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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, 12 Dec 2008 06:45:52 -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/2008/Dec/12/t12290899948pgbz5se670qo7h.htm/, Retrieved Fri, 17 May 2024 12:59:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32734, Retrieved Fri, 17 May 2024 12:59:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Standard Deviation-Mean Plot] [Q5 Standard DMP] [2008-11-29 16:26:32] [aa5573c1db401b164e448aef050955a1]
-   PD    [Standard Deviation-Mean Plot] [Q8 SDMN bouwprod] [2008-11-30 00:14:02] [aa5573c1db401b164e448aef050955a1]
-           [Standard Deviation-Mean Plot] [Q8 SDMN bouwprod] [2008-11-30 00:31:28] [aa5573c1db401b164e448aef050955a1]
-   P         [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-12 12:06:26] [aa5573c1db401b164e448aef050955a1]
- RM            [Variance Reduction Matrix] [VRM Bouwproductie] [2008-12-12 13:22:47] [aa5573c1db401b164e448aef050955a1]
- RMP             [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:31:29] [aa5573c1db401b164e448aef050955a1]
-   P                 [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:45:52] [8a1195ff8db4df756ce44b463a631c76] [Current]
-   P                   [(Partial) Autocorrelation Function] [ACF bouwproductie...] [2008-12-12 13:59:06] [aa5573c1db401b164e448aef050955a1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32734&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32734&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.247004-1.79820.038919
20.1194140.86930.194289
30.1350450.98310.165002
40.1223810.89090.188491
5-0.026564-0.19340.423697
60.2652231.93090.029429
7-0.086633-0.63070.265474
80.1096340.79810.214174
90.1755351.27790.103424
100.0212440.15470.43884
110.0429830.31290.377785
12-0.07647-0.55670.290034
130.0233230.16980.43291
14-0.073345-0.5340.297802
150.159121.15840.125944
16-0.185365-1.34950.091461
170.0753420.54850.292827
18-0.009993-0.07270.47114
19-0.005073-0.03690.485338
20-0.146083-1.06350.146188
210.0147250.10720.457519
22-0.259221-1.88720.032311
230.1735281.26330.106004
24-0.261117-1.9010.031376
25-0.045675-0.33250.370405
260.0073030.05320.4789
27-0.011833-0.08610.465838
28-0.14191-1.03310.15312
290.0093920.06840.472871
30-0.100415-0.7310.23399
31-0.105477-0.76790.222981
320.068490.49860.310057
33-0.068881-0.50150.309061
34-0.028933-0.21060.416989
35-0.066852-0.48670.314242
360.0837380.60960.272357

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.247004 & -1.7982 & 0.038919 \tabularnewline
2 & 0.119414 & 0.8693 & 0.194289 \tabularnewline
3 & 0.135045 & 0.9831 & 0.165002 \tabularnewline
4 & 0.122381 & 0.8909 & 0.188491 \tabularnewline
5 & -0.026564 & -0.1934 & 0.423697 \tabularnewline
6 & 0.265223 & 1.9309 & 0.029429 \tabularnewline
7 & -0.086633 & -0.6307 & 0.265474 \tabularnewline
8 & 0.109634 & 0.7981 & 0.214174 \tabularnewline
9 & 0.175535 & 1.2779 & 0.103424 \tabularnewline
10 & 0.021244 & 0.1547 & 0.43884 \tabularnewline
11 & 0.042983 & 0.3129 & 0.377785 \tabularnewline
12 & -0.07647 & -0.5567 & 0.290034 \tabularnewline
13 & 0.023323 & 0.1698 & 0.43291 \tabularnewline
14 & -0.073345 & -0.534 & 0.297802 \tabularnewline
15 & 0.15912 & 1.1584 & 0.125944 \tabularnewline
16 & -0.185365 & -1.3495 & 0.091461 \tabularnewline
17 & 0.075342 & 0.5485 & 0.292827 \tabularnewline
18 & -0.009993 & -0.0727 & 0.47114 \tabularnewline
19 & -0.005073 & -0.0369 & 0.485338 \tabularnewline
20 & -0.146083 & -1.0635 & 0.146188 \tabularnewline
21 & 0.014725 & 0.1072 & 0.457519 \tabularnewline
22 & -0.259221 & -1.8872 & 0.032311 \tabularnewline
23 & 0.173528 & 1.2633 & 0.106004 \tabularnewline
24 & -0.261117 & -1.901 & 0.031376 \tabularnewline
25 & -0.045675 & -0.3325 & 0.370405 \tabularnewline
26 & 0.007303 & 0.0532 & 0.4789 \tabularnewline
27 & -0.011833 & -0.0861 & 0.465838 \tabularnewline
28 & -0.14191 & -1.0331 & 0.15312 \tabularnewline
29 & 0.009392 & 0.0684 & 0.472871 \tabularnewline
30 & -0.100415 & -0.731 & 0.23399 \tabularnewline
31 & -0.105477 & -0.7679 & 0.222981 \tabularnewline
32 & 0.06849 & 0.4986 & 0.310057 \tabularnewline
33 & -0.068881 & -0.5015 & 0.309061 \tabularnewline
34 & -0.028933 & -0.2106 & 0.416989 \tabularnewline
35 & -0.066852 & -0.4867 & 0.314242 \tabularnewline
36 & 0.083738 & 0.6096 & 0.272357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32734&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]-0.247004[/C][C]-1.7982[/C][C]0.038919[/C][/ROW]
[ROW][C]2[/C][C]0.119414[/C][C]0.8693[/C][C]0.194289[/C][/ROW]
[ROW][C]3[/C][C]0.135045[/C][C]0.9831[/C][C]0.165002[/C][/ROW]
[ROW][C]4[/C][C]0.122381[/C][C]0.8909[/C][C]0.188491[/C][/ROW]
[ROW][C]5[/C][C]-0.026564[/C][C]-0.1934[/C][C]0.423697[/C][/ROW]
[ROW][C]6[/C][C]0.265223[/C][C]1.9309[/C][C]0.029429[/C][/ROW]
[ROW][C]7[/C][C]-0.086633[/C][C]-0.6307[/C][C]0.265474[/C][/ROW]
[ROW][C]8[/C][C]0.109634[/C][C]0.7981[/C][C]0.214174[/C][/ROW]
[ROW][C]9[/C][C]0.175535[/C][C]1.2779[/C][C]0.103424[/C][/ROW]
[ROW][C]10[/C][C]0.021244[/C][C]0.1547[/C][C]0.43884[/C][/ROW]
[ROW][C]11[/C][C]0.042983[/C][C]0.3129[/C][C]0.377785[/C][/ROW]
[ROW][C]12[/C][C]-0.07647[/C][C]-0.5567[/C][C]0.290034[/C][/ROW]
[ROW][C]13[/C][C]0.023323[/C][C]0.1698[/C][C]0.43291[/C][/ROW]
[ROW][C]14[/C][C]-0.073345[/C][C]-0.534[/C][C]0.297802[/C][/ROW]
[ROW][C]15[/C][C]0.15912[/C][C]1.1584[/C][C]0.125944[/C][/ROW]
[ROW][C]16[/C][C]-0.185365[/C][C]-1.3495[/C][C]0.091461[/C][/ROW]
[ROW][C]17[/C][C]0.075342[/C][C]0.5485[/C][C]0.292827[/C][/ROW]
[ROW][C]18[/C][C]-0.009993[/C][C]-0.0727[/C][C]0.47114[/C][/ROW]
[ROW][C]19[/C][C]-0.005073[/C][C]-0.0369[/C][C]0.485338[/C][/ROW]
[ROW][C]20[/C][C]-0.146083[/C][C]-1.0635[/C][C]0.146188[/C][/ROW]
[ROW][C]21[/C][C]0.014725[/C][C]0.1072[/C][C]0.457519[/C][/ROW]
[ROW][C]22[/C][C]-0.259221[/C][C]-1.8872[/C][C]0.032311[/C][/ROW]
[ROW][C]23[/C][C]0.173528[/C][C]1.2633[/C][C]0.106004[/C][/ROW]
[ROW][C]24[/C][C]-0.261117[/C][C]-1.901[/C][C]0.031376[/C][/ROW]
[ROW][C]25[/C][C]-0.045675[/C][C]-0.3325[/C][C]0.370405[/C][/ROW]
[ROW][C]26[/C][C]0.007303[/C][C]0.0532[/C][C]0.4789[/C][/ROW]
[ROW][C]27[/C][C]-0.011833[/C][C]-0.0861[/C][C]0.465838[/C][/ROW]
[ROW][C]28[/C][C]-0.14191[/C][C]-1.0331[/C][C]0.15312[/C][/ROW]
[ROW][C]29[/C][C]0.009392[/C][C]0.0684[/C][C]0.472871[/C][/ROW]
[ROW][C]30[/C][C]-0.100415[/C][C]-0.731[/C][C]0.23399[/C][/ROW]
[ROW][C]31[/C][C]-0.105477[/C][C]-0.7679[/C][C]0.222981[/C][/ROW]
[ROW][C]32[/C][C]0.06849[/C][C]0.4986[/C][C]0.310057[/C][/ROW]
[ROW][C]33[/C][C]-0.068881[/C][C]-0.5015[/C][C]0.309061[/C][/ROW]
[ROW][C]34[/C][C]-0.028933[/C][C]-0.2106[/C][C]0.416989[/C][/ROW]
[ROW][C]35[/C][C]-0.066852[/C][C]-0.4867[/C][C]0.314242[/C][/ROW]
[ROW][C]36[/C][C]0.083738[/C][C]0.6096[/C][C]0.272357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32734&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
1-0.247004-1.79820.038919
20.1194140.86930.194289
30.1350450.98310.165002
40.1223810.89090.188491
5-0.026564-0.19340.423697
60.2652231.93090.029429
7-0.086633-0.63070.265474
80.1096340.79810.214174
90.1755351.27790.103424
100.0212440.15470.43884
110.0429830.31290.377785
12-0.07647-0.55670.290034
130.0233230.16980.43291
14-0.073345-0.5340.297802
150.159121.15840.125944
16-0.185365-1.34950.091461
170.0753420.54850.292827
18-0.009993-0.07270.47114
19-0.005073-0.03690.485338
20-0.146083-1.06350.146188
210.0147250.10720.457519
22-0.259221-1.88720.032311
230.1735281.26330.106004
24-0.261117-1.9010.031376
25-0.045675-0.33250.370405
260.0073030.05320.4789
27-0.011833-0.08610.465838
28-0.14191-1.03310.15312
290.0093920.06840.472871
30-0.100415-0.7310.23399
31-0.105477-0.76790.222981
320.068490.49860.310057
33-0.068881-0.50150.309061
34-0.028933-0.21060.416989
35-0.066852-0.48670.314242
360.0837380.60960.272357






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.247004-1.79820.038919
20.0621980.45280.326269
30.1903761.3860.085782
40.2103181.53110.065841
50.0230960.16810.433556
60.2269341.65210.052213
7-0.014766-0.10750.457399
80.0177160.1290.448933
90.1598011.16340.124945
100.0569680.41470.340007
110.0279240.20330.419843
12-0.234329-1.70590.046937
13-0.138797-1.01050.158433
14-0.188441-1.37190.087942
150.0804330.58560.280327
16-0.082787-0.60270.274639
17-0.005687-0.04140.483564
180.0517540.37680.353923
190.0011920.00870.496553
20-0.078502-0.57150.285036
21-0.067879-0.49420.311616
22-0.197078-1.43470.078617
230.135030.9830.165028
24-0.210509-1.53250.06567
25-0.103555-0.75390.227125
260.0283420.20630.418661
270.1313880.95650.171576
280.0564890.41120.341274
293.4e-052e-040.499901
300.0734090.53440.297642
31-0.004999-0.03640.485553
320.0293310.21350.415864
330.0187370.13640.446008
34-0.026336-0.19170.424343
35-0.056428-0.41080.341437
36-0.084729-0.61680.269992

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.247004 & -1.7982 & 0.038919 \tabularnewline
2 & 0.062198 & 0.4528 & 0.326269 \tabularnewline
3 & 0.190376 & 1.386 & 0.085782 \tabularnewline
4 & 0.210318 & 1.5311 & 0.065841 \tabularnewline
5 & 0.023096 & 0.1681 & 0.433556 \tabularnewline
6 & 0.226934 & 1.6521 & 0.052213 \tabularnewline
7 & -0.014766 & -0.1075 & 0.457399 \tabularnewline
8 & 0.017716 & 0.129 & 0.448933 \tabularnewline
9 & 0.159801 & 1.1634 & 0.124945 \tabularnewline
10 & 0.056968 & 0.4147 & 0.340007 \tabularnewline
11 & 0.027924 & 0.2033 & 0.419843 \tabularnewline
12 & -0.234329 & -1.7059 & 0.046937 \tabularnewline
13 & -0.138797 & -1.0105 & 0.158433 \tabularnewline
14 & -0.188441 & -1.3719 & 0.087942 \tabularnewline
15 & 0.080433 & 0.5856 & 0.280327 \tabularnewline
16 & -0.082787 & -0.6027 & 0.274639 \tabularnewline
17 & -0.005687 & -0.0414 & 0.483564 \tabularnewline
18 & 0.051754 & 0.3768 & 0.353923 \tabularnewline
19 & 0.001192 & 0.0087 & 0.496553 \tabularnewline
20 & -0.078502 & -0.5715 & 0.285036 \tabularnewline
21 & -0.067879 & -0.4942 & 0.311616 \tabularnewline
22 & -0.197078 & -1.4347 & 0.078617 \tabularnewline
23 & 0.13503 & 0.983 & 0.165028 \tabularnewline
24 & -0.210509 & -1.5325 & 0.06567 \tabularnewline
25 & -0.103555 & -0.7539 & 0.227125 \tabularnewline
26 & 0.028342 & 0.2063 & 0.418661 \tabularnewline
27 & 0.131388 & 0.9565 & 0.171576 \tabularnewline
28 & 0.056489 & 0.4112 & 0.341274 \tabularnewline
29 & 3.4e-05 & 2e-04 & 0.499901 \tabularnewline
30 & 0.073409 & 0.5344 & 0.297642 \tabularnewline
31 & -0.004999 & -0.0364 & 0.485553 \tabularnewline
32 & 0.029331 & 0.2135 & 0.415864 \tabularnewline
33 & 0.018737 & 0.1364 & 0.446008 \tabularnewline
34 & -0.026336 & -0.1917 & 0.424343 \tabularnewline
35 & -0.056428 & -0.4108 & 0.341437 \tabularnewline
36 & -0.084729 & -0.6168 & 0.269992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32734&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]-0.247004[/C][C]-1.7982[/C][C]0.038919[/C][/ROW]
[ROW][C]2[/C][C]0.062198[/C][C]0.4528[/C][C]0.326269[/C][/ROW]
[ROW][C]3[/C][C]0.190376[/C][C]1.386[/C][C]0.085782[/C][/ROW]
[ROW][C]4[/C][C]0.210318[/C][C]1.5311[/C][C]0.065841[/C][/ROW]
[ROW][C]5[/C][C]0.023096[/C][C]0.1681[/C][C]0.433556[/C][/ROW]
[ROW][C]6[/C][C]0.226934[/C][C]1.6521[/C][C]0.052213[/C][/ROW]
[ROW][C]7[/C][C]-0.014766[/C][C]-0.1075[/C][C]0.457399[/C][/ROW]
[ROW][C]8[/C][C]0.017716[/C][C]0.129[/C][C]0.448933[/C][/ROW]
[ROW][C]9[/C][C]0.159801[/C][C]1.1634[/C][C]0.124945[/C][/ROW]
[ROW][C]10[/C][C]0.056968[/C][C]0.4147[/C][C]0.340007[/C][/ROW]
[ROW][C]11[/C][C]0.027924[/C][C]0.2033[/C][C]0.419843[/C][/ROW]
[ROW][C]12[/C][C]-0.234329[/C][C]-1.7059[/C][C]0.046937[/C][/ROW]
[ROW][C]13[/C][C]-0.138797[/C][C]-1.0105[/C][C]0.158433[/C][/ROW]
[ROW][C]14[/C][C]-0.188441[/C][C]-1.3719[/C][C]0.087942[/C][/ROW]
[ROW][C]15[/C][C]0.080433[/C][C]0.5856[/C][C]0.280327[/C][/ROW]
[ROW][C]16[/C][C]-0.082787[/C][C]-0.6027[/C][C]0.274639[/C][/ROW]
[ROW][C]17[/C][C]-0.005687[/C][C]-0.0414[/C][C]0.483564[/C][/ROW]
[ROW][C]18[/C][C]0.051754[/C][C]0.3768[/C][C]0.353923[/C][/ROW]
[ROW][C]19[/C][C]0.001192[/C][C]0.0087[/C][C]0.496553[/C][/ROW]
[ROW][C]20[/C][C]-0.078502[/C][C]-0.5715[/C][C]0.285036[/C][/ROW]
[ROW][C]21[/C][C]-0.067879[/C][C]-0.4942[/C][C]0.311616[/C][/ROW]
[ROW][C]22[/C][C]-0.197078[/C][C]-1.4347[/C][C]0.078617[/C][/ROW]
[ROW][C]23[/C][C]0.13503[/C][C]0.983[/C][C]0.165028[/C][/ROW]
[ROW][C]24[/C][C]-0.210509[/C][C]-1.5325[/C][C]0.06567[/C][/ROW]
[ROW][C]25[/C][C]-0.103555[/C][C]-0.7539[/C][C]0.227125[/C][/ROW]
[ROW][C]26[/C][C]0.028342[/C][C]0.2063[/C][C]0.418661[/C][/ROW]
[ROW][C]27[/C][C]0.131388[/C][C]0.9565[/C][C]0.171576[/C][/ROW]
[ROW][C]28[/C][C]0.056489[/C][C]0.4112[/C][C]0.341274[/C][/ROW]
[ROW][C]29[/C][C]3.4e-05[/C][C]2e-04[/C][C]0.499901[/C][/ROW]
[ROW][C]30[/C][C]0.073409[/C][C]0.5344[/C][C]0.297642[/C][/ROW]
[ROW][C]31[/C][C]-0.004999[/C][C]-0.0364[/C][C]0.485553[/C][/ROW]
[ROW][C]32[/C][C]0.029331[/C][C]0.2135[/C][C]0.415864[/C][/ROW]
[ROW][C]33[/C][C]0.018737[/C][C]0.1364[/C][C]0.446008[/C][/ROW]
[ROW][C]34[/C][C]-0.026336[/C][C]-0.1917[/C][C]0.424343[/C][/ROW]
[ROW][C]35[/C][C]-0.056428[/C][C]-0.4108[/C][C]0.341437[/C][/ROW]
[ROW][C]36[/C][C]-0.084729[/C][C]-0.6168[/C][C]0.269992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32734&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32734&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
1-0.247004-1.79820.038919
20.0621980.45280.326269
30.1903761.3860.085782
40.2103181.53110.065841
50.0230960.16810.433556
60.2269341.65210.052213
7-0.014766-0.10750.457399
80.0177160.1290.448933
90.1598011.16340.124945
100.0569680.41470.340007
110.0279240.20330.419843
12-0.234329-1.70590.046937
13-0.138797-1.01050.158433
14-0.188441-1.37190.087942
150.0804330.58560.280327
16-0.082787-0.60270.274639
17-0.005687-0.04140.483564
180.0517540.37680.353923
190.0011920.00870.496553
20-0.078502-0.57150.285036
21-0.067879-0.49420.311616
22-0.197078-1.43470.078617
230.135030.9830.165028
24-0.210509-1.53250.06567
25-0.103555-0.75390.227125
260.0283420.20630.418661
270.1313880.95650.171576
280.0564890.41120.341274
293.4e-052e-040.499901
300.0734090.53440.297642
31-0.004999-0.03640.485553
320.0293310.21350.415864
330.0187370.13640.446008
34-0.026336-0.19170.424343
35-0.056428-0.41080.341437
36-0.084729-0.61680.269992


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 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')