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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 computationSun, 06 Dec 2009 15:34:33 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/06/t12601390200cdo8s4ns3fuq1k.htm/, Retrieved Mon, 06 May 2024 00:25:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64519, Retrieved Mon, 06 May 2024 00:25:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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...] [2007-12-17 14:32:46] [0089dec2868056b990fdbd23bf9edb23]
- RMPD    [(Partial) Autocorrelation Function] [PAPER] [2009-12-06 22:34:33] [2d9a0b3c2f25bb8f387fafb994d0d852] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.00
100.83
101.51
102.16
102.39
102.54
102.85
103.47
103.57
103.69
103.50
103.47
103.45
103.48
103.93
103.89
104.40
104.79
104.77
105.13
105.26
104.96
104.75
105.01
105.15
105.20
105.77
105.78
106.26
106.13
106.12
106.57
106.44
106.54
107.10
108.10
108.40
108.84
109.62
110.42
110.67
111.66
112.28
112.87
112.18
112.36
112.16
111.49
111.25
111.36
111.74
111.10
111.33
111.25
111.04
110.97
111.31
111.02
111.07
111.36

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64519&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64519&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64519&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
016.85570
10.2914321.9980.025763
20.2809171.92590.030091
30.2811311.92730.029997
40.2855151.95740.028127
5-0.150312-1.03050.845973
60.0289150.19820.42186
70.1620731.11110.136086
8-0.069075-0.47360.680994
9-0.226958-1.55590.936785
10-0.20854-1.42970.920289
11-0.094425-0.64730.739721
12-0.476924-3.26960.998991
13-0.270814-1.85660.965179
14-0.136863-0.93830.823553
15-0.027435-0.18810.574191
16-0.170478-1.16870.875798
170.0454940.31190.378252
180.0155820.10680.457692
19-0.034943-0.23960.594144
20-0.145426-0.9970.838062
21-0.053477-0.36660.642227
220.0204870.14050.444452
23-0.038762-0.26570.6042
24-0.053827-0.3690.643114
250.0967550.66330.255183
26-0.012151-0.08330.533019
27-0.116566-0.79910.785885
28-0.067569-0.46320.677332
29-0.014809-0.10150.540219
30-0.072279-0.49550.688729
31-0.021713-0.14890.558848
320.0945060.64790.260101
330.1106570.75860.225932
340.0734320.50340.308508
350.023880.16370.435329
360.1040420.71330.239602
37-0.020106-0.13780.554523
380.0365030.25030.401741
390.0522550.35820.360883
400.0717360.49180.312576
41-0.020721-0.14210.556178
420.0565470.38770.350006
43-0.03444-0.23610.592812
44-0.024184-0.16580.565486
45-0.023843-0.16350.564571
46-0.045216-0.310.62103
47NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 6.8557 & 0 \tabularnewline
1 & 0.291432 & 1.998 & 0.025763 \tabularnewline
2 & 0.280917 & 1.9259 & 0.030091 \tabularnewline
3 & 0.281131 & 1.9273 & 0.029997 \tabularnewline
4 & 0.285515 & 1.9574 & 0.028127 \tabularnewline
5 & -0.150312 & -1.0305 & 0.845973 \tabularnewline
6 & 0.028915 & 0.1982 & 0.42186 \tabularnewline
7 & 0.162073 & 1.1111 & 0.136086 \tabularnewline
8 & -0.069075 & -0.4736 & 0.680994 \tabularnewline
9 & -0.226958 & -1.5559 & 0.936785 \tabularnewline
10 & -0.20854 & -1.4297 & 0.920289 \tabularnewline
11 & -0.094425 & -0.6473 & 0.739721 \tabularnewline
12 & -0.476924 & -3.2696 & 0.998991 \tabularnewline
13 & -0.270814 & -1.8566 & 0.965179 \tabularnewline
14 & -0.136863 & -0.9383 & 0.823553 \tabularnewline
15 & -0.027435 & -0.1881 & 0.574191 \tabularnewline
16 & -0.170478 & -1.1687 & 0.875798 \tabularnewline
17 & 0.045494 & 0.3119 & 0.378252 \tabularnewline
18 & 0.015582 & 0.1068 & 0.457692 \tabularnewline
19 & -0.034943 & -0.2396 & 0.594144 \tabularnewline
20 & -0.145426 & -0.997 & 0.838062 \tabularnewline
21 & -0.053477 & -0.3666 & 0.642227 \tabularnewline
22 & 0.020487 & 0.1405 & 0.444452 \tabularnewline
23 & -0.038762 & -0.2657 & 0.6042 \tabularnewline
24 & -0.053827 & -0.369 & 0.643114 \tabularnewline
25 & 0.096755 & 0.6633 & 0.255183 \tabularnewline
26 & -0.012151 & -0.0833 & 0.533019 \tabularnewline
27 & -0.116566 & -0.7991 & 0.785885 \tabularnewline
28 & -0.067569 & -0.4632 & 0.677332 \tabularnewline
29 & -0.014809 & -0.1015 & 0.540219 \tabularnewline
30 & -0.072279 & -0.4955 & 0.688729 \tabularnewline
31 & -0.021713 & -0.1489 & 0.558848 \tabularnewline
32 & 0.094506 & 0.6479 & 0.260101 \tabularnewline
33 & 0.110657 & 0.7586 & 0.225932 \tabularnewline
34 & 0.073432 & 0.5034 & 0.308508 \tabularnewline
35 & 0.02388 & 0.1637 & 0.435329 \tabularnewline
36 & 0.104042 & 0.7133 & 0.239602 \tabularnewline
37 & -0.020106 & -0.1378 & 0.554523 \tabularnewline
38 & 0.036503 & 0.2503 & 0.401741 \tabularnewline
39 & 0.052255 & 0.3582 & 0.360883 \tabularnewline
40 & 0.071736 & 0.4918 & 0.312576 \tabularnewline
41 & -0.020721 & -0.1421 & 0.556178 \tabularnewline
42 & 0.056547 & 0.3877 & 0.350006 \tabularnewline
43 & -0.03444 & -0.2361 & 0.592812 \tabularnewline
44 & -0.024184 & -0.1658 & 0.565486 \tabularnewline
45 & -0.023843 & -0.1635 & 0.564571 \tabularnewline
46 & -0.045216 & -0.31 & 0.62103 \tabularnewline
47 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64519&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]0[/C][C]1[/C][C]6.8557[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.291432[/C][C]1.998[/C][C]0.025763[/C][/ROW]
[ROW][C]2[/C][C]0.280917[/C][C]1.9259[/C][C]0.030091[/C][/ROW]
[ROW][C]3[/C][C]0.281131[/C][C]1.9273[/C][C]0.029997[/C][/ROW]
[ROW][C]4[/C][C]0.285515[/C][C]1.9574[/C][C]0.028127[/C][/ROW]
[ROW][C]5[/C][C]-0.150312[/C][C]-1.0305[/C][C]0.845973[/C][/ROW]
[ROW][C]6[/C][C]0.028915[/C][C]0.1982[/C][C]0.42186[/C][/ROW]
[ROW][C]7[/C][C]0.162073[/C][C]1.1111[/C][C]0.136086[/C][/ROW]
[ROW][C]8[/C][C]-0.069075[/C][C]-0.4736[/C][C]0.680994[/C][/ROW]
[ROW][C]9[/C][C]-0.226958[/C][C]-1.5559[/C][C]0.936785[/C][/ROW]
[ROW][C]10[/C][C]-0.20854[/C][C]-1.4297[/C][C]0.920289[/C][/ROW]
[ROW][C]11[/C][C]-0.094425[/C][C]-0.6473[/C][C]0.739721[/C][/ROW]
[ROW][C]12[/C][C]-0.476924[/C][C]-3.2696[/C][C]0.998991[/C][/ROW]
[ROW][C]13[/C][C]-0.270814[/C][C]-1.8566[/C][C]0.965179[/C][/ROW]
[ROW][C]14[/C][C]-0.136863[/C][C]-0.9383[/C][C]0.823553[/C][/ROW]
[ROW][C]15[/C][C]-0.027435[/C][C]-0.1881[/C][C]0.574191[/C][/ROW]
[ROW][C]16[/C][C]-0.170478[/C][C]-1.1687[/C][C]0.875798[/C][/ROW]
[ROW][C]17[/C][C]0.045494[/C][C]0.3119[/C][C]0.378252[/C][/ROW]
[ROW][C]18[/C][C]0.015582[/C][C]0.1068[/C][C]0.457692[/C][/ROW]
[ROW][C]19[/C][C]-0.034943[/C][C]-0.2396[/C][C]0.594144[/C][/ROW]
[ROW][C]20[/C][C]-0.145426[/C][C]-0.997[/C][C]0.838062[/C][/ROW]
[ROW][C]21[/C][C]-0.053477[/C][C]-0.3666[/C][C]0.642227[/C][/ROW]
[ROW][C]22[/C][C]0.020487[/C][C]0.1405[/C][C]0.444452[/C][/ROW]
[ROW][C]23[/C][C]-0.038762[/C][C]-0.2657[/C][C]0.6042[/C][/ROW]
[ROW][C]24[/C][C]-0.053827[/C][C]-0.369[/C][C]0.643114[/C][/ROW]
[ROW][C]25[/C][C]0.096755[/C][C]0.6633[/C][C]0.255183[/C][/ROW]
[ROW][C]26[/C][C]-0.012151[/C][C]-0.0833[/C][C]0.533019[/C][/ROW]
[ROW][C]27[/C][C]-0.116566[/C][C]-0.7991[/C][C]0.785885[/C][/ROW]
[ROW][C]28[/C][C]-0.067569[/C][C]-0.4632[/C][C]0.677332[/C][/ROW]
[ROW][C]29[/C][C]-0.014809[/C][C]-0.1015[/C][C]0.540219[/C][/ROW]
[ROW][C]30[/C][C]-0.072279[/C][C]-0.4955[/C][C]0.688729[/C][/ROW]
[ROW][C]31[/C][C]-0.021713[/C][C]-0.1489[/C][C]0.558848[/C][/ROW]
[ROW][C]32[/C][C]0.094506[/C][C]0.6479[/C][C]0.260101[/C][/ROW]
[ROW][C]33[/C][C]0.110657[/C][C]0.7586[/C][C]0.225932[/C][/ROW]
[ROW][C]34[/C][C]0.073432[/C][C]0.5034[/C][C]0.308508[/C][/ROW]
[ROW][C]35[/C][C]0.02388[/C][C]0.1637[/C][C]0.435329[/C][/ROW]
[ROW][C]36[/C][C]0.104042[/C][C]0.7133[/C][C]0.239602[/C][/ROW]
[ROW][C]37[/C][C]-0.020106[/C][C]-0.1378[/C][C]0.554523[/C][/ROW]
[ROW][C]38[/C][C]0.036503[/C][C]0.2503[/C][C]0.401741[/C][/ROW]
[ROW][C]39[/C][C]0.052255[/C][C]0.3582[/C][C]0.360883[/C][/ROW]
[ROW][C]40[/C][C]0.071736[/C][C]0.4918[/C][C]0.312576[/C][/ROW]
[ROW][C]41[/C][C]-0.020721[/C][C]-0.1421[/C][C]0.556178[/C][/ROW]
[ROW][C]42[/C][C]0.056547[/C][C]0.3877[/C][C]0.350006[/C][/ROW]
[ROW][C]43[/C][C]-0.03444[/C][C]-0.2361[/C][C]0.592812[/C][/ROW]
[ROW][C]44[/C][C]-0.024184[/C][C]-0.1658[/C][C]0.565486[/C][/ROW]
[ROW][C]45[/C][C]-0.023843[/C][C]-0.1635[/C][C]0.564571[/C][/ROW]
[ROW][C]46[/C][C]-0.045216[/C][C]-0.31[/C][C]0.62103[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64519&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64519&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
016.85570
10.2914321.9980.025763
20.2809171.92590.030091
30.2811311.92730.029997
40.2855151.95740.028127
5-0.150312-1.03050.845973
60.0289150.19820.42186
70.1620731.11110.136086
8-0.069075-0.47360.680994
9-0.226958-1.55590.936785
10-0.20854-1.42970.920289
11-0.094425-0.64730.739721
12-0.476924-3.26960.998991
13-0.270814-1.85660.965179
14-0.136863-0.93830.823553
15-0.027435-0.18810.574191
16-0.170478-1.16870.875798
170.0454940.31190.378252
180.0155820.10680.457692
19-0.034943-0.23960.594144
20-0.145426-0.9970.838062
21-0.053477-0.36660.642227
220.0204870.14050.444452
23-0.038762-0.26570.6042
24-0.053827-0.3690.643114
250.0967550.66330.255183
26-0.012151-0.08330.533019
27-0.116566-0.79910.785885
28-0.067569-0.46320.677332
29-0.014809-0.10150.540219
30-0.072279-0.49550.688729
31-0.021713-0.14890.558848
320.0945060.64790.260101
330.1106570.75860.225932
340.0734320.50340.308508
350.023880.16370.435329
360.1040420.71330.239602
37-0.020106-0.13780.554523
380.0365030.25030.401741
390.0522550.35820.360883
400.0717360.49180.312576
41-0.020721-0.14210.556178
420.0565470.38770.350006
43-0.03444-0.23610.592812
44-0.024184-0.16580.565486
45-0.023843-0.16350.564571
46-0.045216-0.310.62103
47NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.2914321.9980.025763
10.2141741.46830.074341
20.1768191.21220.115745
30.1554251.06550.146038
4-0.393645-2.69870.99518
5-0.000477-0.00330.501297
60.2533241.73670.044495
7-0.110833-0.75980.774424
8-0.23173-1.58870.940579
9-0.365541-2.5060.992135
100.0966140.66240.255491
11-0.155254-1.06440.853701
12-0.002103-0.01440.505722
130.0335870.23030.409444
140.1318440.90390.185335
150.1564741.07270.144434
16-0.077353-0.53030.700802
17-0.182676-1.25240.891684
180.0081790.05610.477762
19-0.12777-0.87590.807244
20-0.221171-1.51630.931926
21-0.136365-0.93490.822683
220.0707490.4850.314955
23-0.074064-0.50780.693
240.1024370.70230.242986
25-0.124876-0.85610.801859
260.0576130.3950.347325
270.090140.6180.26979
28-0.071906-0.4930.687833
29-0.143591-0.98440.835023
30-0.023203-0.15910.562854
310.0189950.13020.448472
32-0.046748-0.32050.624991
33-0.0628-0.43050.665613
34-0.05324-0.3650.641623
35-0.005243-0.03590.514261
360.0033590.0230.490864
37-0.007778-0.05330.521148
380.022470.1540.439118
39-0.101117-0.69320.75421
40-0.11436-0.7840.781516
41-0.021955-0.15050.559499
420.0136990.09390.462788
430.0639510.43840.331544
44-0.001066-0.00730.502899
45-0.076271-0.52290.698246
46NANANA
47NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.291432 & 1.998 & 0.025763 \tabularnewline
1 & 0.214174 & 1.4683 & 0.074341 \tabularnewline
2 & 0.176819 & 1.2122 & 0.115745 \tabularnewline
3 & 0.155425 & 1.0655 & 0.146038 \tabularnewline
4 & -0.393645 & -2.6987 & 0.99518 \tabularnewline
5 & -0.000477 & -0.0033 & 0.501297 \tabularnewline
6 & 0.253324 & 1.7367 & 0.044495 \tabularnewline
7 & -0.110833 & -0.7598 & 0.774424 \tabularnewline
8 & -0.23173 & -1.5887 & 0.940579 \tabularnewline
9 & -0.365541 & -2.506 & 0.992135 \tabularnewline
10 & 0.096614 & 0.6624 & 0.255491 \tabularnewline
11 & -0.155254 & -1.0644 & 0.853701 \tabularnewline
12 & -0.002103 & -0.0144 & 0.505722 \tabularnewline
13 & 0.033587 & 0.2303 & 0.409444 \tabularnewline
14 & 0.131844 & 0.9039 & 0.185335 \tabularnewline
15 & 0.156474 & 1.0727 & 0.144434 \tabularnewline
16 & -0.077353 & -0.5303 & 0.700802 \tabularnewline
17 & -0.182676 & -1.2524 & 0.891684 \tabularnewline
18 & 0.008179 & 0.0561 & 0.477762 \tabularnewline
19 & -0.12777 & -0.8759 & 0.807244 \tabularnewline
20 & -0.221171 & -1.5163 & 0.931926 \tabularnewline
21 & -0.136365 & -0.9349 & 0.822683 \tabularnewline
22 & 0.070749 & 0.485 & 0.314955 \tabularnewline
23 & -0.074064 & -0.5078 & 0.693 \tabularnewline
24 & 0.102437 & 0.7023 & 0.242986 \tabularnewline
25 & -0.124876 & -0.8561 & 0.801859 \tabularnewline
26 & 0.057613 & 0.395 & 0.347325 \tabularnewline
27 & 0.09014 & 0.618 & 0.26979 \tabularnewline
28 & -0.071906 & -0.493 & 0.687833 \tabularnewline
29 & -0.143591 & -0.9844 & 0.835023 \tabularnewline
30 & -0.023203 & -0.1591 & 0.562854 \tabularnewline
31 & 0.018995 & 0.1302 & 0.448472 \tabularnewline
32 & -0.046748 & -0.3205 & 0.624991 \tabularnewline
33 & -0.0628 & -0.4305 & 0.665613 \tabularnewline
34 & -0.05324 & -0.365 & 0.641623 \tabularnewline
35 & -0.005243 & -0.0359 & 0.514261 \tabularnewline
36 & 0.003359 & 0.023 & 0.490864 \tabularnewline
37 & -0.007778 & -0.0533 & 0.521148 \tabularnewline
38 & 0.02247 & 0.154 & 0.439118 \tabularnewline
39 & -0.101117 & -0.6932 & 0.75421 \tabularnewline
40 & -0.11436 & -0.784 & 0.781516 \tabularnewline
41 & -0.021955 & -0.1505 & 0.559499 \tabularnewline
42 & 0.013699 & 0.0939 & 0.462788 \tabularnewline
43 & 0.063951 & 0.4384 & 0.331544 \tabularnewline
44 & -0.001066 & -0.0073 & 0.502899 \tabularnewline
45 & -0.076271 & -0.5229 & 0.698246 \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64519&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]0[/C][C]0.291432[/C][C]1.998[/C][C]0.025763[/C][/ROW]
[ROW][C]1[/C][C]0.214174[/C][C]1.4683[/C][C]0.074341[/C][/ROW]
[ROW][C]2[/C][C]0.176819[/C][C]1.2122[/C][C]0.115745[/C][/ROW]
[ROW][C]3[/C][C]0.155425[/C][C]1.0655[/C][C]0.146038[/C][/ROW]
[ROW][C]4[/C][C]-0.393645[/C][C]-2.6987[/C][C]0.99518[/C][/ROW]
[ROW][C]5[/C][C]-0.000477[/C][C]-0.0033[/C][C]0.501297[/C][/ROW]
[ROW][C]6[/C][C]0.253324[/C][C]1.7367[/C][C]0.044495[/C][/ROW]
[ROW][C]7[/C][C]-0.110833[/C][C]-0.7598[/C][C]0.774424[/C][/ROW]
[ROW][C]8[/C][C]-0.23173[/C][C]-1.5887[/C][C]0.940579[/C][/ROW]
[ROW][C]9[/C][C]-0.365541[/C][C]-2.506[/C][C]0.992135[/C][/ROW]
[ROW][C]10[/C][C]0.096614[/C][C]0.6624[/C][C]0.255491[/C][/ROW]
[ROW][C]11[/C][C]-0.155254[/C][C]-1.0644[/C][C]0.853701[/C][/ROW]
[ROW][C]12[/C][C]-0.002103[/C][C]-0.0144[/C][C]0.505722[/C][/ROW]
[ROW][C]13[/C][C]0.033587[/C][C]0.2303[/C][C]0.409444[/C][/ROW]
[ROW][C]14[/C][C]0.131844[/C][C]0.9039[/C][C]0.185335[/C][/ROW]
[ROW][C]15[/C][C]0.156474[/C][C]1.0727[/C][C]0.144434[/C][/ROW]
[ROW][C]16[/C][C]-0.077353[/C][C]-0.5303[/C][C]0.700802[/C][/ROW]
[ROW][C]17[/C][C]-0.182676[/C][C]-1.2524[/C][C]0.891684[/C][/ROW]
[ROW][C]18[/C][C]0.008179[/C][C]0.0561[/C][C]0.477762[/C][/ROW]
[ROW][C]19[/C][C]-0.12777[/C][C]-0.8759[/C][C]0.807244[/C][/ROW]
[ROW][C]20[/C][C]-0.221171[/C][C]-1.5163[/C][C]0.931926[/C][/ROW]
[ROW][C]21[/C][C]-0.136365[/C][C]-0.9349[/C][C]0.822683[/C][/ROW]
[ROW][C]22[/C][C]0.070749[/C][C]0.485[/C][C]0.314955[/C][/ROW]
[ROW][C]23[/C][C]-0.074064[/C][C]-0.5078[/C][C]0.693[/C][/ROW]
[ROW][C]24[/C][C]0.102437[/C][C]0.7023[/C][C]0.242986[/C][/ROW]
[ROW][C]25[/C][C]-0.124876[/C][C]-0.8561[/C][C]0.801859[/C][/ROW]
[ROW][C]26[/C][C]0.057613[/C][C]0.395[/C][C]0.347325[/C][/ROW]
[ROW][C]27[/C][C]0.09014[/C][C]0.618[/C][C]0.26979[/C][/ROW]
[ROW][C]28[/C][C]-0.071906[/C][C]-0.493[/C][C]0.687833[/C][/ROW]
[ROW][C]29[/C][C]-0.143591[/C][C]-0.9844[/C][C]0.835023[/C][/ROW]
[ROW][C]30[/C][C]-0.023203[/C][C]-0.1591[/C][C]0.562854[/C][/ROW]
[ROW][C]31[/C][C]0.018995[/C][C]0.1302[/C][C]0.448472[/C][/ROW]
[ROW][C]32[/C][C]-0.046748[/C][C]-0.3205[/C][C]0.624991[/C][/ROW]
[ROW][C]33[/C][C]-0.0628[/C][C]-0.4305[/C][C]0.665613[/C][/ROW]
[ROW][C]34[/C][C]-0.05324[/C][C]-0.365[/C][C]0.641623[/C][/ROW]
[ROW][C]35[/C][C]-0.005243[/C][C]-0.0359[/C][C]0.514261[/C][/ROW]
[ROW][C]36[/C][C]0.003359[/C][C]0.023[/C][C]0.490864[/C][/ROW]
[ROW][C]37[/C][C]-0.007778[/C][C]-0.0533[/C][C]0.521148[/C][/ROW]
[ROW][C]38[/C][C]0.02247[/C][C]0.154[/C][C]0.439118[/C][/ROW]
[ROW][C]39[/C][C]-0.101117[/C][C]-0.6932[/C][C]0.75421[/C][/ROW]
[ROW][C]40[/C][C]-0.11436[/C][C]-0.784[/C][C]0.781516[/C][/ROW]
[ROW][C]41[/C][C]-0.021955[/C][C]-0.1505[/C][C]0.559499[/C][/ROW]
[ROW][C]42[/C][C]0.013699[/C][C]0.0939[/C][C]0.462788[/C][/ROW]
[ROW][C]43[/C][C]0.063951[/C][C]0.4384[/C][C]0.331544[/C][/ROW]
[ROW][C]44[/C][C]-0.001066[/C][C]-0.0073[/C][C]0.502899[/C][/ROW]
[ROW][C]45[/C][C]-0.076271[/C][C]-0.5229[/C][C]0.698246[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64519&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64519&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
00.2914321.9980.025763
10.2141741.46830.074341
20.1768191.21220.115745
30.1554251.06550.146038
4-0.393645-2.69870.99518
5-0.000477-0.00330.501297
60.2533241.73670.044495
7-0.110833-0.75980.774424
8-0.23173-1.58870.940579
9-0.365541-2.5060.992135
100.0966140.66240.255491
11-0.155254-1.06440.853701
12-0.002103-0.01440.505722
130.0335870.23030.409444
140.1318440.90390.185335
150.1564741.07270.144434
16-0.077353-0.53030.700802
17-0.182676-1.25240.891684
180.0081790.05610.477762
19-0.12777-0.87590.807244
20-0.221171-1.51630.931926
21-0.136365-0.93490.822683
220.0707490.4850.314955
23-0.074064-0.50780.693
240.1024370.70230.242986
25-0.124876-0.85610.801859
260.0576130.3950.347325
270.090140.6180.26979
28-0.071906-0.4930.687833
29-0.143591-0.98440.835023
30-0.023203-0.15910.562854
310.0189950.13020.448472
32-0.046748-0.32050.624991
33-0.0628-0.43050.665613
34-0.05324-0.3650.641623
35-0.005243-0.03590.514261
360.0033590.0230.490864
37-0.007778-0.05330.521148
380.022470.1540.439118
39-0.101117-0.69320.75421
40-0.11436-0.7840.781516
41-0.021955-0.15050.559499
420.0136990.09390.462788
430.0639510.43840.331544
44-0.001066-0.00730.502899
45-0.076271-0.52290.698246
46NANANA
47NANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')