]-0.017704[/C][C]-0.1882[/C][C]0.425531[/C][/ROW]
[ROW][C]8[/C][C]0.014277[/C][C]0.1518[/C][C]0.439821[/C][/ROW]
[ROW][C]9[/C][C]0.101782[/C][C]1.082[/C][C]0.140787[/C][/ROW]
[ROW][C]10[/C][C]0.024625[/C][C]0.2618[/C][C]0.396987[/C][/ROW]
[ROW][C]11[/C][C]0.087828[/C][C]0.9336[/C][C]0.176244[/C][/ROW]
[ROW][C]12[/C][C]-0.27745[/C][C]-2.9493[/C][C]0.001936[/C][/ROW]
[ROW][C]13[/C][C]-0.140658[/C][C]-1.4952[/C][C]0.068823[/C][/ROW]
[ROW][C]14[/C][C]-0.048803[/C][C]-0.5188[/C][C]0.302465[/C][/ROW]
[ROW][C]15[/C][C]-0.067182[/C][C]-0.7142[/C][C]0.238302[/C][/ROW]
[ROW][C]16[/C][C]-0.263331[/C][C]-2.7992[/C][C]0.003013[/C][/ROW]
[ROW][C]17[/C][C]-0.204028[/C][C]-2.1689[/C][C]0.016095[/C][/ROW]
[ROW][C]18[/C][C]-0.184453[/C][C]-1.9608[/C][C]0.026184[/C][/ROW]
[ROW][C]19[/C][C]-0.142324[/C][C]-1.5129[/C][C]0.066545[/C][/ROW]
[ROW][C]20[/C][C]0.053238[/C][C]0.5659[/C][C]0.286282[/C][/ROW]
[ROW][C]21[/C][C]-0.034567[/C][C]-0.3675[/C][C]0.356984[/C][/ROW]
[ROW][C]22[/C][C]0.015626[/C][C]0.1661[/C][C]0.434185[/C][/ROW]
[ROW][C]23[/C][C]0.065969[/C][C]0.7013[/C][C]0.242291[/C][/ROW]
[ROW][C]24[/C][C]-0.218923[/C][C]-2.3272[/C][C]0.010868[/C][/ROW]
[ROW][C]25[/C][C]-0.063429[/C][C]-0.6743[/C][C]0.250761[/C][/ROW]
[ROW][C]26[/C][C]-0.028833[/C][C]-0.3065[/C][C]0.379894[/C][/ROW]
[ROW][C]27[/C][C]0.125828[/C][C]1.3376[/C][C]0.091861[/C][/ROW]
[ROW][C]28[/C][C]-0.018476[/C][C]-0.1964[/C][C]0.422323[/C][/ROW]
[ROW][C]29[/C][C]-0.134942[/C][C]-1.4344[/C][C]0.077103[/C][/ROW]
[ROW][C]30[/C][C]-0.066417[/C][C]-0.706[/C][C]0.240814[/C][/ROW]
[ROW][C]31[/C][C]0.036988[/C][C]0.3932[/C][C]0.347462[/C][/ROW]
[ROW][C]32[/C][C]-0.048981[/C][C]-0.5207[/C][C]0.301806[/C][/ROW]
[ROW][C]33[/C][C]0.037545[/C][C]0.3991[/C][C]0.345282[/C][/ROW]
[ROW][C]34[/C][C]-0.029595[/C][C]-0.3146[/C][C]0.376823[/C][/ROW]
[ROW][C]35[/C][C]0.105469[/C][C]1.1211[/C][C]0.132301[/C][/ROW]
[ROW][C]36[/C][C]-0.11448[/C][C]-1.2169[/C][C]0.113081[/C][/ROW]
[ROW][C]37[/C][C]-0.01591[/C][C]-0.1691[/C][C]0.433[/C][/ROW]
[ROW][C]38[/C][C]-0.029739[/C][C]-0.3161[/C][C]0.376242[/C][/ROW]
[ROW][C]39[/C][C]0.132722[/C][C]1.4109[/C][C]0.080518[/C][/ROW]
[ROW][C]40[/C][C]-0.049877[/C][C]-0.5302[/C][C]0.298509[/C][/ROW]
[ROW][C]41[/C][C]0.006204[/C][C]0.066[/C][C]0.473767[/C][/ROW]
[ROW][C]42[/C][C]0.050013[/C][C]0.5316[/C][C]0.298006[/C][/ROW]
[ROW][C]43[/C][C]0.073291[/C][C]0.7791[/C][C]0.218776[/C][/ROW]
[ROW][C]44[/C][C]0.015998[/C][C]0.1701[/C][C]0.432635[/C][/ROW]
[ROW][C]45[/C][C]-0.015577[/C][C]-0.1656[/C][C]0.434387[/C][/ROW]
[ROW][C]46[/C][C]-0.10513[/C][C]-1.1176[/C][C]0.133065[/C][/ROW]
[ROW][C]47[/C][C]0.021184[/C][C]0.2252[/C][C]0.41112[/C][/ROW]
[ROW][C]48[/C][C]-0.079629[/C][C]-0.8465[/C][C]0.199541[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298162&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298162&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
1-0.106138-1.12830.130799
2-0.141871-1.50810.067159
3-0.125922-1.33860.091698
4-0.157532-1.67460.048391
5-0.195577-2.0790.01994
6-0.169275-1.79940.037311
7-0.017704-0.18820.425531
80.0142770.15180.439821
90.1017821.0820.140787
100.0246250.26180.396987
110.0878280.93360.176244
12-0.27745-2.94930.001936
13-0.140658-1.49520.068823
14-0.048803-0.51880.302465
15-0.067182-0.71420.238302
16-0.263331-2.79920.003013
17-0.204028-2.16890.016095
18-0.184453-1.96080.026184
19-0.142324-1.51290.066545
200.0532380.56590.286282
21-0.034567-0.36750.356984
220.0156260.16610.434185
230.0659690.70130.242291
24-0.218923-2.32720.010868
25-0.063429-0.67430.250761
26-0.028833-0.30650.379894
270.1258281.33760.091861
28-0.018476-0.19640.422323
29-0.134942-1.43440.077103
30-0.066417-0.7060.240814
310.0369880.39320.347462
32-0.048981-0.52070.301806
330.0375450.39910.345282
34-0.029595-0.31460.376823
350.1054691.12110.132301
36-0.11448-1.21690.113081
37-0.01591-0.16910.433
38-0.029739-0.31610.376242
390.1327221.41090.080518
40-0.049877-0.53020.298509
410.0062040.0660.473767
420.0500130.53160.298006
430.0732910.77910.218776
440.0159980.17010.432635
45-0.015577-0.16560.434387
46-0.10513-1.11760.133065
470.0211840.22520.41112
48-0.079629-0.84650.199541



Parameters (Session):
par1 = 48 ; par2 = -2.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = -2.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '1'
par3 <- '1'
par2 <- '-2.0'
par1 <- 'Default'
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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')