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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 computationSun, 07 Aug 2016 12:53:46 +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/Aug/07/t1470570865ulv66ocq3hpf8e6.htm/, Retrieved Thu, 02 May 2024 14:53:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296072, Retrieved Thu, 02 May 2024 14:53:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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] [gedifferentieerde...] [2016-08-07 11:53:46] [e98d32ae432942f69cb1b3451eac7d8c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 106 474.50 
 106 559.75 
 106 636.75 
 106 722.00 
 106 804.50 
 106 889.75 
 106 972.25 
 107 057.50 
 107 142.75 
 107 225.25 
 107 310.50 
 107 393.00 
 107 478.25 
 107 563.50 
 107 640.50 
 107 725.75 
 107 808.25 
 107 893.50 
 107 976.00 
 108 061.25 
 108 146.50 
 108 229.00 
 108 314.25 
 108 396.75 
 108 482.00 
 108 567.25 
 108 647.00 
 108 732.25 
 108 814.75 
 108 900.00 
 108 982.50 
 109 067.75 
 109 153.00 
 109 235.50 
 109 320.75 
 109 403.25 
 109 488.50 
 109 573.75 
 109 650.75 
 109 736.00 
 109 818.50 
 109 903.75 
 109 986.25 
 110 071.50 
 110 156.75 
 110 239.25 
 110 324.50 
 110 407.00 
 110 492.25 
 110 577.50 
 110 654.50 
 110 739.75 
 110 822.25 
 110 907.50 
 110 990.00 
 111 075.25 
 111 160.50 
 111 243.00 
 111 328.25 
 111 410.75 
 111 496.00 
 111 581.25 
 111 658.25 
 111 743.50 
 111 826.00 
 111 911.25 
 111 993.75 
 112 079.00 
 112 164.25 
 112 246.75 
 112 332.00 
 112 414.50 
 112 499.75 
 112 585.00 
 112 664.75 
 112 750.00 
 112 832.50 
 112 917.75 
 113 000.25 
 113 085.50 
 113 170.75 
 113 253.25 
 113 338.50 
 113 421.00 
 113 506.25 
 113 591.50 
 113 668.50 
 113 753.75 
 113 836.25 
 113 921.50 
 114 004.00 
 114 089.25 
 114 174.50 
 114 257.00 
 114 342.25 
 114 424.75 
 114 510.00 
 114 595.25 
 114 672.25 
 114 757.50 
 114 840.00 
 114 925.25 
 115 007.75 
 115 093.00 
 115 178.25 
 115 260.75 
 115 346.00 
 115 428.50 
 115 513.75 
 115 599.00 
 115 676.00 
 115 761.25 
 115 843.75 
 115 929.00 
 116 011.50 
 116 096.75 
 116 182.00 
 116 264.50 
 116 349.75 
 116 432.25

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296072&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296072&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296072&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.475855-5.1910
20.1327971.44860.075034
3-0.024396-0.26610.395299
4-0.107646-1.17430.121314
50.2087532.27720.012279
6-0.44668-4.87272e-06
70.2394372.61190.005081
8-0.139588-1.52270.065241
90.0113180.12350.450974
100.1023641.11670.133194
11-0.424547-4.63135e-06
120.8654439.44090
13-0.425553-4.64224e-06
140.1214791.32520.093825
15-0.02339-0.25520.399521
16-0.094316-1.02890.152815
170.1851112.01930.022851
18-0.396378-4.3241.6e-05
190.2157952.3540.010105
20-0.126258-1.37730.085501
210.0123240.13440.446642
220.0910460.99320.161314
23-0.374245-4.08254.1e-05
240.7555338.24190
25-0.375252-4.09353.9e-05
260.1031191.12490.131449
27-0.017103-0.18660.426159
28-0.088028-0.96030.169432
290.1667511.8190.03571
30-0.353119-3.85219.5e-05
310.1851112.01930.022851
32-0.107646-1.17430.121314
330.0062880.06860.472715
340.085010.92740.177811
35-0.330986-3.61060.000224
360.6755537.36940
37-0.331992-3.62160.000216
380.0918011.00140.159326
39-0.016097-0.17560.430456
40-0.074698-0.81490.20839
410.1431091.56110.060574
42-0.302817-3.30330.000631
430.1614691.76140.040368
44-0.094316-1.02890.152815
450.0072940.07960.468358
460.066650.72710.234307
47-0.287726-3.13870.00107
480.6078976.63140

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.475855 & -5.191 & 0 \tabularnewline
2 & 0.132797 & 1.4486 & 0.075034 \tabularnewline
3 & -0.024396 & -0.2661 & 0.395299 \tabularnewline
4 & -0.107646 & -1.1743 & 0.121314 \tabularnewline
5 & 0.208753 & 2.2772 & 0.012279 \tabularnewline
6 & -0.44668 & -4.8727 & 2e-06 \tabularnewline
7 & 0.239437 & 2.6119 & 0.005081 \tabularnewline
8 & -0.139588 & -1.5227 & 0.065241 \tabularnewline
9 & 0.011318 & 0.1235 & 0.450974 \tabularnewline
10 & 0.102364 & 1.1167 & 0.133194 \tabularnewline
11 & -0.424547 & -4.6313 & 5e-06 \tabularnewline
12 & 0.865443 & 9.4409 & 0 \tabularnewline
13 & -0.425553 & -4.6422 & 4e-06 \tabularnewline
14 & 0.121479 & 1.3252 & 0.093825 \tabularnewline
15 & -0.02339 & -0.2552 & 0.399521 \tabularnewline
16 & -0.094316 & -1.0289 & 0.152815 \tabularnewline
17 & 0.185111 & 2.0193 & 0.022851 \tabularnewline
18 & -0.396378 & -4.324 & 1.6e-05 \tabularnewline
19 & 0.215795 & 2.354 & 0.010105 \tabularnewline
20 & -0.126258 & -1.3773 & 0.085501 \tabularnewline
21 & 0.012324 & 0.1344 & 0.446642 \tabularnewline
22 & 0.091046 & 0.9932 & 0.161314 \tabularnewline
23 & -0.374245 & -4.0825 & 4.1e-05 \tabularnewline
24 & 0.755533 & 8.2419 & 0 \tabularnewline
25 & -0.375252 & -4.0935 & 3.9e-05 \tabularnewline
26 & 0.103119 & 1.1249 & 0.131449 \tabularnewline
27 & -0.017103 & -0.1866 & 0.426159 \tabularnewline
28 & -0.088028 & -0.9603 & 0.169432 \tabularnewline
29 & 0.166751 & 1.819 & 0.03571 \tabularnewline
30 & -0.353119 & -3.8521 & 9.5e-05 \tabularnewline
31 & 0.185111 & 2.0193 & 0.022851 \tabularnewline
32 & -0.107646 & -1.1743 & 0.121314 \tabularnewline
33 & 0.006288 & 0.0686 & 0.472715 \tabularnewline
34 & 0.08501 & 0.9274 & 0.177811 \tabularnewline
35 & -0.330986 & -3.6106 & 0.000224 \tabularnewline
36 & 0.675553 & 7.3694 & 0 \tabularnewline
37 & -0.331992 & -3.6216 & 0.000216 \tabularnewline
38 & 0.091801 & 1.0014 & 0.159326 \tabularnewline
39 & -0.016097 & -0.1756 & 0.430456 \tabularnewline
40 & -0.074698 & -0.8149 & 0.20839 \tabularnewline
41 & 0.143109 & 1.5611 & 0.060574 \tabularnewline
42 & -0.302817 & -3.3033 & 0.000631 \tabularnewline
43 & 0.161469 & 1.7614 & 0.040368 \tabularnewline
44 & -0.094316 & -1.0289 & 0.152815 \tabularnewline
45 & 0.007294 & 0.0796 & 0.468358 \tabularnewline
46 & 0.06665 & 0.7271 & 0.234307 \tabularnewline
47 & -0.287726 & -3.1387 & 0.00107 \tabularnewline
48 & 0.607897 & 6.6314 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296072&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]-0.475855[/C][C]-5.191[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.132797[/C][C]1.4486[/C][C]0.075034[/C][/ROW]
[ROW][C]3[/C][C]-0.024396[/C][C]-0.2661[/C][C]0.395299[/C][/ROW]
[ROW][C]4[/C][C]-0.107646[/C][C]-1.1743[/C][C]0.121314[/C][/ROW]
[ROW][C]5[/C][C]0.208753[/C][C]2.2772[/C][C]0.012279[/C][/ROW]
[ROW][C]6[/C][C]-0.44668[/C][C]-4.8727[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.239437[/C][C]2.6119[/C][C]0.005081[/C][/ROW]
[ROW][C]8[/C][C]-0.139588[/C][C]-1.5227[/C][C]0.065241[/C][/ROW]
[ROW][C]9[/C][C]0.011318[/C][C]0.1235[/C][C]0.450974[/C][/ROW]
[ROW][C]10[/C][C]0.102364[/C][C]1.1167[/C][C]0.133194[/C][/ROW]
[ROW][C]11[/C][C]-0.424547[/C][C]-4.6313[/C][C]5e-06[/C][/ROW]
[ROW][C]12[/C][C]0.865443[/C][C]9.4409[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.425553[/C][C]-4.6422[/C][C]4e-06[/C][/ROW]
[ROW][C]14[/C][C]0.121479[/C][C]1.3252[/C][C]0.093825[/C][/ROW]
[ROW][C]15[/C][C]-0.02339[/C][C]-0.2552[/C][C]0.399521[/C][/ROW]
[ROW][C]16[/C][C]-0.094316[/C][C]-1.0289[/C][C]0.152815[/C][/ROW]
[ROW][C]17[/C][C]0.185111[/C][C]2.0193[/C][C]0.022851[/C][/ROW]
[ROW][C]18[/C][C]-0.396378[/C][C]-4.324[/C][C]1.6e-05[/C][/ROW]
[ROW][C]19[/C][C]0.215795[/C][C]2.354[/C][C]0.010105[/C][/ROW]
[ROW][C]20[/C][C]-0.126258[/C][C]-1.3773[/C][C]0.085501[/C][/ROW]
[ROW][C]21[/C][C]0.012324[/C][C]0.1344[/C][C]0.446642[/C][/ROW]
[ROW][C]22[/C][C]0.091046[/C][C]0.9932[/C][C]0.161314[/C][/ROW]
[ROW][C]23[/C][C]-0.374245[/C][C]-4.0825[/C][C]4.1e-05[/C][/ROW]
[ROW][C]24[/C][C]0.755533[/C][C]8.2419[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.375252[/C][C]-4.0935[/C][C]3.9e-05[/C][/ROW]
[ROW][C]26[/C][C]0.103119[/C][C]1.1249[/C][C]0.131449[/C][/ROW]
[ROW][C]27[/C][C]-0.017103[/C][C]-0.1866[/C][C]0.426159[/C][/ROW]
[ROW][C]28[/C][C]-0.088028[/C][C]-0.9603[/C][C]0.169432[/C][/ROW]
[ROW][C]29[/C][C]0.166751[/C][C]1.819[/C][C]0.03571[/C][/ROW]
[ROW][C]30[/C][C]-0.353119[/C][C]-3.8521[/C][C]9.5e-05[/C][/ROW]
[ROW][C]31[/C][C]0.185111[/C][C]2.0193[/C][C]0.022851[/C][/ROW]
[ROW][C]32[/C][C]-0.107646[/C][C]-1.1743[/C][C]0.121314[/C][/ROW]
[ROW][C]33[/C][C]0.006288[/C][C]0.0686[/C][C]0.472715[/C][/ROW]
[ROW][C]34[/C][C]0.08501[/C][C]0.9274[/C][C]0.177811[/C][/ROW]
[ROW][C]35[/C][C]-0.330986[/C][C]-3.6106[/C][C]0.000224[/C][/ROW]
[ROW][C]36[/C][C]0.675553[/C][C]7.3694[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.331992[/C][C]-3.6216[/C][C]0.000216[/C][/ROW]
[ROW][C]38[/C][C]0.091801[/C][C]1.0014[/C][C]0.159326[/C][/ROW]
[ROW][C]39[/C][C]-0.016097[/C][C]-0.1756[/C][C]0.430456[/C][/ROW]
[ROW][C]40[/C][C]-0.074698[/C][C]-0.8149[/C][C]0.20839[/C][/ROW]
[ROW][C]41[/C][C]0.143109[/C][C]1.5611[/C][C]0.060574[/C][/ROW]
[ROW][C]42[/C][C]-0.302817[/C][C]-3.3033[/C][C]0.000631[/C][/ROW]
[ROW][C]43[/C][C]0.161469[/C][C]1.7614[/C][C]0.040368[/C][/ROW]
[ROW][C]44[/C][C]-0.094316[/C][C]-1.0289[/C][C]0.152815[/C][/ROW]
[ROW][C]45[/C][C]0.007294[/C][C]0.0796[/C][C]0.468358[/C][/ROW]
[ROW][C]46[/C][C]0.06665[/C][C]0.7271[/C][C]0.234307[/C][/ROW]
[ROW][C]47[/C][C]-0.287726[/C][C]-3.1387[/C][C]0.00107[/C][/ROW]
[ROW][C]48[/C][C]0.607897[/C][C]6.6314[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296072&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296072&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
1-0.475855-5.1910
20.1327971.44860.075034
3-0.024396-0.26610.395299
4-0.107646-1.17430.121314
50.2087532.27720.012279
6-0.44668-4.87272e-06
70.2394372.61190.005081
8-0.139588-1.52270.065241
90.0113180.12350.450974
100.1023641.11670.133194
11-0.424547-4.63135e-06
120.8654439.44090
13-0.425553-4.64224e-06
140.1214791.32520.093825
15-0.02339-0.25520.399521
16-0.094316-1.02890.152815
170.1851112.01930.022851
18-0.396378-4.3241.6e-05
190.2157952.3540.010105
20-0.126258-1.37730.085501
210.0123240.13440.446642
220.0910460.99320.161314
23-0.374245-4.08254.1e-05
240.7555338.24190
25-0.375252-4.09353.9e-05
260.1031191.12490.131449
27-0.017103-0.18660.426159
28-0.088028-0.96030.169432
290.1667511.8190.03571
30-0.353119-3.85219.5e-05
310.1851112.01930.022851
32-0.107646-1.17430.121314
330.0062880.06860.472715
340.085010.92740.177811
35-0.330986-3.61060.000224
360.6755537.36940
37-0.331992-3.62160.000216
380.0918011.00140.159326
39-0.016097-0.17560.430456
40-0.074698-0.81490.20839
410.1431091.56110.060574
42-0.302817-3.30330.000631
430.1614691.76140.040368
44-0.094316-1.02890.152815
450.0072940.07960.468358
460.066650.72710.234307
47-0.287726-3.13870.00107
480.6078976.63140






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.475855-5.1910
2-0.121052-1.32050.094597
3-0.014639-0.15970.436698
4-0.145076-1.58260.058084
50.1213491.32380.09406
6-0.389535-4.24932.1e-05
7-0.201462-2.19770.014954
8-0.189668-2.0690.020354
9-0.194019-2.11650.018193
10-0.097177-1.06010.145627
11-0.655506-7.15070
120.5818456.34720
130.2371092.58650.005449
14-0.088444-0.96480.168297
150.012130.13230.447474
16-0.051865-0.56580.286302
17-0.091783-1.00120.159373
180.1437151.56770.059798
19-0.110084-1.20090.116093
20-0.005202-0.05670.477421
21-0.042666-0.46540.321236
22-0.085712-0.9350.17584
230.0193690.21130.416511
240.0307020.33490.369138
25-0.029523-0.32210.373986
26-0.009022-0.09840.460884
27-0.059446-0.64850.258963
28-0.042154-0.45980.323234
29-0.016883-0.18420.427095
30-0.03517-0.38370.350957
31-0.089088-0.97180.166551
32-0.055579-0.60630.272736
33-0.083825-0.91440.181171
34-0.068441-0.74660.228386
35-0.049152-0.53620.296416
360.008760.09560.462016
37-0.022886-0.24970.401641
38-0.018155-0.1980.421673
39-0.065697-0.71670.237491
40-0.018996-0.20720.418097
41-0.049896-0.54430.293625
420.0137880.15040.440349
430.0159880.17440.43092
44-0.025943-0.2830.38883
45-0.009204-0.10040.460097
46-0.052035-0.56760.285678
47-0.042913-0.46810.320275
480.0653720.71310.238581

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.475855 & -5.191 & 0 \tabularnewline
2 & -0.121052 & -1.3205 & 0.094597 \tabularnewline
3 & -0.014639 & -0.1597 & 0.436698 \tabularnewline
4 & -0.145076 & -1.5826 & 0.058084 \tabularnewline
5 & 0.121349 & 1.3238 & 0.09406 \tabularnewline
6 & -0.389535 & -4.2493 & 2.1e-05 \tabularnewline
7 & -0.201462 & -2.1977 & 0.014954 \tabularnewline
8 & -0.189668 & -2.069 & 0.020354 \tabularnewline
9 & -0.194019 & -2.1165 & 0.018193 \tabularnewline
10 & -0.097177 & -1.0601 & 0.145627 \tabularnewline
11 & -0.655506 & -7.1507 & 0 \tabularnewline
12 & 0.581845 & 6.3472 & 0 \tabularnewline
13 & 0.237109 & 2.5865 & 0.005449 \tabularnewline
14 & -0.088444 & -0.9648 & 0.168297 \tabularnewline
15 & 0.01213 & 0.1323 & 0.447474 \tabularnewline
16 & -0.051865 & -0.5658 & 0.286302 \tabularnewline
17 & -0.091783 & -1.0012 & 0.159373 \tabularnewline
18 & 0.143715 & 1.5677 & 0.059798 \tabularnewline
19 & -0.110084 & -1.2009 & 0.116093 \tabularnewline
20 & -0.005202 & -0.0567 & 0.477421 \tabularnewline
21 & -0.042666 & -0.4654 & 0.321236 \tabularnewline
22 & -0.085712 & -0.935 & 0.17584 \tabularnewline
23 & 0.019369 & 0.2113 & 0.416511 \tabularnewline
24 & 0.030702 & 0.3349 & 0.369138 \tabularnewline
25 & -0.029523 & -0.3221 & 0.373986 \tabularnewline
26 & -0.009022 & -0.0984 & 0.460884 \tabularnewline
27 & -0.059446 & -0.6485 & 0.258963 \tabularnewline
28 & -0.042154 & -0.4598 & 0.323234 \tabularnewline
29 & -0.016883 & -0.1842 & 0.427095 \tabularnewline
30 & -0.03517 & -0.3837 & 0.350957 \tabularnewline
31 & -0.089088 & -0.9718 & 0.166551 \tabularnewline
32 & -0.055579 & -0.6063 & 0.272736 \tabularnewline
33 & -0.083825 & -0.9144 & 0.181171 \tabularnewline
34 & -0.068441 & -0.7466 & 0.228386 \tabularnewline
35 & -0.049152 & -0.5362 & 0.296416 \tabularnewline
36 & 0.00876 & 0.0956 & 0.462016 \tabularnewline
37 & -0.022886 & -0.2497 & 0.401641 \tabularnewline
38 & -0.018155 & -0.198 & 0.421673 \tabularnewline
39 & -0.065697 & -0.7167 & 0.237491 \tabularnewline
40 & -0.018996 & -0.2072 & 0.418097 \tabularnewline
41 & -0.049896 & -0.5443 & 0.293625 \tabularnewline
42 & 0.013788 & 0.1504 & 0.440349 \tabularnewline
43 & 0.015988 & 0.1744 & 0.43092 \tabularnewline
44 & -0.025943 & -0.283 & 0.38883 \tabularnewline
45 & -0.009204 & -0.1004 & 0.460097 \tabularnewline
46 & -0.052035 & -0.5676 & 0.285678 \tabularnewline
47 & -0.042913 & -0.4681 & 0.320275 \tabularnewline
48 & 0.065372 & 0.7131 & 0.238581 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296072&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]-0.475855[/C][C]-5.191[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.121052[/C][C]-1.3205[/C][C]0.094597[/C][/ROW]
[ROW][C]3[/C][C]-0.014639[/C][C]-0.1597[/C][C]0.436698[/C][/ROW]
[ROW][C]4[/C][C]-0.145076[/C][C]-1.5826[/C][C]0.058084[/C][/ROW]
[ROW][C]5[/C][C]0.121349[/C][C]1.3238[/C][C]0.09406[/C][/ROW]
[ROW][C]6[/C][C]-0.389535[/C][C]-4.2493[/C][C]2.1e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.201462[/C][C]-2.1977[/C][C]0.014954[/C][/ROW]
[ROW][C]8[/C][C]-0.189668[/C][C]-2.069[/C][C]0.020354[/C][/ROW]
[ROW][C]9[/C][C]-0.194019[/C][C]-2.1165[/C][C]0.018193[/C][/ROW]
[ROW][C]10[/C][C]-0.097177[/C][C]-1.0601[/C][C]0.145627[/C][/ROW]
[ROW][C]11[/C][C]-0.655506[/C][C]-7.1507[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.581845[/C][C]6.3472[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.237109[/C][C]2.5865[/C][C]0.005449[/C][/ROW]
[ROW][C]14[/C][C]-0.088444[/C][C]-0.9648[/C][C]0.168297[/C][/ROW]
[ROW][C]15[/C][C]0.01213[/C][C]0.1323[/C][C]0.447474[/C][/ROW]
[ROW][C]16[/C][C]-0.051865[/C][C]-0.5658[/C][C]0.286302[/C][/ROW]
[ROW][C]17[/C][C]-0.091783[/C][C]-1.0012[/C][C]0.159373[/C][/ROW]
[ROW][C]18[/C][C]0.143715[/C][C]1.5677[/C][C]0.059798[/C][/ROW]
[ROW][C]19[/C][C]-0.110084[/C][C]-1.2009[/C][C]0.116093[/C][/ROW]
[ROW][C]20[/C][C]-0.005202[/C][C]-0.0567[/C][C]0.477421[/C][/ROW]
[ROW][C]21[/C][C]-0.042666[/C][C]-0.4654[/C][C]0.321236[/C][/ROW]
[ROW][C]22[/C][C]-0.085712[/C][C]-0.935[/C][C]0.17584[/C][/ROW]
[ROW][C]23[/C][C]0.019369[/C][C]0.2113[/C][C]0.416511[/C][/ROW]
[ROW][C]24[/C][C]0.030702[/C][C]0.3349[/C][C]0.369138[/C][/ROW]
[ROW][C]25[/C][C]-0.029523[/C][C]-0.3221[/C][C]0.373986[/C][/ROW]
[ROW][C]26[/C][C]-0.009022[/C][C]-0.0984[/C][C]0.460884[/C][/ROW]
[ROW][C]27[/C][C]-0.059446[/C][C]-0.6485[/C][C]0.258963[/C][/ROW]
[ROW][C]28[/C][C]-0.042154[/C][C]-0.4598[/C][C]0.323234[/C][/ROW]
[ROW][C]29[/C][C]-0.016883[/C][C]-0.1842[/C][C]0.427095[/C][/ROW]
[ROW][C]30[/C][C]-0.03517[/C][C]-0.3837[/C][C]0.350957[/C][/ROW]
[ROW][C]31[/C][C]-0.089088[/C][C]-0.9718[/C][C]0.166551[/C][/ROW]
[ROW][C]32[/C][C]-0.055579[/C][C]-0.6063[/C][C]0.272736[/C][/ROW]
[ROW][C]33[/C][C]-0.083825[/C][C]-0.9144[/C][C]0.181171[/C][/ROW]
[ROW][C]34[/C][C]-0.068441[/C][C]-0.7466[/C][C]0.228386[/C][/ROW]
[ROW][C]35[/C][C]-0.049152[/C][C]-0.5362[/C][C]0.296416[/C][/ROW]
[ROW][C]36[/C][C]0.00876[/C][C]0.0956[/C][C]0.462016[/C][/ROW]
[ROW][C]37[/C][C]-0.022886[/C][C]-0.2497[/C][C]0.401641[/C][/ROW]
[ROW][C]38[/C][C]-0.018155[/C][C]-0.198[/C][C]0.421673[/C][/ROW]
[ROW][C]39[/C][C]-0.065697[/C][C]-0.7167[/C][C]0.237491[/C][/ROW]
[ROW][C]40[/C][C]-0.018996[/C][C]-0.2072[/C][C]0.418097[/C][/ROW]
[ROW][C]41[/C][C]-0.049896[/C][C]-0.5443[/C][C]0.293625[/C][/ROW]
[ROW][C]42[/C][C]0.013788[/C][C]0.1504[/C][C]0.440349[/C][/ROW]
[ROW][C]43[/C][C]0.015988[/C][C]0.1744[/C][C]0.43092[/C][/ROW]
[ROW][C]44[/C][C]-0.025943[/C][C]-0.283[/C][C]0.38883[/C][/ROW]
[ROW][C]45[/C][C]-0.009204[/C][C]-0.1004[/C][C]0.460097[/C][/ROW]
[ROW][C]46[/C][C]-0.052035[/C][C]-0.5676[/C][C]0.285678[/C][/ROW]
[ROW][C]47[/C][C]-0.042913[/C][C]-0.4681[/C][C]0.320275[/C][/ROW]
[ROW][C]48[/C][C]0.065372[/C][C]0.7131[/C][C]0.238581[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296072&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296072&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
1-0.475855-5.1910
2-0.121052-1.32050.094597
3-0.014639-0.15970.436698
4-0.145076-1.58260.058084
50.1213491.32380.09406
6-0.389535-4.24932.1e-05
7-0.201462-2.19770.014954
8-0.189668-2.0690.020354
9-0.194019-2.11650.018193
10-0.097177-1.06010.145627
11-0.655506-7.15070
120.5818456.34720
130.2371092.58650.005449
14-0.088444-0.96480.168297
150.012130.13230.447474
16-0.051865-0.56580.286302
17-0.091783-1.00120.159373
180.1437151.56770.059798
19-0.110084-1.20090.116093
20-0.005202-0.05670.477421
21-0.042666-0.46540.321236
22-0.085712-0.9350.17584
230.0193690.21130.416511
240.0307020.33490.369138
25-0.029523-0.32210.373986
26-0.009022-0.09840.460884
27-0.059446-0.64850.258963
28-0.042154-0.45980.323234
29-0.016883-0.18420.427095
30-0.03517-0.38370.350957
31-0.089088-0.97180.166551
32-0.055579-0.60630.272736
33-0.083825-0.91440.181171
34-0.068441-0.74660.228386
35-0.049152-0.53620.296416
360.008760.09560.462016
37-0.022886-0.24970.401641
38-0.018155-0.1980.421673
39-0.065697-0.71670.237491
40-0.018996-0.20720.418097
41-0.049896-0.54430.293625
420.0137880.15040.440349
430.0159880.17440.43092
44-0.025943-0.2830.38883
45-0.009204-0.10040.460097
46-0.052035-0.56760.285678
47-0.042913-0.46810.320275
480.0653720.71310.238581


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,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 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,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,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')