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Description of Statistical Computation

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 computationFri, 09 Dec 2016 18:53:20 +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/09/t1481306075ocpveis4s29vqq2.htm/, Retrieved Sat, 18 May 2024 08:19:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298597, Retrieved Sat, 18 May 2024 08:19:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelation F...] [2016-12-09 17:53:20] [e6dc02234f5305f92311fb16bc25f73e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13663
11635
9606
8784.5
9415.5
10418
11344.5
11271
11895
12152.5
12731
12951
10692
8563.5
6217
5562
6294.5
7422
9254.5
10607
11268
12041
12962.5
12200.5
10400.5
8765
7000
6677
7318
7999
8762
9696
10373
10682.5
10935.5
10815.5
8669
7079.5
5640
5238.5
5777.5
6479
7290
7343
7810.5
8171.5
8532
8719
7281.5
5923.5
4837
4675.5
4585.5
5083
5766
6201
6778
7393.5
7849.5
8282.5
7610
6192.5
4693.5
4869
5149
5648.5
6230.5
7032
7727
8087.5
8443
9002
7717.5
6374.5
4995.5
4655
5198
5501
6119.5
6922
7390
7466.5
7773
7865
6567
5132.5
3656.5
3623
4045.5
4617
5374
6022.5
6464.5
7058
7484.5
7955
6801
5499
4179.5
4305.5
3304
5773.5
6419.5
6938
7760
8224
8381
8667
7304.5
5565.5
4023
3932.5
4508.5
5491
6284

Tables (Output of Computation)





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=298597&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=298597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298597&T=0

As an alternative you can also use a QR Code:  
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
10.628346.70880
20.2472872.64030.004722
3-0.169423-1.80890.036548
4-0.413742-4.41761.1e-05
5-0.498867-5.32640
6-0.486941-5.19910
7-0.475178-5.07351e-06
8-0.365554-3.9038.1e-05
9-0.129409-1.38170.084881
100.2708172.89150.002296
110.6071176.48220
120.7693768.21470
130.5529725.90410
140.1904192.03310.022181
15-0.173814-1.85580.03303
16-0.344014-3.67310.000183
17-0.428764-4.57796e-06
18-0.434146-4.63545e-06
19-0.378059-4.03664.9e-05
20-0.313467-3.34690.000554
21-0.116715-1.24620.107627
220.2217532.36770.009792
230.4842845.17071e-06
240.6136556.5520
250.4531864.83872e-06
260.1649451.76110.040448
27-0.132684-1.41670.079653
28-0.268116-2.86270.0025
29-0.329898-3.52230.000308
30-0.34471-3.68050.000179
31-0.310968-3.32020.000604
32-0.259517-2.77090.003265
33-0.105037-1.12150.132218
340.1693011.80760.03665
350.4016914.28891.9e-05
360.5302195.66120
370.3802264.05974.5e-05
380.1671151.78430.038518
39-0.104032-1.11080.134505
40-0.2312-2.46850.007525
41-0.261239-2.78930.003097
42-0.274427-2.93010.002047
43-0.275418-2.94070.001983
44-0.230693-2.46310.007634
45-0.094766-1.01180.156883
460.1216461.29880.098314
470.3340143.56630.000265
480.4547794.85572e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.62834 & 6.7088 & 0 \tabularnewline
2 & 0.247287 & 2.6403 & 0.004722 \tabularnewline
3 & -0.169423 & -1.8089 & 0.036548 \tabularnewline
4 & -0.413742 & -4.4176 & 1.1e-05 \tabularnewline
5 & -0.498867 & -5.3264 & 0 \tabularnewline
6 & -0.486941 & -5.1991 & 0 \tabularnewline
7 & -0.475178 & -5.0735 & 1e-06 \tabularnewline
8 & -0.365554 & -3.903 & 8.1e-05 \tabularnewline
9 & -0.129409 & -1.3817 & 0.084881 \tabularnewline
10 & 0.270817 & 2.8915 & 0.002296 \tabularnewline
11 & 0.607117 & 6.4822 & 0 \tabularnewline
12 & 0.769376 & 8.2147 & 0 \tabularnewline
13 & 0.552972 & 5.9041 & 0 \tabularnewline
14 & 0.190419 & 2.0331 & 0.022181 \tabularnewline
15 & -0.173814 & -1.8558 & 0.03303 \tabularnewline
16 & -0.344014 & -3.6731 & 0.000183 \tabularnewline
17 & -0.428764 & -4.5779 & 6e-06 \tabularnewline
18 & -0.434146 & -4.6354 & 5e-06 \tabularnewline
19 & -0.378059 & -4.0366 & 4.9e-05 \tabularnewline
20 & -0.313467 & -3.3469 & 0.000554 \tabularnewline
21 & -0.116715 & -1.2462 & 0.107627 \tabularnewline
22 & 0.221753 & 2.3677 & 0.009792 \tabularnewline
23 & 0.484284 & 5.1707 & 1e-06 \tabularnewline
24 & 0.613655 & 6.552 & 0 \tabularnewline
25 & 0.453186 & 4.8387 & 2e-06 \tabularnewline
26 & 0.164945 & 1.7611 & 0.040448 \tabularnewline
27 & -0.132684 & -1.4167 & 0.079653 \tabularnewline
28 & -0.268116 & -2.8627 & 0.0025 \tabularnewline
29 & -0.329898 & -3.5223 & 0.000308 \tabularnewline
30 & -0.34471 & -3.6805 & 0.000179 \tabularnewline
31 & -0.310968 & -3.3202 & 0.000604 \tabularnewline
32 & -0.259517 & -2.7709 & 0.003265 \tabularnewline
33 & -0.105037 & -1.1215 & 0.132218 \tabularnewline
34 & 0.169301 & 1.8076 & 0.03665 \tabularnewline
35 & 0.401691 & 4.2889 & 1.9e-05 \tabularnewline
36 & 0.530219 & 5.6612 & 0 \tabularnewline
37 & 0.380226 & 4.0597 & 4.5e-05 \tabularnewline
38 & 0.167115 & 1.7843 & 0.038518 \tabularnewline
39 & -0.104032 & -1.1108 & 0.134505 \tabularnewline
40 & -0.2312 & -2.4685 & 0.007525 \tabularnewline
41 & -0.261239 & -2.7893 & 0.003097 \tabularnewline
42 & -0.274427 & -2.9301 & 0.002047 \tabularnewline
43 & -0.275418 & -2.9407 & 0.001983 \tabularnewline
44 & -0.230693 & -2.4631 & 0.007634 \tabularnewline
45 & -0.094766 & -1.0118 & 0.156883 \tabularnewline
46 & 0.121646 & 1.2988 & 0.098314 \tabularnewline
47 & 0.334014 & 3.5663 & 0.000265 \tabularnewline
48 & 0.454779 & 4.8557 & 2e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298597&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]0.62834[/C][C]6.7088[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.247287[/C][C]2.6403[/C][C]0.004722[/C][/ROW]
[ROW][C]3[/C][C]-0.169423[/C][C]-1.8089[/C][C]0.036548[/C][/ROW]
[ROW][C]4[/C][C]-0.413742[/C][C]-4.4176[/C][C]1.1e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.498867[/C][C]-5.3264[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]-0.486941[/C][C]-5.1991[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.475178[/C][C]-5.0735[/C][C]1e-06[/C][/ROW]
[ROW][C]8[/C][C]-0.365554[/C][C]-3.903[/C][C]8.1e-05[/C][/ROW]
[ROW][C]9[/C][C]-0.129409[/C][C]-1.3817[/C][C]0.084881[/C][/ROW]
[ROW][C]10[/C][C]0.270817[/C][C]2.8915[/C][C]0.002296[/C][/ROW]
[ROW][C]11[/C][C]0.607117[/C][C]6.4822[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.769376[/C][C]8.2147[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.552972[/C][C]5.9041[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.190419[/C][C]2.0331[/C][C]0.022181[/C][/ROW]
[ROW][C]15[/C][C]-0.173814[/C][C]-1.8558[/C][C]0.03303[/C][/ROW]
[ROW][C]16[/C][C]-0.344014[/C][C]-3.6731[/C][C]0.000183[/C][/ROW]
[ROW][C]17[/C][C]-0.428764[/C][C]-4.5779[/C][C]6e-06[/C][/ROW]
[ROW][C]18[/C][C]-0.434146[/C][C]-4.6354[/C][C]5e-06[/C][/ROW]
[ROW][C]19[/C][C]-0.378059[/C][C]-4.0366[/C][C]4.9e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.313467[/C][C]-3.3469[/C][C]0.000554[/C][/ROW]
[ROW][C]21[/C][C]-0.116715[/C][C]-1.2462[/C][C]0.107627[/C][/ROW]
[ROW][C]22[/C][C]0.221753[/C][C]2.3677[/C][C]0.009792[/C][/ROW]
[ROW][C]23[/C][C]0.484284[/C][C]5.1707[/C][C]1e-06[/C][/ROW]
[ROW][C]24[/C][C]0.613655[/C][C]6.552[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.453186[/C][C]4.8387[/C][C]2e-06[/C][/ROW]
[ROW][C]26[/C][C]0.164945[/C][C]1.7611[/C][C]0.040448[/C][/ROW]
[ROW][C]27[/C][C]-0.132684[/C][C]-1.4167[/C][C]0.079653[/C][/ROW]
[ROW][C]28[/C][C]-0.268116[/C][C]-2.8627[/C][C]0.0025[/C][/ROW]
[ROW][C]29[/C][C]-0.329898[/C][C]-3.5223[/C][C]0.000308[/C][/ROW]
[ROW][C]30[/C][C]-0.34471[/C][C]-3.6805[/C][C]0.000179[/C][/ROW]
[ROW][C]31[/C][C]-0.310968[/C][C]-3.3202[/C][C]0.000604[/C][/ROW]
[ROW][C]32[/C][C]-0.259517[/C][C]-2.7709[/C][C]0.003265[/C][/ROW]
[ROW][C]33[/C][C]-0.105037[/C][C]-1.1215[/C][C]0.132218[/C][/ROW]
[ROW][C]34[/C][C]0.169301[/C][C]1.8076[/C][C]0.03665[/C][/ROW]
[ROW][C]35[/C][C]0.401691[/C][C]4.2889[/C][C]1.9e-05[/C][/ROW]
[ROW][C]36[/C][C]0.530219[/C][C]5.6612[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.380226[/C][C]4.0597[/C][C]4.5e-05[/C][/ROW]
[ROW][C]38[/C][C]0.167115[/C][C]1.7843[/C][C]0.038518[/C][/ROW]
[ROW][C]39[/C][C]-0.104032[/C][C]-1.1108[/C][C]0.134505[/C][/ROW]
[ROW][C]40[/C][C]-0.2312[/C][C]-2.4685[/C][C]0.007525[/C][/ROW]
[ROW][C]41[/C][C]-0.261239[/C][C]-2.7893[/C][C]0.003097[/C][/ROW]
[ROW][C]42[/C][C]-0.274427[/C][C]-2.9301[/C][C]0.002047[/C][/ROW]
[ROW][C]43[/C][C]-0.275418[/C][C]-2.9407[/C][C]0.001983[/C][/ROW]
[ROW][C]44[/C][C]-0.230693[/C][C]-2.4631[/C][C]0.007634[/C][/ROW]
[ROW][C]45[/C][C]-0.094766[/C][C]-1.0118[/C][C]0.156883[/C][/ROW]
[ROW][C]46[/C][C]0.121646[/C][C]1.2988[/C][C]0.098314[/C][/ROW]
[ROW][C]47[/C][C]0.334014[/C][C]3.5663[/C][C]0.000265[/C][/ROW]
[ROW][C]48[/C][C]0.454779[/C][C]4.8557[/C][C]2e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298597&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.628346.70880
20.2472872.64030.004722
3-0.169423-1.80890.036548
4-0.413742-4.41761.1e-05
5-0.498867-5.32640
6-0.486941-5.19910
7-0.475178-5.07351e-06
8-0.365554-3.9038.1e-05
9-0.129409-1.38170.084881
100.2708172.89150.002296
110.6071176.48220
120.7693768.21470
130.5529725.90410
140.1904192.03310.022181
15-0.173814-1.85580.03303
16-0.344014-3.67310.000183
17-0.428764-4.57796e-06
18-0.434146-4.63545e-06
19-0.378059-4.03664.9e-05
20-0.313467-3.34690.000554
21-0.116715-1.24620.107627
220.2217532.36770.009792
230.4842845.17071e-06
240.6136556.5520
250.4531864.83872e-06
260.1649451.76110.040448
27-0.132684-1.41670.079653
28-0.268116-2.86270.0025
29-0.329898-3.52230.000308
30-0.34471-3.68050.000179
31-0.310968-3.32020.000604
32-0.259517-2.77090.003265
33-0.105037-1.12150.132218
340.1693011.80760.03665
350.4016914.28891.9e-05
360.5302195.66120
370.3802264.05974.5e-05
380.1671151.78430.038518
39-0.104032-1.11080.134505
40-0.2312-2.46850.007525
41-0.261239-2.78930.003097
42-0.274427-2.93010.002047
43-0.275418-2.94070.001983
44-0.230693-2.46310.007634
45-0.094766-1.01180.156883
460.1216461.29880.098314
470.3340143.56630.000265
480.4547794.85572e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.628346.70880
2-0.243764-2.60270.005239
3-0.368065-3.92997.3e-05
4-0.154678-1.65150.050694
5-0.13713-1.46410.072953
6-0.24364-2.60140.005258
7-0.417315-4.45571e-05
8-0.338334-3.61240.000226
9-0.209154-2.23310.013746
100.1074241.1470.126898
110.156531.67130.048704
120.2467032.63410.004804
13-0.059272-0.63290.264048
14-0.068543-0.73180.232885
15-0.033345-0.3560.361238
160.1491491.59250.057024
170.0371890.39710.34603
18-0.006004-0.06410.474501
190.1585221.69260.046636
20-0.051098-0.54560.293211
21-0.109392-1.1680.122625
22-0.022836-0.24380.403905
23-0.08914-0.95180.171616
240.0116880.12480.450455
25-0.048289-0.51560.30357
26-0.030027-0.32060.37455
27-0.066776-0.7130.238658
280.0348260.37180.355352
29-0.012601-0.13450.446606
30-0.057505-0.6140.270223
310.0541140.57780.282275
32-0.005654-0.06040.475982
33-3.8e-05-4e-040.499838
340.060570.64670.259561
350.0209790.2240.411581
360.158041.68740.047129
370.000970.01040.495878
380.0846030.90330.184132
39-0.014903-0.15910.436926
400.0336970.35980.359835
410.0893740.95430.170986
420.0305480.32620.37245
430.0028320.03020.487964
44-0.007367-0.07870.468722
450.0609510.65080.258251
46-0.029241-0.31220.377726
47-0.046301-0.49440.311003
480.0649390.69340.244747

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.62834 & 6.7088 & 0 \tabularnewline
2 & -0.243764 & -2.6027 & 0.005239 \tabularnewline
3 & -0.368065 & -3.9299 & 7.3e-05 \tabularnewline
4 & -0.154678 & -1.6515 & 0.050694 \tabularnewline
5 & -0.13713 & -1.4641 & 0.072953 \tabularnewline
6 & -0.24364 & -2.6014 & 0.005258 \tabularnewline
7 & -0.417315 & -4.4557 & 1e-05 \tabularnewline
8 & -0.338334 & -3.6124 & 0.000226 \tabularnewline
9 & -0.209154 & -2.2331 & 0.013746 \tabularnewline
10 & 0.107424 & 1.147 & 0.126898 \tabularnewline
11 & 0.15653 & 1.6713 & 0.048704 \tabularnewline
12 & 0.246703 & 2.6341 & 0.004804 \tabularnewline
13 & -0.059272 & -0.6329 & 0.264048 \tabularnewline
14 & -0.068543 & -0.7318 & 0.232885 \tabularnewline
15 & -0.033345 & -0.356 & 0.361238 \tabularnewline
16 & 0.149149 & 1.5925 & 0.057024 \tabularnewline
17 & 0.037189 & 0.3971 & 0.34603 \tabularnewline
18 & -0.006004 & -0.0641 & 0.474501 \tabularnewline
19 & 0.158522 & 1.6926 & 0.046636 \tabularnewline
20 & -0.051098 & -0.5456 & 0.293211 \tabularnewline
21 & -0.109392 & -1.168 & 0.122625 \tabularnewline
22 & -0.022836 & -0.2438 & 0.403905 \tabularnewline
23 & -0.08914 & -0.9518 & 0.171616 \tabularnewline
24 & 0.011688 & 0.1248 & 0.450455 \tabularnewline
25 & -0.048289 & -0.5156 & 0.30357 \tabularnewline
26 & -0.030027 & -0.3206 & 0.37455 \tabularnewline
27 & -0.066776 & -0.713 & 0.238658 \tabularnewline
28 & 0.034826 & 0.3718 & 0.355352 \tabularnewline
29 & -0.012601 & -0.1345 & 0.446606 \tabularnewline
30 & -0.057505 & -0.614 & 0.270223 \tabularnewline
31 & 0.054114 & 0.5778 & 0.282275 \tabularnewline
32 & -0.005654 & -0.0604 & 0.475982 \tabularnewline
33 & -3.8e-05 & -4e-04 & 0.499838 \tabularnewline
34 & 0.06057 & 0.6467 & 0.259561 \tabularnewline
35 & 0.020979 & 0.224 & 0.411581 \tabularnewline
36 & 0.15804 & 1.6874 & 0.047129 \tabularnewline
37 & 0.00097 & 0.0104 & 0.495878 \tabularnewline
38 & 0.084603 & 0.9033 & 0.184132 \tabularnewline
39 & -0.014903 & -0.1591 & 0.436926 \tabularnewline
40 & 0.033697 & 0.3598 & 0.359835 \tabularnewline
41 & 0.089374 & 0.9543 & 0.170986 \tabularnewline
42 & 0.030548 & 0.3262 & 0.37245 \tabularnewline
43 & 0.002832 & 0.0302 & 0.487964 \tabularnewline
44 & -0.007367 & -0.0787 & 0.468722 \tabularnewline
45 & 0.060951 & 0.6508 & 0.258251 \tabularnewline
46 & -0.029241 & -0.3122 & 0.377726 \tabularnewline
47 & -0.046301 & -0.4944 & 0.311003 \tabularnewline
48 & 0.064939 & 0.6934 & 0.244747 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298597&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]0.62834[/C][C]6.7088[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.243764[/C][C]-2.6027[/C][C]0.005239[/C][/ROW]
[ROW][C]3[/C][C]-0.368065[/C][C]-3.9299[/C][C]7.3e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.154678[/C][C]-1.6515[/C][C]0.050694[/C][/ROW]
[ROW][C]5[/C][C]-0.13713[/C][C]-1.4641[/C][C]0.072953[/C][/ROW]
[ROW][C]6[/C][C]-0.24364[/C][C]-2.6014[/C][C]0.005258[/C][/ROW]
[ROW][C]7[/C][C]-0.417315[/C][C]-4.4557[/C][C]1e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.338334[/C][C]-3.6124[/C][C]0.000226[/C][/ROW]
[ROW][C]9[/C][C]-0.209154[/C][C]-2.2331[/C][C]0.013746[/C][/ROW]
[ROW][C]10[/C][C]0.107424[/C][C]1.147[/C][C]0.126898[/C][/ROW]
[ROW][C]11[/C][C]0.15653[/C][C]1.6713[/C][C]0.048704[/C][/ROW]
[ROW][C]12[/C][C]0.246703[/C][C]2.6341[/C][C]0.004804[/C][/ROW]
[ROW][C]13[/C][C]-0.059272[/C][C]-0.6329[/C][C]0.264048[/C][/ROW]
[ROW][C]14[/C][C]-0.068543[/C][C]-0.7318[/C][C]0.232885[/C][/ROW]
[ROW][C]15[/C][C]-0.033345[/C][C]-0.356[/C][C]0.361238[/C][/ROW]
[ROW][C]16[/C][C]0.149149[/C][C]1.5925[/C][C]0.057024[/C][/ROW]
[ROW][C]17[/C][C]0.037189[/C][C]0.3971[/C][C]0.34603[/C][/ROW]
[ROW][C]18[/C][C]-0.006004[/C][C]-0.0641[/C][C]0.474501[/C][/ROW]
[ROW][C]19[/C][C]0.158522[/C][C]1.6926[/C][C]0.046636[/C][/ROW]
[ROW][C]20[/C][C]-0.051098[/C][C]-0.5456[/C][C]0.293211[/C][/ROW]
[ROW][C]21[/C][C]-0.109392[/C][C]-1.168[/C][C]0.122625[/C][/ROW]
[ROW][C]22[/C][C]-0.022836[/C][C]-0.2438[/C][C]0.403905[/C][/ROW]
[ROW][C]23[/C][C]-0.08914[/C][C]-0.9518[/C][C]0.171616[/C][/ROW]
[ROW][C]24[/C][C]0.011688[/C][C]0.1248[/C][C]0.450455[/C][/ROW]
[ROW][C]25[/C][C]-0.048289[/C][C]-0.5156[/C][C]0.30357[/C][/ROW]
[ROW][C]26[/C][C]-0.030027[/C][C]-0.3206[/C][C]0.37455[/C][/ROW]
[ROW][C]27[/C][C]-0.066776[/C][C]-0.713[/C][C]0.238658[/C][/ROW]
[ROW][C]28[/C][C]0.034826[/C][C]0.3718[/C][C]0.355352[/C][/ROW]
[ROW][C]29[/C][C]-0.012601[/C][C]-0.1345[/C][C]0.446606[/C][/ROW]
[ROW][C]30[/C][C]-0.057505[/C][C]-0.614[/C][C]0.270223[/C][/ROW]
[ROW][C]31[/C][C]0.054114[/C][C]0.5778[/C][C]0.282275[/C][/ROW]
[ROW][C]32[/C][C]-0.005654[/C][C]-0.0604[/C][C]0.475982[/C][/ROW]
[ROW][C]33[/C][C]-3.8e-05[/C][C]-4e-04[/C][C]0.499838[/C][/ROW]
[ROW][C]34[/C][C]0.06057[/C][C]0.6467[/C][C]0.259561[/C][/ROW]
[ROW][C]35[/C][C]0.020979[/C][C]0.224[/C][C]0.411581[/C][/ROW]
[ROW][C]36[/C][C]0.15804[/C][C]1.6874[/C][C]0.047129[/C][/ROW]
[ROW][C]37[/C][C]0.00097[/C][C]0.0104[/C][C]0.495878[/C][/ROW]
[ROW][C]38[/C][C]0.084603[/C][C]0.9033[/C][C]0.184132[/C][/ROW]
[ROW][C]39[/C][C]-0.014903[/C][C]-0.1591[/C][C]0.436926[/C][/ROW]
[ROW][C]40[/C][C]0.033697[/C][C]0.3598[/C][C]0.359835[/C][/ROW]
[ROW][C]41[/C][C]0.089374[/C][C]0.9543[/C][C]0.170986[/C][/ROW]
[ROW][C]42[/C][C]0.030548[/C][C]0.3262[/C][C]0.37245[/C][/ROW]
[ROW][C]43[/C][C]0.002832[/C][C]0.0302[/C][C]0.487964[/C][/ROW]
[ROW][C]44[/C][C]-0.007367[/C][C]-0.0787[/C][C]0.468722[/C][/ROW]
[ROW][C]45[/C][C]0.060951[/C][C]0.6508[/C][C]0.258251[/C][/ROW]
[ROW][C]46[/C][C]-0.029241[/C][C]-0.3122[/C][C]0.377726[/C][/ROW]
[ROW][C]47[/C][C]-0.046301[/C][C]-0.4944[/C][C]0.311003[/C][/ROW]
[ROW][C]48[/C][C]0.064939[/C][C]0.6934[/C][C]0.244747[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298597&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298597&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.628346.70880
2-0.243764-2.60270.005239
3-0.368065-3.92997.3e-05
4-0.154678-1.65150.050694
5-0.13713-1.46410.072953
6-0.24364-2.60140.005258
7-0.417315-4.45571e-05
8-0.338334-3.61240.000226
9-0.209154-2.23310.013746
100.1074241.1470.126898
110.156531.67130.048704
120.2467032.63410.004804
13-0.059272-0.63290.264048
14-0.068543-0.73180.232885
15-0.033345-0.3560.361238
160.1491491.59250.057024
170.0371890.39710.34603
18-0.006004-0.06410.474501
190.1585221.69260.046636
20-0.051098-0.54560.293211
21-0.109392-1.1680.122625
22-0.022836-0.24380.403905
23-0.08914-0.95180.171616
240.0116880.12480.450455
25-0.048289-0.51560.30357
26-0.030027-0.32060.37455
27-0.066776-0.7130.238658
280.0348260.37180.355352
29-0.012601-0.13450.446606
30-0.057505-0.6140.270223
310.0541140.57780.282275
32-0.005654-0.06040.475982
33-3.8e-05-4e-040.499838
340.060570.64670.259561
350.0209790.2240.411581
360.158041.68740.047129
370.000970.01040.495878
380.0846030.90330.184132
39-0.014903-0.15910.436926
400.0336970.35980.359835
410.0893740.95430.170986
420.0305480.32620.37245
430.0028320.03020.487964
44-0.007367-0.07870.468722
450.0609510.65080.258251
46-0.029241-0.31220.377726
47-0.046301-0.49440.311003
480.0649390.69340.244747


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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):
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')