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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 27 Jul 2017 00:34:33 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jul/27/t15011085421eq9xx2h0ofj78s.htm/, Retrieved Thu, 16 May 2024 01:30:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306760, Retrieved Thu, 16 May 2024 01:30:45 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Tijdreeks A stap 21] [2017-07-26 22:34:33] [5e513ceaaef205c0c6f269c0b513af8d] [Current]
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Dataseries X:
6195800
6172725
6149325
6100900
6579950
6554600
6195800
5957250
5980325
5980325
6006000
6052150
6123975
6123975
6077825
5957250
6579950
6674850
6531525
6195800
6339450
6123975
6221150
6267625
6316050
6195800
6221150
6052150
6579950
6746675
6603350
6339450
6626425
6316050
6603350
6579950
6651775
6387875
6674850
6651775
7082400
6985225
6603350
6410950
6674850
6316050
6579950
6626425
6723600
6508450
6626425
6698250
6962150
6746675
6459700
6149325
6436625
5646875
6029075
6244225
6459700
6149325
6149325
6149325
6316050
6077825
5765175
5503550
5693350
4952350
5406375
5670275
5718700
5454800
5477875
5406375
5646875
5477875
5144750
4903925
5311150
4426825
5001100
5262725
5262725
4952350
4665375
4642300
4903925
4665375
4211675
3899025
4234750
3445325
4162925
4544800
4665375
4401475
4068025
4306575
4401475
4329650
3611725
3278600
3516825
2799225
3540225
3804125
4019275
3660475
3324750
3516825
3611725
3421925
2704325
2391675
2678650
1889225
2750475
3278600




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306760&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306760&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306760&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 time2 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.216906-2.36620.009794
2-0.052827-0.57630.282758
3-0.144728-1.57880.058519
40.0670330.73120.233035
5-0.127179-1.38740.083963
60.050570.55160.291112
7-0.084742-0.92440.178566
80.0849790.9270.177899
9-0.162055-1.76780.039828
10-0.0398-0.43420.332476
11-0.178014-1.94190.027256
120.8242888.99190
13-0.222699-2.42940.00831
14-0.040343-0.44010.330336
15-0.126437-1.37930.085199
160.0712580.77730.219252
17-0.148908-1.62440.053469
180.0786670.85820.196265
19-0.087466-0.95410.170974
200.0933111.01790.155396
21-0.122622-1.33760.091781
22-0.020635-0.22510.411143
23-0.146841-1.60180.055921
240.6759217.37340
25-0.227425-2.48090.007251
26-0.032956-0.35950.359925
27-0.105104-1.14660.126934
280.0665240.72570.234725
29-0.166075-1.81170.03628
300.104621.14130.128024
31-0.071965-0.7850.216994
320.0869940.9490.172274
33-0.110953-1.21040.114271
34-0.009771-0.10660.457646
35-0.106316-1.15980.124233
360.5385935.87540
37-0.216558-2.36240.009891
38-0.033417-0.36450.358053
39-0.080526-0.87840.19074
400.0186280.20320.419661
41-0.174393-1.90240.029768
420.1107921.20860.114607
43-0.049793-0.54320.294011
440.0949651.03590.151164
45-0.089998-0.98180.164104
46-0.015308-0.1670.433829
47-0.057284-0.62490.266618
480.4131574.5078e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.216906 & -2.3662 & 0.009794 \tabularnewline
2 & -0.052827 & -0.5763 & 0.282758 \tabularnewline
3 & -0.144728 & -1.5788 & 0.058519 \tabularnewline
4 & 0.067033 & 0.7312 & 0.233035 \tabularnewline
5 & -0.127179 & -1.3874 & 0.083963 \tabularnewline
6 & 0.05057 & 0.5516 & 0.291112 \tabularnewline
7 & -0.084742 & -0.9244 & 0.178566 \tabularnewline
8 & 0.084979 & 0.927 & 0.177899 \tabularnewline
9 & -0.162055 & -1.7678 & 0.039828 \tabularnewline
10 & -0.0398 & -0.4342 & 0.332476 \tabularnewline
11 & -0.178014 & -1.9419 & 0.027256 \tabularnewline
12 & 0.824288 & 8.9919 & 0 \tabularnewline
13 & -0.222699 & -2.4294 & 0.00831 \tabularnewline
14 & -0.040343 & -0.4401 & 0.330336 \tabularnewline
15 & -0.126437 & -1.3793 & 0.085199 \tabularnewline
16 & 0.071258 & 0.7773 & 0.219252 \tabularnewline
17 & -0.148908 & -1.6244 & 0.053469 \tabularnewline
18 & 0.078667 & 0.8582 & 0.196265 \tabularnewline
19 & -0.087466 & -0.9541 & 0.170974 \tabularnewline
20 & 0.093311 & 1.0179 & 0.155396 \tabularnewline
21 & -0.122622 & -1.3376 & 0.091781 \tabularnewline
22 & -0.020635 & -0.2251 & 0.411143 \tabularnewline
23 & -0.146841 & -1.6018 & 0.055921 \tabularnewline
24 & 0.675921 & 7.3734 & 0 \tabularnewline
25 & -0.227425 & -2.4809 & 0.007251 \tabularnewline
26 & -0.032956 & -0.3595 & 0.359925 \tabularnewline
27 & -0.105104 & -1.1466 & 0.126934 \tabularnewline
28 & 0.066524 & 0.7257 & 0.234725 \tabularnewline
29 & -0.166075 & -1.8117 & 0.03628 \tabularnewline
30 & 0.10462 & 1.1413 & 0.128024 \tabularnewline
31 & -0.071965 & -0.785 & 0.216994 \tabularnewline
32 & 0.086994 & 0.949 & 0.172274 \tabularnewline
33 & -0.110953 & -1.2104 & 0.114271 \tabularnewline
34 & -0.009771 & -0.1066 & 0.457646 \tabularnewline
35 & -0.106316 & -1.1598 & 0.124233 \tabularnewline
36 & 0.538593 & 5.8754 & 0 \tabularnewline
37 & -0.216558 & -2.3624 & 0.009891 \tabularnewline
38 & -0.033417 & -0.3645 & 0.358053 \tabularnewline
39 & -0.080526 & -0.8784 & 0.19074 \tabularnewline
40 & 0.018628 & 0.2032 & 0.419661 \tabularnewline
41 & -0.174393 & -1.9024 & 0.029768 \tabularnewline
42 & 0.110792 & 1.2086 & 0.114607 \tabularnewline
43 & -0.049793 & -0.5432 & 0.294011 \tabularnewline
44 & 0.094965 & 1.0359 & 0.151164 \tabularnewline
45 & -0.089998 & -0.9818 & 0.164104 \tabularnewline
46 & -0.015308 & -0.167 & 0.433829 \tabularnewline
47 & -0.057284 & -0.6249 & 0.266618 \tabularnewline
48 & 0.413157 & 4.507 & 8e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306760&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]-0.216906[/C][C]-2.3662[/C][C]0.009794[/C][/ROW]
[ROW][C]2[/C][C]-0.052827[/C][C]-0.5763[/C][C]0.282758[/C][/ROW]
[ROW][C]3[/C][C]-0.144728[/C][C]-1.5788[/C][C]0.058519[/C][/ROW]
[ROW][C]4[/C][C]0.067033[/C][C]0.7312[/C][C]0.233035[/C][/ROW]
[ROW][C]5[/C][C]-0.127179[/C][C]-1.3874[/C][C]0.083963[/C][/ROW]
[ROW][C]6[/C][C]0.05057[/C][C]0.5516[/C][C]0.291112[/C][/ROW]
[ROW][C]7[/C][C]-0.084742[/C][C]-0.9244[/C][C]0.178566[/C][/ROW]
[ROW][C]8[/C][C]0.084979[/C][C]0.927[/C][C]0.177899[/C][/ROW]
[ROW][C]9[/C][C]-0.162055[/C][C]-1.7678[/C][C]0.039828[/C][/ROW]
[ROW][C]10[/C][C]-0.0398[/C][C]-0.4342[/C][C]0.332476[/C][/ROW]
[ROW][C]11[/C][C]-0.178014[/C][C]-1.9419[/C][C]0.027256[/C][/ROW]
[ROW][C]12[/C][C]0.824288[/C][C]8.9919[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.222699[/C][C]-2.4294[/C][C]0.00831[/C][/ROW]
[ROW][C]14[/C][C]-0.040343[/C][C]-0.4401[/C][C]0.330336[/C][/ROW]
[ROW][C]15[/C][C]-0.126437[/C][C]-1.3793[/C][C]0.085199[/C][/ROW]
[ROW][C]16[/C][C]0.071258[/C][C]0.7773[/C][C]0.219252[/C][/ROW]
[ROW][C]17[/C][C]-0.148908[/C][C]-1.6244[/C][C]0.053469[/C][/ROW]
[ROW][C]18[/C][C]0.078667[/C][C]0.8582[/C][C]0.196265[/C][/ROW]
[ROW][C]19[/C][C]-0.087466[/C][C]-0.9541[/C][C]0.170974[/C][/ROW]
[ROW][C]20[/C][C]0.093311[/C][C]1.0179[/C][C]0.155396[/C][/ROW]
[ROW][C]21[/C][C]-0.122622[/C][C]-1.3376[/C][C]0.091781[/C][/ROW]
[ROW][C]22[/C][C]-0.020635[/C][C]-0.2251[/C][C]0.411143[/C][/ROW]
[ROW][C]23[/C][C]-0.146841[/C][C]-1.6018[/C][C]0.055921[/C][/ROW]
[ROW][C]24[/C][C]0.675921[/C][C]7.3734[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.227425[/C][C]-2.4809[/C][C]0.007251[/C][/ROW]
[ROW][C]26[/C][C]-0.032956[/C][C]-0.3595[/C][C]0.359925[/C][/ROW]
[ROW][C]27[/C][C]-0.105104[/C][C]-1.1466[/C][C]0.126934[/C][/ROW]
[ROW][C]28[/C][C]0.066524[/C][C]0.7257[/C][C]0.234725[/C][/ROW]
[ROW][C]29[/C][C]-0.166075[/C][C]-1.8117[/C][C]0.03628[/C][/ROW]
[ROW][C]30[/C][C]0.10462[/C][C]1.1413[/C][C]0.128024[/C][/ROW]
[ROW][C]31[/C][C]-0.071965[/C][C]-0.785[/C][C]0.216994[/C][/ROW]
[ROW][C]32[/C][C]0.086994[/C][C]0.949[/C][C]0.172274[/C][/ROW]
[ROW][C]33[/C][C]-0.110953[/C][C]-1.2104[/C][C]0.114271[/C][/ROW]
[ROW][C]34[/C][C]-0.009771[/C][C]-0.1066[/C][C]0.457646[/C][/ROW]
[ROW][C]35[/C][C]-0.106316[/C][C]-1.1598[/C][C]0.124233[/C][/ROW]
[ROW][C]36[/C][C]0.538593[/C][C]5.8754[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.216558[/C][C]-2.3624[/C][C]0.009891[/C][/ROW]
[ROW][C]38[/C][C]-0.033417[/C][C]-0.3645[/C][C]0.358053[/C][/ROW]
[ROW][C]39[/C][C]-0.080526[/C][C]-0.8784[/C][C]0.19074[/C][/ROW]
[ROW][C]40[/C][C]0.018628[/C][C]0.2032[/C][C]0.419661[/C][/ROW]
[ROW][C]41[/C][C]-0.174393[/C][C]-1.9024[/C][C]0.029768[/C][/ROW]
[ROW][C]42[/C][C]0.110792[/C][C]1.2086[/C][C]0.114607[/C][/ROW]
[ROW][C]43[/C][C]-0.049793[/C][C]-0.5432[/C][C]0.294011[/C][/ROW]
[ROW][C]44[/C][C]0.094965[/C][C]1.0359[/C][C]0.151164[/C][/ROW]
[ROW][C]45[/C][C]-0.089998[/C][C]-0.9818[/C][C]0.164104[/C][/ROW]
[ROW][C]46[/C][C]-0.015308[/C][C]-0.167[/C][C]0.433829[/C][/ROW]
[ROW][C]47[/C][C]-0.057284[/C][C]-0.6249[/C][C]0.266618[/C][/ROW]
[ROW][C]48[/C][C]0.413157[/C][C]4.507[/C][C]8e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306760&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306760&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
1-0.216906-2.36620.009794
2-0.052827-0.57630.282758
3-0.144728-1.57880.058519
40.0670330.73120.233035
5-0.127179-1.38740.083963
60.050570.55160.291112
7-0.084742-0.92440.178566
80.0849790.9270.177899
9-0.162055-1.76780.039828
10-0.0398-0.43420.332476
11-0.178014-1.94190.027256
120.8242888.99190
13-0.222699-2.42940.00831
14-0.040343-0.44010.330336
15-0.126437-1.37930.085199
160.0712580.77730.219252
17-0.148908-1.62440.053469
180.0786670.85820.196265
19-0.087466-0.95410.170974
200.0933111.01790.155396
21-0.122622-1.33760.091781
22-0.020635-0.22510.411143
23-0.146841-1.60180.055921
240.6759217.37340
25-0.227425-2.48090.007251
26-0.032956-0.35950.359925
27-0.105104-1.14660.126934
280.0665240.72570.234725
29-0.166075-1.81170.03628
300.104621.14130.128024
31-0.071965-0.7850.216994
320.0869940.9490.172274
33-0.110953-1.21040.114271
34-0.009771-0.10660.457646
35-0.106316-1.15980.124233
360.5385935.87540
37-0.216558-2.36240.009891
38-0.033417-0.36450.358053
39-0.080526-0.87840.19074
400.0186280.20320.419661
41-0.174393-1.90240.029768
420.1107921.20860.114607
43-0.049793-0.54320.294011
440.0949651.03590.151164
45-0.089998-0.98180.164104
46-0.015308-0.1670.433829
47-0.057284-0.62490.266618
480.4131574.5078e-06







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.216906-2.36620.009794
2-0.104807-1.14330.127603
3-0.191113-2.08480.019613
4-0.021979-0.23980.405463
5-0.161887-1.7660.039982
6-0.047081-0.51360.304244
7-0.123989-1.35260.089381
8-0.013633-0.14870.441014
9-0.190288-2.07580.020033
10-0.202374-2.20760.014593
11-0.356777-3.8928.2e-05
120.7549058.2350
130.0226310.24690.402713
140.0220060.24010.40535
15-0.014819-0.16170.435924
160.0432670.4720.318899
170.0084680.09240.463279
180.077160.84170.200818
19-0.100726-1.09880.137039
20-0.019258-0.21010.416982
210.1401631.5290.064459
220.0534310.58290.280543
230.0211850.23110.408818
24-0.006015-0.06560.473895
25-0.016166-0.17630.430161
260.0039220.04280.482974
270.04370.47670.317222
28-0.046821-0.51080.305233
29-0.04663-0.50870.305962
300.025740.28080.38968
310.0711470.77610.21961
32-0.010283-0.11220.455439
33-0.060151-0.65620.256492
34-0.048444-0.52850.299081
350.0587220.64060.261514
36-0.025592-0.27920.390299
370.001550.01690.493268
38-0.081776-0.89210.187078
390.0062030.06770.473082
40-0.12315-1.34340.090847
41-0.043859-0.47840.316605
42-0.129025-1.40750.080943
43-0.025571-0.27890.390385
440.0159360.17380.431143
450.0196510.21440.415315
46-0.090472-0.98690.162839
470.0402730.43930.330609
48-0.056761-0.61920.268489

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.216906 & -2.3662 & 0.009794 \tabularnewline
2 & -0.104807 & -1.1433 & 0.127603 \tabularnewline
3 & -0.191113 & -2.0848 & 0.019613 \tabularnewline
4 & -0.021979 & -0.2398 & 0.405463 \tabularnewline
5 & -0.161887 & -1.766 & 0.039982 \tabularnewline
6 & -0.047081 & -0.5136 & 0.304244 \tabularnewline
7 & -0.123989 & -1.3526 & 0.089381 \tabularnewline
8 & -0.013633 & -0.1487 & 0.441014 \tabularnewline
9 & -0.190288 & -2.0758 & 0.020033 \tabularnewline
10 & -0.202374 & -2.2076 & 0.014593 \tabularnewline
11 & -0.356777 & -3.892 & 8.2e-05 \tabularnewline
12 & 0.754905 & 8.235 & 0 \tabularnewline
13 & 0.022631 & 0.2469 & 0.402713 \tabularnewline
14 & 0.022006 & 0.2401 & 0.40535 \tabularnewline
15 & -0.014819 & -0.1617 & 0.435924 \tabularnewline
16 & 0.043267 & 0.472 & 0.318899 \tabularnewline
17 & 0.008468 & 0.0924 & 0.463279 \tabularnewline
18 & 0.07716 & 0.8417 & 0.200818 \tabularnewline
19 & -0.100726 & -1.0988 & 0.137039 \tabularnewline
20 & -0.019258 & -0.2101 & 0.416982 \tabularnewline
21 & 0.140163 & 1.529 & 0.064459 \tabularnewline
22 & 0.053431 & 0.5829 & 0.280543 \tabularnewline
23 & 0.021185 & 0.2311 & 0.408818 \tabularnewline
24 & -0.006015 & -0.0656 & 0.473895 \tabularnewline
25 & -0.016166 & -0.1763 & 0.430161 \tabularnewline
26 & 0.003922 & 0.0428 & 0.482974 \tabularnewline
27 & 0.0437 & 0.4767 & 0.317222 \tabularnewline
28 & -0.046821 & -0.5108 & 0.305233 \tabularnewline
29 & -0.04663 & -0.5087 & 0.305962 \tabularnewline
30 & 0.02574 & 0.2808 & 0.38968 \tabularnewline
31 & 0.071147 & 0.7761 & 0.21961 \tabularnewline
32 & -0.010283 & -0.1122 & 0.455439 \tabularnewline
33 & -0.060151 & -0.6562 & 0.256492 \tabularnewline
34 & -0.048444 & -0.5285 & 0.299081 \tabularnewline
35 & 0.058722 & 0.6406 & 0.261514 \tabularnewline
36 & -0.025592 & -0.2792 & 0.390299 \tabularnewline
37 & 0.00155 & 0.0169 & 0.493268 \tabularnewline
38 & -0.081776 & -0.8921 & 0.187078 \tabularnewline
39 & 0.006203 & 0.0677 & 0.473082 \tabularnewline
40 & -0.12315 & -1.3434 & 0.090847 \tabularnewline
41 & -0.043859 & -0.4784 & 0.316605 \tabularnewline
42 & -0.129025 & -1.4075 & 0.080943 \tabularnewline
43 & -0.025571 & -0.2789 & 0.390385 \tabularnewline
44 & 0.015936 & 0.1738 & 0.431143 \tabularnewline
45 & 0.019651 & 0.2144 & 0.415315 \tabularnewline
46 & -0.090472 & -0.9869 & 0.162839 \tabularnewline
47 & 0.040273 & 0.4393 & 0.330609 \tabularnewline
48 & -0.056761 & -0.6192 & 0.268489 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306760&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]-0.216906[/C][C]-2.3662[/C][C]0.009794[/C][/ROW]
[ROW][C]2[/C][C]-0.104807[/C][C]-1.1433[/C][C]0.127603[/C][/ROW]
[ROW][C]3[/C][C]-0.191113[/C][C]-2.0848[/C][C]0.019613[/C][/ROW]
[ROW][C]4[/C][C]-0.021979[/C][C]-0.2398[/C][C]0.405463[/C][/ROW]
[ROW][C]5[/C][C]-0.161887[/C][C]-1.766[/C][C]0.039982[/C][/ROW]
[ROW][C]6[/C][C]-0.047081[/C][C]-0.5136[/C][C]0.304244[/C][/ROW]
[ROW][C]7[/C][C]-0.123989[/C][C]-1.3526[/C][C]0.089381[/C][/ROW]
[ROW][C]8[/C][C]-0.013633[/C][C]-0.1487[/C][C]0.441014[/C][/ROW]
[ROW][C]9[/C][C]-0.190288[/C][C]-2.0758[/C][C]0.020033[/C][/ROW]
[ROW][C]10[/C][C]-0.202374[/C][C]-2.2076[/C][C]0.014593[/C][/ROW]
[ROW][C]11[/C][C]-0.356777[/C][C]-3.892[/C][C]8.2e-05[/C][/ROW]
[ROW][C]12[/C][C]0.754905[/C][C]8.235[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.022631[/C][C]0.2469[/C][C]0.402713[/C][/ROW]
[ROW][C]14[/C][C]0.022006[/C][C]0.2401[/C][C]0.40535[/C][/ROW]
[ROW][C]15[/C][C]-0.014819[/C][C]-0.1617[/C][C]0.435924[/C][/ROW]
[ROW][C]16[/C][C]0.043267[/C][C]0.472[/C][C]0.318899[/C][/ROW]
[ROW][C]17[/C][C]0.008468[/C][C]0.0924[/C][C]0.463279[/C][/ROW]
[ROW][C]18[/C][C]0.07716[/C][C]0.8417[/C][C]0.200818[/C][/ROW]
[ROW][C]19[/C][C]-0.100726[/C][C]-1.0988[/C][C]0.137039[/C][/ROW]
[ROW][C]20[/C][C]-0.019258[/C][C]-0.2101[/C][C]0.416982[/C][/ROW]
[ROW][C]21[/C][C]0.140163[/C][C]1.529[/C][C]0.064459[/C][/ROW]
[ROW][C]22[/C][C]0.053431[/C][C]0.5829[/C][C]0.280543[/C][/ROW]
[ROW][C]23[/C][C]0.021185[/C][C]0.2311[/C][C]0.408818[/C][/ROW]
[ROW][C]24[/C][C]-0.006015[/C][C]-0.0656[/C][C]0.473895[/C][/ROW]
[ROW][C]25[/C][C]-0.016166[/C][C]-0.1763[/C][C]0.430161[/C][/ROW]
[ROW][C]26[/C][C]0.003922[/C][C]0.0428[/C][C]0.482974[/C][/ROW]
[ROW][C]27[/C][C]0.0437[/C][C]0.4767[/C][C]0.317222[/C][/ROW]
[ROW][C]28[/C][C]-0.046821[/C][C]-0.5108[/C][C]0.305233[/C][/ROW]
[ROW][C]29[/C][C]-0.04663[/C][C]-0.5087[/C][C]0.305962[/C][/ROW]
[ROW][C]30[/C][C]0.02574[/C][C]0.2808[/C][C]0.38968[/C][/ROW]
[ROW][C]31[/C][C]0.071147[/C][C]0.7761[/C][C]0.21961[/C][/ROW]
[ROW][C]32[/C][C]-0.010283[/C][C]-0.1122[/C][C]0.455439[/C][/ROW]
[ROW][C]33[/C][C]-0.060151[/C][C]-0.6562[/C][C]0.256492[/C][/ROW]
[ROW][C]34[/C][C]-0.048444[/C][C]-0.5285[/C][C]0.299081[/C][/ROW]
[ROW][C]35[/C][C]0.058722[/C][C]0.6406[/C][C]0.261514[/C][/ROW]
[ROW][C]36[/C][C]-0.025592[/C][C]-0.2792[/C][C]0.390299[/C][/ROW]
[ROW][C]37[/C][C]0.00155[/C][C]0.0169[/C][C]0.493268[/C][/ROW]
[ROW][C]38[/C][C]-0.081776[/C][C]-0.8921[/C][C]0.187078[/C][/ROW]
[ROW][C]39[/C][C]0.006203[/C][C]0.0677[/C][C]0.473082[/C][/ROW]
[ROW][C]40[/C][C]-0.12315[/C][C]-1.3434[/C][C]0.090847[/C][/ROW]
[ROW][C]41[/C][C]-0.043859[/C][C]-0.4784[/C][C]0.316605[/C][/ROW]
[ROW][C]42[/C][C]-0.129025[/C][C]-1.4075[/C][C]0.080943[/C][/ROW]
[ROW][C]43[/C][C]-0.025571[/C][C]-0.2789[/C][C]0.390385[/C][/ROW]
[ROW][C]44[/C][C]0.015936[/C][C]0.1738[/C][C]0.431143[/C][/ROW]
[ROW][C]45[/C][C]0.019651[/C][C]0.2144[/C][C]0.415315[/C][/ROW]
[ROW][C]46[/C][C]-0.090472[/C][C]-0.9869[/C][C]0.162839[/C][/ROW]
[ROW][C]47[/C][C]0.040273[/C][C]0.4393[/C][C]0.330609[/C][/ROW]
[ROW][C]48[/C][C]-0.056761[/C][C]-0.6192[/C][C]0.268489[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306760&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306760&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
1-0.216906-2.36620.009794
2-0.104807-1.14330.127603
3-0.191113-2.08480.019613
4-0.021979-0.23980.405463
5-0.161887-1.7660.039982
6-0.047081-0.51360.304244
7-0.123989-1.35260.089381
8-0.013633-0.14870.441014
9-0.190288-2.07580.020033
10-0.202374-2.20760.014593
11-0.356777-3.8928.2e-05
120.7549058.2350
130.0226310.24690.402713
140.0220060.24010.40535
15-0.014819-0.16170.435924
160.0432670.4720.318899
170.0084680.09240.463279
180.077160.84170.200818
19-0.100726-1.09880.137039
20-0.019258-0.21010.416982
210.1401631.5290.064459
220.0534310.58290.280543
230.0211850.23110.408818
24-0.006015-0.06560.473895
25-0.016166-0.17630.430161
260.0039220.04280.482974
270.04370.47670.317222
28-0.046821-0.51080.305233
29-0.04663-0.50870.305962
300.025740.28080.38968
310.0711470.77610.21961
32-0.010283-0.11220.455439
33-0.060151-0.65620.256492
34-0.048444-0.52850.299081
350.0587220.64060.261514
36-0.025592-0.27920.390299
370.001550.01690.493268
38-0.081776-0.89210.187078
390.0062030.06770.473082
40-0.12315-1.34340.090847
41-0.043859-0.47840.316605
42-0.129025-1.40750.080943
43-0.025571-0.27890.390385
440.0159360.17380.431143
450.0196510.21440.415315
46-0.090472-0.98690.162839
470.0402730.43930.330609
48-0.056761-0.61920.268489



Parameters (Session):
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- 'Yt-Yt-1'
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '1'
par2 <- '1'
par1 <- '48'
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')