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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 03 Aug 2017 22:39:01 +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/Aug/03/t1501792770l0p7i2r76rldjes.htm/, Retrieved Thu, 09 May 2024 23:12:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306896, Retrieved Thu, 09 May 2024 23:12:49 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

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] [Reeks B stap 18] [2017-08-03 20:39:01] [5e513ceaaef205c0c6f269c0b513af8d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 755 000
1 690 000
1 787 500
1 430 000
1 852 500
1 820 000
1 950 000
2 015 000
2 242 500
1 950 000
1 852 500
2 307 500
1 950 000
1 462 500
1 722 500
1 300 000
1 820 000
1 495 000
1 982 500
1 787 500
1 885 000
2 112 500
2 080 000
2 470 000
1 787 500
1 495 000
1 657 500
1 202 500
1 722 500
1 332 500
1 885 000
1 787 500
1 592 500
2 275 000
2 047 500
2 340 000
1 755 000
1 625 000
1 462 500
1 202 500
1 592 500
1 430 000
1 950 000
1 885 000
1 625 000
2 177 500
2 015 000
2 600 000
2 080 000
1 267 500
1 267 500
1 267 500
1 495 000
1 495 000
2 015 000
1 852 500
1 657 500
2 080 000
1 917 500
2 762 500
2 177 500
1 267 500
1 332 500
1 105 000
1 527 500
1 755 000
2 210 000
2 177 500
1 755 000
2 047 500
1 820 000
2 600 000
1 982 500
1 592 500
1 430 000
1 072 500
1 592 500
1 917 500
2 242 500
2 112 500
1 560 000
2 242 500
1 755 000
2 697 500
2 242 500
1 625 000
1 495 000
1 007 500
1 592 500
1 527 500
2 307 500
2 307 500
1 755 000
2 275 000
1 690 000
2 632 500
2 242 500
1 657 500
1 267 500
877 500
1 722 500
1 657 500
2 177 500
2 502 500
1 852 500
2 080 000
1 560 000
2 697 500

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=306896&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=306896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306896&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
1-0.34099-3.52720.00031
20.1611711.66720.049203
3-0.187224-1.93670.027712
4-0.339596-3.51280.000325
50.3709553.83720.000105
6-0.34395-3.55780.000279
70.4181114.3251.7e-05
8-0.287596-2.97490.001811
9-0.184079-1.90410.02979
100.1344191.39040.083641
11-0.313093-3.23878e-04
120.7895528.16720
13-0.255181-2.63960.00477
140.1906571.97220.025585
15-0.164844-1.70520.045533
16-0.350569-3.62630.000221
170.3377353.49360.000347
18-0.308274-3.18880.000937
190.3765073.89468.6e-05
20-0.224228-2.31940.011135
21-0.157817-1.63250.05276
220.1035141.07080.143344
23-0.273867-2.83290.002757
240.6024246.23150
25-0.138764-1.43540.077048
260.1768421.82930.035072
27-0.136543-1.41240.080366
28-0.308312-3.18920.000936
290.2472632.55770.005968
30-0.257776-2.66650.004428
310.3053563.15860.00103
32-0.153114-1.58380.058093
33-0.118564-1.22640.111363
340.0930660.96270.168939
35-0.263403-2.72470.00376
360.5013685.18621e-06
37-0.076549-0.79180.215107
380.0989851.02390.154094
39-0.083705-0.86590.194254
40-0.251284-2.59930.00533
410.1909591.97530.025405
42-0.253929-2.62670.004944
430.276632.86150.002536
44-0.101626-1.05120.14776
45-0.079109-0.81830.2075
460.0858940.88850.188134
47-0.251043-2.59680.005366
480.3942864.07854.4e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.34099 & -3.5272 & 0.00031 \tabularnewline
2 & 0.161171 & 1.6672 & 0.049203 \tabularnewline
3 & -0.187224 & -1.9367 & 0.027712 \tabularnewline
4 & -0.339596 & -3.5128 & 0.000325 \tabularnewline
5 & 0.370955 & 3.8372 & 0.000105 \tabularnewline
6 & -0.34395 & -3.5578 & 0.000279 \tabularnewline
7 & 0.418111 & 4.325 & 1.7e-05 \tabularnewline
8 & -0.287596 & -2.9749 & 0.001811 \tabularnewline
9 & -0.184079 & -1.9041 & 0.02979 \tabularnewline
10 & 0.134419 & 1.3904 & 0.083641 \tabularnewline
11 & -0.313093 & -3.2387 & 8e-04 \tabularnewline
12 & 0.789552 & 8.1672 & 0 \tabularnewline
13 & -0.255181 & -2.6396 & 0.00477 \tabularnewline
14 & 0.190657 & 1.9722 & 0.025585 \tabularnewline
15 & -0.164844 & -1.7052 & 0.045533 \tabularnewline
16 & -0.350569 & -3.6263 & 0.000221 \tabularnewline
17 & 0.337735 & 3.4936 & 0.000347 \tabularnewline
18 & -0.308274 & -3.1888 & 0.000937 \tabularnewline
19 & 0.376507 & 3.8946 & 8.6e-05 \tabularnewline
20 & -0.224228 & -2.3194 & 0.011135 \tabularnewline
21 & -0.157817 & -1.6325 & 0.05276 \tabularnewline
22 & 0.103514 & 1.0708 & 0.143344 \tabularnewline
23 & -0.273867 & -2.8329 & 0.002757 \tabularnewline
24 & 0.602424 & 6.2315 & 0 \tabularnewline
25 & -0.138764 & -1.4354 & 0.077048 \tabularnewline
26 & 0.176842 & 1.8293 & 0.035072 \tabularnewline
27 & -0.136543 & -1.4124 & 0.080366 \tabularnewline
28 & -0.308312 & -3.1892 & 0.000936 \tabularnewline
29 & 0.247263 & 2.5577 & 0.005968 \tabularnewline
30 & -0.257776 & -2.6665 & 0.004428 \tabularnewline
31 & 0.305356 & 3.1586 & 0.00103 \tabularnewline
32 & -0.153114 & -1.5838 & 0.058093 \tabularnewline
33 & -0.118564 & -1.2264 & 0.111363 \tabularnewline
34 & 0.093066 & 0.9627 & 0.168939 \tabularnewline
35 & -0.263403 & -2.7247 & 0.00376 \tabularnewline
36 & 0.501368 & 5.1862 & 1e-06 \tabularnewline
37 & -0.076549 & -0.7918 & 0.215107 \tabularnewline
38 & 0.098985 & 1.0239 & 0.154094 \tabularnewline
39 & -0.083705 & -0.8659 & 0.194254 \tabularnewline
40 & -0.251284 & -2.5993 & 0.00533 \tabularnewline
41 & 0.190959 & 1.9753 & 0.025405 \tabularnewline
42 & -0.253929 & -2.6267 & 0.004944 \tabularnewline
43 & 0.27663 & 2.8615 & 0.002536 \tabularnewline
44 & -0.101626 & -1.0512 & 0.14776 \tabularnewline
45 & -0.079109 & -0.8183 & 0.2075 \tabularnewline
46 & 0.085894 & 0.8885 & 0.188134 \tabularnewline
47 & -0.251043 & -2.5968 & 0.005366 \tabularnewline
48 & 0.394286 & 4.0785 & 4.4e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306896&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]-0.34099[/C][C]-3.5272[/C][C]0.00031[/C][/ROW]
[ROW][C]2[/C][C]0.161171[/C][C]1.6672[/C][C]0.049203[/C][/ROW]
[ROW][C]3[/C][C]-0.187224[/C][C]-1.9367[/C][C]0.027712[/C][/ROW]
[ROW][C]4[/C][C]-0.339596[/C][C]-3.5128[/C][C]0.000325[/C][/ROW]
[ROW][C]5[/C][C]0.370955[/C][C]3.8372[/C][C]0.000105[/C][/ROW]
[ROW][C]6[/C][C]-0.34395[/C][C]-3.5578[/C][C]0.000279[/C][/ROW]
[ROW][C]7[/C][C]0.418111[/C][C]4.325[/C][C]1.7e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.287596[/C][C]-2.9749[/C][C]0.001811[/C][/ROW]
[ROW][C]9[/C][C]-0.184079[/C][C]-1.9041[/C][C]0.02979[/C][/ROW]
[ROW][C]10[/C][C]0.134419[/C][C]1.3904[/C][C]0.083641[/C][/ROW]
[ROW][C]11[/C][C]-0.313093[/C][C]-3.2387[/C][C]8e-04[/C][/ROW]
[ROW][C]12[/C][C]0.789552[/C][C]8.1672[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.255181[/C][C]-2.6396[/C][C]0.00477[/C][/ROW]
[ROW][C]14[/C][C]0.190657[/C][C]1.9722[/C][C]0.025585[/C][/ROW]
[ROW][C]15[/C][C]-0.164844[/C][C]-1.7052[/C][C]0.045533[/C][/ROW]
[ROW][C]16[/C][C]-0.350569[/C][C]-3.6263[/C][C]0.000221[/C][/ROW]
[ROW][C]17[/C][C]0.337735[/C][C]3.4936[/C][C]0.000347[/C][/ROW]
[ROW][C]18[/C][C]-0.308274[/C][C]-3.1888[/C][C]0.000937[/C][/ROW]
[ROW][C]19[/C][C]0.376507[/C][C]3.8946[/C][C]8.6e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.224228[/C][C]-2.3194[/C][C]0.011135[/C][/ROW]
[ROW][C]21[/C][C]-0.157817[/C][C]-1.6325[/C][C]0.05276[/C][/ROW]
[ROW][C]22[/C][C]0.103514[/C][C]1.0708[/C][C]0.143344[/C][/ROW]
[ROW][C]23[/C][C]-0.273867[/C][C]-2.8329[/C][C]0.002757[/C][/ROW]
[ROW][C]24[/C][C]0.602424[/C][C]6.2315[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.138764[/C][C]-1.4354[/C][C]0.077048[/C][/ROW]
[ROW][C]26[/C][C]0.176842[/C][C]1.8293[/C][C]0.035072[/C][/ROW]
[ROW][C]27[/C][C]-0.136543[/C][C]-1.4124[/C][C]0.080366[/C][/ROW]
[ROW][C]28[/C][C]-0.308312[/C][C]-3.1892[/C][C]0.000936[/C][/ROW]
[ROW][C]29[/C][C]0.247263[/C][C]2.5577[/C][C]0.005968[/C][/ROW]
[ROW][C]30[/C][C]-0.257776[/C][C]-2.6665[/C][C]0.004428[/C][/ROW]
[ROW][C]31[/C][C]0.305356[/C][C]3.1586[/C][C]0.00103[/C][/ROW]
[ROW][C]32[/C][C]-0.153114[/C][C]-1.5838[/C][C]0.058093[/C][/ROW]
[ROW][C]33[/C][C]-0.118564[/C][C]-1.2264[/C][C]0.111363[/C][/ROW]
[ROW][C]34[/C][C]0.093066[/C][C]0.9627[/C][C]0.168939[/C][/ROW]
[ROW][C]35[/C][C]-0.263403[/C][C]-2.7247[/C][C]0.00376[/C][/ROW]
[ROW][C]36[/C][C]0.501368[/C][C]5.1862[/C][C]1e-06[/C][/ROW]
[ROW][C]37[/C][C]-0.076549[/C][C]-0.7918[/C][C]0.215107[/C][/ROW]
[ROW][C]38[/C][C]0.098985[/C][C]1.0239[/C][C]0.154094[/C][/ROW]
[ROW][C]39[/C][C]-0.083705[/C][C]-0.8659[/C][C]0.194254[/C][/ROW]
[ROW][C]40[/C][C]-0.251284[/C][C]-2.5993[/C][C]0.00533[/C][/ROW]
[ROW][C]41[/C][C]0.190959[/C][C]1.9753[/C][C]0.025405[/C][/ROW]
[ROW][C]42[/C][C]-0.253929[/C][C]-2.6267[/C][C]0.004944[/C][/ROW]
[ROW][C]43[/C][C]0.27663[/C][C]2.8615[/C][C]0.002536[/C][/ROW]
[ROW][C]44[/C][C]-0.101626[/C][C]-1.0512[/C][C]0.14776[/C][/ROW]
[ROW][C]45[/C][C]-0.079109[/C][C]-0.8183[/C][C]0.2075[/C][/ROW]
[ROW][C]46[/C][C]0.085894[/C][C]0.8885[/C][C]0.188134[/C][/ROW]
[ROW][C]47[/C][C]-0.251043[/C][C]-2.5968[/C][C]0.005366[/C][/ROW]
[ROW][C]48[/C][C]0.394286[/C][C]4.0785[/C][C]4.4e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306896&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
1-0.34099-3.52720.00031
20.1611711.66720.049203
3-0.187224-1.93670.027712
4-0.339596-3.51280.000325
50.3709553.83720.000105
6-0.34395-3.55780.000279
70.4181114.3251.7e-05
8-0.287596-2.97490.001811
9-0.184079-1.90410.02979
100.1344191.39040.083641
11-0.313093-3.23878e-04
120.7895528.16720
13-0.255181-2.63960.00477
140.1906571.97220.025585
15-0.164844-1.70520.045533
16-0.350569-3.62630.000221
170.3377353.49360.000347
18-0.308274-3.18880.000937
190.3765073.89468.6e-05
20-0.224228-2.31940.011135
21-0.157817-1.63250.05276
220.1035141.07080.143344
23-0.273867-2.83290.002757
240.6024246.23150
25-0.138764-1.43540.077048
260.1768421.82930.035072
27-0.136543-1.41240.080366
28-0.308312-3.18920.000936
290.2472632.55770.005968
30-0.257776-2.66650.004428
310.3053563.15860.00103
32-0.153114-1.58380.058093
33-0.118564-1.22640.111363
340.0930660.96270.168939
35-0.263403-2.72470.00376
360.5013685.18621e-06
37-0.076549-0.79180.215107
380.0989851.02390.154094
39-0.083705-0.86590.194254
40-0.251284-2.59930.00533
410.1909591.97530.025405
42-0.253929-2.62670.004944
430.276632.86150.002536
44-0.101626-1.05120.14776
45-0.079109-0.81830.2075
460.0858940.88850.188134
47-0.251043-2.59680.005366
480.3942864.07854.4e-05






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.34099-3.52720.00031
20.0508040.52550.300154
3-0.13357-1.38170.084977
4-0.514821-5.32530
50.1798151.860.032814
6-0.220958-2.28560.012124
70.0767560.7940.214484
8-0.234549-2.42620.008465
9-0.434093-4.49039e-06
10-0.217-2.24470.013423
11-0.396937-4.10593.9e-05
120.4450364.60356e-06
130.1086521.12390.131784
140.0436250.45130.326357
15-0.004306-0.04450.48228
16-0.015357-0.15890.43704
170.0497710.51480.303866
180.0897240.92810.17772
19-0.104654-1.08250.140722
20-0.051051-0.52810.299269
21-0.005491-0.05680.477404
22-0.041122-0.42540.335712
230.039510.40870.34179
24-0.115361-1.19330.117694
250.0722250.74710.22832
260.0430090.44490.328649
27-0.018901-0.19550.422681
280.0667360.69030.245744
29-0.040516-0.41910.33799
30-0.017416-0.18020.428685
31-0.047433-0.49060.31234
32-0.044357-0.45880.323643
330.0145530.15050.44031
340.0806490.83420.203003
35-0.100601-1.04060.150197
360.1274541.31840.095094
370.0688680.71240.23889
38-0.162689-1.68290.047658
39-0.038458-0.39780.345782
400.0542420.56110.287955
410.0718620.74340.229449
42-0.132689-1.37260.086381
43-0.007348-0.0760.469775
440.00960.09930.46054
450.1240141.28280.101164
460.0532380.55070.291493
47-0.053355-0.55190.291083
48-0.098084-1.01460.156296

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.34099 & -3.5272 & 0.00031 \tabularnewline
2 & 0.050804 & 0.5255 & 0.300154 \tabularnewline
3 & -0.13357 & -1.3817 & 0.084977 \tabularnewline
4 & -0.514821 & -5.3253 & 0 \tabularnewline
5 & 0.179815 & 1.86 & 0.032814 \tabularnewline
6 & -0.220958 & -2.2856 & 0.012124 \tabularnewline
7 & 0.076756 & 0.794 & 0.214484 \tabularnewline
8 & -0.234549 & -2.4262 & 0.008465 \tabularnewline
9 & -0.434093 & -4.4903 & 9e-06 \tabularnewline
10 & -0.217 & -2.2447 & 0.013423 \tabularnewline
11 & -0.396937 & -4.1059 & 3.9e-05 \tabularnewline
12 & 0.445036 & 4.6035 & 6e-06 \tabularnewline
13 & 0.108652 & 1.1239 & 0.131784 \tabularnewline
14 & 0.043625 & 0.4513 & 0.326357 \tabularnewline
15 & -0.004306 & -0.0445 & 0.48228 \tabularnewline
16 & -0.015357 & -0.1589 & 0.43704 \tabularnewline
17 & 0.049771 & 0.5148 & 0.303866 \tabularnewline
18 & 0.089724 & 0.9281 & 0.17772 \tabularnewline
19 & -0.104654 & -1.0825 & 0.140722 \tabularnewline
20 & -0.051051 & -0.5281 & 0.299269 \tabularnewline
21 & -0.005491 & -0.0568 & 0.477404 \tabularnewline
22 & -0.041122 & -0.4254 & 0.335712 \tabularnewline
23 & 0.03951 & 0.4087 & 0.34179 \tabularnewline
24 & -0.115361 & -1.1933 & 0.117694 \tabularnewline
25 & 0.072225 & 0.7471 & 0.22832 \tabularnewline
26 & 0.043009 & 0.4449 & 0.328649 \tabularnewline
27 & -0.018901 & -0.1955 & 0.422681 \tabularnewline
28 & 0.066736 & 0.6903 & 0.245744 \tabularnewline
29 & -0.040516 & -0.4191 & 0.33799 \tabularnewline
30 & -0.017416 & -0.1802 & 0.428685 \tabularnewline
31 & -0.047433 & -0.4906 & 0.31234 \tabularnewline
32 & -0.044357 & -0.4588 & 0.323643 \tabularnewline
33 & 0.014553 & 0.1505 & 0.44031 \tabularnewline
34 & 0.080649 & 0.8342 & 0.203003 \tabularnewline
35 & -0.100601 & -1.0406 & 0.150197 \tabularnewline
36 & 0.127454 & 1.3184 & 0.095094 \tabularnewline
37 & 0.068868 & 0.7124 & 0.23889 \tabularnewline
38 & -0.162689 & -1.6829 & 0.047658 \tabularnewline
39 & -0.038458 & -0.3978 & 0.345782 \tabularnewline
40 & 0.054242 & 0.5611 & 0.287955 \tabularnewline
41 & 0.071862 & 0.7434 & 0.229449 \tabularnewline
42 & -0.132689 & -1.3726 & 0.086381 \tabularnewline
43 & -0.007348 & -0.076 & 0.469775 \tabularnewline
44 & 0.0096 & 0.0993 & 0.46054 \tabularnewline
45 & 0.124014 & 1.2828 & 0.101164 \tabularnewline
46 & 0.053238 & 0.5507 & 0.291493 \tabularnewline
47 & -0.053355 & -0.5519 & 0.291083 \tabularnewline
48 & -0.098084 & -1.0146 & 0.156296 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306896&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]-0.34099[/C][C]-3.5272[/C][C]0.00031[/C][/ROW]
[ROW][C]2[/C][C]0.050804[/C][C]0.5255[/C][C]0.300154[/C][/ROW]
[ROW][C]3[/C][C]-0.13357[/C][C]-1.3817[/C][C]0.084977[/C][/ROW]
[ROW][C]4[/C][C]-0.514821[/C][C]-5.3253[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.179815[/C][C]1.86[/C][C]0.032814[/C][/ROW]
[ROW][C]6[/C][C]-0.220958[/C][C]-2.2856[/C][C]0.012124[/C][/ROW]
[ROW][C]7[/C][C]0.076756[/C][C]0.794[/C][C]0.214484[/C][/ROW]
[ROW][C]8[/C][C]-0.234549[/C][C]-2.4262[/C][C]0.008465[/C][/ROW]
[ROW][C]9[/C][C]-0.434093[/C][C]-4.4903[/C][C]9e-06[/C][/ROW]
[ROW][C]10[/C][C]-0.217[/C][C]-2.2447[/C][C]0.013423[/C][/ROW]
[ROW][C]11[/C][C]-0.396937[/C][C]-4.1059[/C][C]3.9e-05[/C][/ROW]
[ROW][C]12[/C][C]0.445036[/C][C]4.6035[/C][C]6e-06[/C][/ROW]
[ROW][C]13[/C][C]0.108652[/C][C]1.1239[/C][C]0.131784[/C][/ROW]
[ROW][C]14[/C][C]0.043625[/C][C]0.4513[/C][C]0.326357[/C][/ROW]
[ROW][C]15[/C][C]-0.004306[/C][C]-0.0445[/C][C]0.48228[/C][/ROW]
[ROW][C]16[/C][C]-0.015357[/C][C]-0.1589[/C][C]0.43704[/C][/ROW]
[ROW][C]17[/C][C]0.049771[/C][C]0.5148[/C][C]0.303866[/C][/ROW]
[ROW][C]18[/C][C]0.089724[/C][C]0.9281[/C][C]0.17772[/C][/ROW]
[ROW][C]19[/C][C]-0.104654[/C][C]-1.0825[/C][C]0.140722[/C][/ROW]
[ROW][C]20[/C][C]-0.051051[/C][C]-0.5281[/C][C]0.299269[/C][/ROW]
[ROW][C]21[/C][C]-0.005491[/C][C]-0.0568[/C][C]0.477404[/C][/ROW]
[ROW][C]22[/C][C]-0.041122[/C][C]-0.4254[/C][C]0.335712[/C][/ROW]
[ROW][C]23[/C][C]0.03951[/C][C]0.4087[/C][C]0.34179[/C][/ROW]
[ROW][C]24[/C][C]-0.115361[/C][C]-1.1933[/C][C]0.117694[/C][/ROW]
[ROW][C]25[/C][C]0.072225[/C][C]0.7471[/C][C]0.22832[/C][/ROW]
[ROW][C]26[/C][C]0.043009[/C][C]0.4449[/C][C]0.328649[/C][/ROW]
[ROW][C]27[/C][C]-0.018901[/C][C]-0.1955[/C][C]0.422681[/C][/ROW]
[ROW][C]28[/C][C]0.066736[/C][C]0.6903[/C][C]0.245744[/C][/ROW]
[ROW][C]29[/C][C]-0.040516[/C][C]-0.4191[/C][C]0.33799[/C][/ROW]
[ROW][C]30[/C][C]-0.017416[/C][C]-0.1802[/C][C]0.428685[/C][/ROW]
[ROW][C]31[/C][C]-0.047433[/C][C]-0.4906[/C][C]0.31234[/C][/ROW]
[ROW][C]32[/C][C]-0.044357[/C][C]-0.4588[/C][C]0.323643[/C][/ROW]
[ROW][C]33[/C][C]0.014553[/C][C]0.1505[/C][C]0.44031[/C][/ROW]
[ROW][C]34[/C][C]0.080649[/C][C]0.8342[/C][C]0.203003[/C][/ROW]
[ROW][C]35[/C][C]-0.100601[/C][C]-1.0406[/C][C]0.150197[/C][/ROW]
[ROW][C]36[/C][C]0.127454[/C][C]1.3184[/C][C]0.095094[/C][/ROW]
[ROW][C]37[/C][C]0.068868[/C][C]0.7124[/C][C]0.23889[/C][/ROW]
[ROW][C]38[/C][C]-0.162689[/C][C]-1.6829[/C][C]0.047658[/C][/ROW]
[ROW][C]39[/C][C]-0.038458[/C][C]-0.3978[/C][C]0.345782[/C][/ROW]
[ROW][C]40[/C][C]0.054242[/C][C]0.5611[/C][C]0.287955[/C][/ROW]
[ROW][C]41[/C][C]0.071862[/C][C]0.7434[/C][C]0.229449[/C][/ROW]
[ROW][C]42[/C][C]-0.132689[/C][C]-1.3726[/C][C]0.086381[/C][/ROW]
[ROW][C]43[/C][C]-0.007348[/C][C]-0.076[/C][C]0.469775[/C][/ROW]
[ROW][C]44[/C][C]0.0096[/C][C]0.0993[/C][C]0.46054[/C][/ROW]
[ROW][C]45[/C][C]0.124014[/C][C]1.2828[/C][C]0.101164[/C][/ROW]
[ROW][C]46[/C][C]0.053238[/C][C]0.5507[/C][C]0.291493[/C][/ROW]
[ROW][C]47[/C][C]-0.053355[/C][C]-0.5519[/C][C]0.291083[/C][/ROW]
[ROW][C]48[/C][C]-0.098084[/C][C]-1.0146[/C][C]0.156296[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306896&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306896&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
1-0.34099-3.52720.00031
20.0508040.52550.300154
3-0.13357-1.38170.084977
4-0.514821-5.32530
50.1798151.860.032814
6-0.220958-2.28560.012124
70.0767560.7940.214484
8-0.234549-2.42620.008465
9-0.434093-4.49039e-06
10-0.217-2.24470.013423
11-0.396937-4.10593.9e-05
120.4450364.60356e-06
130.1086521.12390.131784
140.0436250.45130.326357
15-0.004306-0.04450.48228
16-0.015357-0.15890.43704
170.0497710.51480.303866
180.0897240.92810.17772
19-0.104654-1.08250.140722
20-0.051051-0.52810.299269
21-0.005491-0.05680.477404
22-0.041122-0.42540.335712
230.039510.40870.34179
24-0.115361-1.19330.117694
250.0722250.74710.22832
260.0430090.44490.328649
27-0.018901-0.19550.422681
280.0667360.69030.245744
29-0.040516-0.41910.33799
30-0.017416-0.18020.428685
31-0.047433-0.49060.31234
32-0.044357-0.45880.323643
330.0145530.15050.44031
340.0806490.83420.203003
35-0.100601-1.04060.150197
360.1274541.31840.095094
370.0688680.71240.23889
38-0.162689-1.68290.047658
39-0.038458-0.39780.345782
400.0542420.56110.287955
410.0718620.74340.229449
42-0.132689-1.37260.086381
43-0.007348-0.0760.469775
440.00960.09930.46054
450.1240141.28280.101164
460.0532380.55070.291493
47-0.053355-0.55190.291083
48-0.098084-1.01460.156296


Figures (Output of Computation)

Input Parameters & R Code

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):
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')