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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 computationFri, 04 Dec 2009 09:32:23 -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/04/t1259944369131r9t84577y6ek.htm/, Retrieved Sat, 27 Apr 2024 19:31:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63868, Retrieved Sat, 27 Apr 2024 19:31:54 +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)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [] [2009-11-28 14:05:04] [74be16979710d4c4e7c6647856088456]
-   PD          [(Partial) Autocorrelation Function] [] [2009-12-04 16:12:11] [bb3c50fa849023ee18f70dac946932de]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-04 16:32:23] [1c886d75b2eec2d50a82160bb8104e3b] [Current]
-   P                 [(Partial) Autocorrelation Function] [] [2009-12-11 13:36:38] [bb3c50fa849023ee18f70dac946932de]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95.5
76.7
79.4
55.2
60
64.8
82.3
210.5
106
80.8
97.3
189.5
90
69.3
87.3
57.4
56.2
61.6
77.7
177.2
97.6
81.6
96.8
191.3
106
75.1
72
63.5
57.4
62.3
79.4
178.1
109.3
85.2
102.7
193.7
108.4
73.4
85.9
58.5
58.6
62.7
77.5
180.5
102.2
82.6
97.8
197.8
93.8
72.4
77.7
58.7
53.1
64.3
76.4
188.4
105.5
79.8
96.1
202.5

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=63868&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=63868&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63868&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
1-0.08248-0.57140.285185
20.0936360.64870.259803
30.1294920.89710.187059
40.1144690.79310.215821
5-0.056461-0.39120.348701
60.0671230.4650.322001
70.0532590.3690.356879
8-0.029371-0.20350.419808
90.1135530.78670.217658
10-3.7e-05-3e-040.499898
11-0.004048-0.0280.48887
12-0.46766-3.240.001087
130.2125881.47290.073659
14-0.153917-1.06640.145796
15-0.130994-0.90760.184323
16-0.145049-1.00490.159984
17-0.068188-0.47240.319383
18-0.054021-0.37430.354926
19-0.123769-0.85750.197716
20-0.10324-0.71530.238953
21-0.137006-0.94920.173635
220.0080360.05570.477915
23-0.026172-0.18130.428439
240.0493940.34220.366842
25-0.178305-1.23530.111359
260.0943120.65340.258304
27-0.032236-0.22330.412111
280.0066140.04580.48182
290.0646620.4480.328087
300.0028460.01970.492175
310.1106470.76660.223542
320.1249840.86590.195422
330.0245940.17040.432709
34-0.017771-0.12310.451263
350.0447190.30980.37902
36-0.010513-0.07280.471119

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.08248 & -0.5714 & 0.285185 \tabularnewline
2 & 0.093636 & 0.6487 & 0.259803 \tabularnewline
3 & 0.129492 & 0.8971 & 0.187059 \tabularnewline
4 & 0.114469 & 0.7931 & 0.215821 \tabularnewline
5 & -0.056461 & -0.3912 & 0.348701 \tabularnewline
6 & 0.067123 & 0.465 & 0.322001 \tabularnewline
7 & 0.053259 & 0.369 & 0.356879 \tabularnewline
8 & -0.029371 & -0.2035 & 0.419808 \tabularnewline
9 & 0.113553 & 0.7867 & 0.217658 \tabularnewline
10 & -3.7e-05 & -3e-04 & 0.499898 \tabularnewline
11 & -0.004048 & -0.028 & 0.48887 \tabularnewline
12 & -0.46766 & -3.24 & 0.001087 \tabularnewline
13 & 0.212588 & 1.4729 & 0.073659 \tabularnewline
14 & -0.153917 & -1.0664 & 0.145796 \tabularnewline
15 & -0.130994 & -0.9076 & 0.184323 \tabularnewline
16 & -0.145049 & -1.0049 & 0.159984 \tabularnewline
17 & -0.068188 & -0.4724 & 0.319383 \tabularnewline
18 & -0.054021 & -0.3743 & 0.354926 \tabularnewline
19 & -0.123769 & -0.8575 & 0.197716 \tabularnewline
20 & -0.10324 & -0.7153 & 0.238953 \tabularnewline
21 & -0.137006 & -0.9492 & 0.173635 \tabularnewline
22 & 0.008036 & 0.0557 & 0.477915 \tabularnewline
23 & -0.026172 & -0.1813 & 0.428439 \tabularnewline
24 & 0.049394 & 0.3422 & 0.366842 \tabularnewline
25 & -0.178305 & -1.2353 & 0.111359 \tabularnewline
26 & 0.094312 & 0.6534 & 0.258304 \tabularnewline
27 & -0.032236 & -0.2233 & 0.412111 \tabularnewline
28 & 0.006614 & 0.0458 & 0.48182 \tabularnewline
29 & 0.064662 & 0.448 & 0.328087 \tabularnewline
30 & 0.002846 & 0.0197 & 0.492175 \tabularnewline
31 & 0.110647 & 0.7666 & 0.223542 \tabularnewline
32 & 0.124984 & 0.8659 & 0.195422 \tabularnewline
33 & 0.024594 & 0.1704 & 0.432709 \tabularnewline
34 & -0.017771 & -0.1231 & 0.451263 \tabularnewline
35 & 0.044719 & 0.3098 & 0.37902 \tabularnewline
36 & -0.010513 & -0.0728 & 0.471119 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63868&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]-0.08248[/C][C]-0.5714[/C][C]0.285185[/C][/ROW]
[ROW][C]2[/C][C]0.093636[/C][C]0.6487[/C][C]0.259803[/C][/ROW]
[ROW][C]3[/C][C]0.129492[/C][C]0.8971[/C][C]0.187059[/C][/ROW]
[ROW][C]4[/C][C]0.114469[/C][C]0.7931[/C][C]0.215821[/C][/ROW]
[ROW][C]5[/C][C]-0.056461[/C][C]-0.3912[/C][C]0.348701[/C][/ROW]
[ROW][C]6[/C][C]0.067123[/C][C]0.465[/C][C]0.322001[/C][/ROW]
[ROW][C]7[/C][C]0.053259[/C][C]0.369[/C][C]0.356879[/C][/ROW]
[ROW][C]8[/C][C]-0.029371[/C][C]-0.2035[/C][C]0.419808[/C][/ROW]
[ROW][C]9[/C][C]0.113553[/C][C]0.7867[/C][C]0.217658[/C][/ROW]
[ROW][C]10[/C][C]-3.7e-05[/C][C]-3e-04[/C][C]0.499898[/C][/ROW]
[ROW][C]11[/C][C]-0.004048[/C][C]-0.028[/C][C]0.48887[/C][/ROW]
[ROW][C]12[/C][C]-0.46766[/C][C]-3.24[/C][C]0.001087[/C][/ROW]
[ROW][C]13[/C][C]0.212588[/C][C]1.4729[/C][C]0.073659[/C][/ROW]
[ROW][C]14[/C][C]-0.153917[/C][C]-1.0664[/C][C]0.145796[/C][/ROW]
[ROW][C]15[/C][C]-0.130994[/C][C]-0.9076[/C][C]0.184323[/C][/ROW]
[ROW][C]16[/C][C]-0.145049[/C][C]-1.0049[/C][C]0.159984[/C][/ROW]
[ROW][C]17[/C][C]-0.068188[/C][C]-0.4724[/C][C]0.319383[/C][/ROW]
[ROW][C]18[/C][C]-0.054021[/C][C]-0.3743[/C][C]0.354926[/C][/ROW]
[ROW][C]19[/C][C]-0.123769[/C][C]-0.8575[/C][C]0.197716[/C][/ROW]
[ROW][C]20[/C][C]-0.10324[/C][C]-0.7153[/C][C]0.238953[/C][/ROW]
[ROW][C]21[/C][C]-0.137006[/C][C]-0.9492[/C][C]0.173635[/C][/ROW]
[ROW][C]22[/C][C]0.008036[/C][C]0.0557[/C][C]0.477915[/C][/ROW]
[ROW][C]23[/C][C]-0.026172[/C][C]-0.1813[/C][C]0.428439[/C][/ROW]
[ROW][C]24[/C][C]0.049394[/C][C]0.3422[/C][C]0.366842[/C][/ROW]
[ROW][C]25[/C][C]-0.178305[/C][C]-1.2353[/C][C]0.111359[/C][/ROW]
[ROW][C]26[/C][C]0.094312[/C][C]0.6534[/C][C]0.258304[/C][/ROW]
[ROW][C]27[/C][C]-0.032236[/C][C]-0.2233[/C][C]0.412111[/C][/ROW]
[ROW][C]28[/C][C]0.006614[/C][C]0.0458[/C][C]0.48182[/C][/ROW]
[ROW][C]29[/C][C]0.064662[/C][C]0.448[/C][C]0.328087[/C][/ROW]
[ROW][C]30[/C][C]0.002846[/C][C]0.0197[/C][C]0.492175[/C][/ROW]
[ROW][C]31[/C][C]0.110647[/C][C]0.7666[/C][C]0.223542[/C][/ROW]
[ROW][C]32[/C][C]0.124984[/C][C]0.8659[/C][C]0.195422[/C][/ROW]
[ROW][C]33[/C][C]0.024594[/C][C]0.1704[/C][C]0.432709[/C][/ROW]
[ROW][C]34[/C][C]-0.017771[/C][C]-0.1231[/C][C]0.451263[/C][/ROW]
[ROW][C]35[/C][C]0.044719[/C][C]0.3098[/C][C]0.37902[/C][/ROW]
[ROW][C]36[/C][C]-0.010513[/C][C]-0.0728[/C][C]0.471119[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63868&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63868&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
1-0.08248-0.57140.285185
20.0936360.64870.259803
30.1294920.89710.187059
40.1144690.79310.215821
5-0.056461-0.39120.348701
60.0671230.4650.322001
70.0532590.3690.356879
8-0.029371-0.20350.419808
90.1135530.78670.217658
10-3.7e-05-3e-040.499898
11-0.004048-0.0280.48887
12-0.46766-3.240.001087
130.2125881.47290.073659
14-0.153917-1.06640.145796
15-0.130994-0.90760.184323
16-0.145049-1.00490.159984
17-0.068188-0.47240.319383
18-0.054021-0.37430.354926
19-0.123769-0.85750.197716
20-0.10324-0.71530.238953
21-0.137006-0.94920.173635
220.0080360.05570.477915
23-0.026172-0.18130.428439
240.0493940.34220.366842
25-0.178305-1.23530.111359
260.0943120.65340.258304
27-0.032236-0.22330.412111
280.0066140.04580.48182
290.0646620.4480.328087
300.0028460.01970.492175
310.1106470.76660.223542
320.1249840.86590.195422
330.0245940.17040.432709
34-0.017771-0.12310.451263
350.0447190.30980.37902
36-0.010513-0.07280.471119






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.08248-0.57140.285185
20.0874280.60570.273778
30.145851.01050.158666
40.13340.92420.179997
5-0.062222-0.43110.334167
60.0132960.09210.463495
70.0395170.27380.392714
8-0.026915-0.18650.42643
90.1070680.74180.230914
10-0.000937-0.00650.497424
11-0.024532-0.170.432877
12-0.527211-3.65260.000321
130.1285340.89050.188818
14-0.023308-0.16150.436195
15-0.021794-0.1510.440308
16-0.153654-1.06450.146203
17-0.188208-1.30390.099236
180.0746450.51720.303712
19-0.071226-0.49350.311965
20-0.070055-0.48540.314815
21-0.014588-0.10110.459958
220.0141430.0980.461175
230.0586180.40610.34323
24-0.187456-1.29870.10012
250.0456070.3160.376697
260.0048630.03370.486632
27-0.081316-0.56340.2879
28-0.096359-0.66760.253795
290.0428290.29670.383978
300.1026720.71130.240161
31-0.047056-0.3260.372915
32-0.006343-0.04390.482564
33-0.066328-0.45950.323962
340.0015970.01110.495608
35-0.062651-0.43410.333095
36-0.164621-1.14050.129862

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.08248 & -0.5714 & 0.285185 \tabularnewline
2 & 0.087428 & 0.6057 & 0.273778 \tabularnewline
3 & 0.14585 & 1.0105 & 0.158666 \tabularnewline
4 & 0.1334 & 0.9242 & 0.179997 \tabularnewline
5 & -0.062222 & -0.4311 & 0.334167 \tabularnewline
6 & 0.013296 & 0.0921 & 0.463495 \tabularnewline
7 & 0.039517 & 0.2738 & 0.392714 \tabularnewline
8 & -0.026915 & -0.1865 & 0.42643 \tabularnewline
9 & 0.107068 & 0.7418 & 0.230914 \tabularnewline
10 & -0.000937 & -0.0065 & 0.497424 \tabularnewline
11 & -0.024532 & -0.17 & 0.432877 \tabularnewline
12 & -0.527211 & -3.6526 & 0.000321 \tabularnewline
13 & 0.128534 & 0.8905 & 0.188818 \tabularnewline
14 & -0.023308 & -0.1615 & 0.436195 \tabularnewline
15 & -0.021794 & -0.151 & 0.440308 \tabularnewline
16 & -0.153654 & -1.0645 & 0.146203 \tabularnewline
17 & -0.188208 & -1.3039 & 0.099236 \tabularnewline
18 & 0.074645 & 0.5172 & 0.303712 \tabularnewline
19 & -0.071226 & -0.4935 & 0.311965 \tabularnewline
20 & -0.070055 & -0.4854 & 0.314815 \tabularnewline
21 & -0.014588 & -0.1011 & 0.459958 \tabularnewline
22 & 0.014143 & 0.098 & 0.461175 \tabularnewline
23 & 0.058618 & 0.4061 & 0.34323 \tabularnewline
24 & -0.187456 & -1.2987 & 0.10012 \tabularnewline
25 & 0.045607 & 0.316 & 0.376697 \tabularnewline
26 & 0.004863 & 0.0337 & 0.486632 \tabularnewline
27 & -0.081316 & -0.5634 & 0.2879 \tabularnewline
28 & -0.096359 & -0.6676 & 0.253795 \tabularnewline
29 & 0.042829 & 0.2967 & 0.383978 \tabularnewline
30 & 0.102672 & 0.7113 & 0.240161 \tabularnewline
31 & -0.047056 & -0.326 & 0.372915 \tabularnewline
32 & -0.006343 & -0.0439 & 0.482564 \tabularnewline
33 & -0.066328 & -0.4595 & 0.323962 \tabularnewline
34 & 0.001597 & 0.0111 & 0.495608 \tabularnewline
35 & -0.062651 & -0.4341 & 0.333095 \tabularnewline
36 & -0.164621 & -1.1405 & 0.129862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63868&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]-0.08248[/C][C]-0.5714[/C][C]0.285185[/C][/ROW]
[ROW][C]2[/C][C]0.087428[/C][C]0.6057[/C][C]0.273778[/C][/ROW]
[ROW][C]3[/C][C]0.14585[/C][C]1.0105[/C][C]0.158666[/C][/ROW]
[ROW][C]4[/C][C]0.1334[/C][C]0.9242[/C][C]0.179997[/C][/ROW]
[ROW][C]5[/C][C]-0.062222[/C][C]-0.4311[/C][C]0.334167[/C][/ROW]
[ROW][C]6[/C][C]0.013296[/C][C]0.0921[/C][C]0.463495[/C][/ROW]
[ROW][C]7[/C][C]0.039517[/C][C]0.2738[/C][C]0.392714[/C][/ROW]
[ROW][C]8[/C][C]-0.026915[/C][C]-0.1865[/C][C]0.42643[/C][/ROW]
[ROW][C]9[/C][C]0.107068[/C][C]0.7418[/C][C]0.230914[/C][/ROW]
[ROW][C]10[/C][C]-0.000937[/C][C]-0.0065[/C][C]0.497424[/C][/ROW]
[ROW][C]11[/C][C]-0.024532[/C][C]-0.17[/C][C]0.432877[/C][/ROW]
[ROW][C]12[/C][C]-0.527211[/C][C]-3.6526[/C][C]0.000321[/C][/ROW]
[ROW][C]13[/C][C]0.128534[/C][C]0.8905[/C][C]0.188818[/C][/ROW]
[ROW][C]14[/C][C]-0.023308[/C][C]-0.1615[/C][C]0.436195[/C][/ROW]
[ROW][C]15[/C][C]-0.021794[/C][C]-0.151[/C][C]0.440308[/C][/ROW]
[ROW][C]16[/C][C]-0.153654[/C][C]-1.0645[/C][C]0.146203[/C][/ROW]
[ROW][C]17[/C][C]-0.188208[/C][C]-1.3039[/C][C]0.099236[/C][/ROW]
[ROW][C]18[/C][C]0.074645[/C][C]0.5172[/C][C]0.303712[/C][/ROW]
[ROW][C]19[/C][C]-0.071226[/C][C]-0.4935[/C][C]0.311965[/C][/ROW]
[ROW][C]20[/C][C]-0.070055[/C][C]-0.4854[/C][C]0.314815[/C][/ROW]
[ROW][C]21[/C][C]-0.014588[/C][C]-0.1011[/C][C]0.459958[/C][/ROW]
[ROW][C]22[/C][C]0.014143[/C][C]0.098[/C][C]0.461175[/C][/ROW]
[ROW][C]23[/C][C]0.058618[/C][C]0.4061[/C][C]0.34323[/C][/ROW]
[ROW][C]24[/C][C]-0.187456[/C][C]-1.2987[/C][C]0.10012[/C][/ROW]
[ROW][C]25[/C][C]0.045607[/C][C]0.316[/C][C]0.376697[/C][/ROW]
[ROW][C]26[/C][C]0.004863[/C][C]0.0337[/C][C]0.486632[/C][/ROW]
[ROW][C]27[/C][C]-0.081316[/C][C]-0.5634[/C][C]0.2879[/C][/ROW]
[ROW][C]28[/C][C]-0.096359[/C][C]-0.6676[/C][C]0.253795[/C][/ROW]
[ROW][C]29[/C][C]0.042829[/C][C]0.2967[/C][C]0.383978[/C][/ROW]
[ROW][C]30[/C][C]0.102672[/C][C]0.7113[/C][C]0.240161[/C][/ROW]
[ROW][C]31[/C][C]-0.047056[/C][C]-0.326[/C][C]0.372915[/C][/ROW]
[ROW][C]32[/C][C]-0.006343[/C][C]-0.0439[/C][C]0.482564[/C][/ROW]
[ROW][C]33[/C][C]-0.066328[/C][C]-0.4595[/C][C]0.323962[/C][/ROW]
[ROW][C]34[/C][C]0.001597[/C][C]0.0111[/C][C]0.495608[/C][/ROW]
[ROW][C]35[/C][C]-0.062651[/C][C]-0.4341[/C][C]0.333095[/C][/ROW]
[ROW][C]36[/C][C]-0.164621[/C][C]-1.1405[/C][C]0.129862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63868&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63868&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
1-0.08248-0.57140.285185
20.0874280.60570.273778
30.145851.01050.158666
40.13340.92420.179997
5-0.062222-0.43110.334167
60.0132960.09210.463495
70.0395170.27380.392714
8-0.026915-0.18650.42643
90.1070680.74180.230914
10-0.000937-0.00650.497424
11-0.024532-0.170.432877
12-0.527211-3.65260.000321
130.1285340.89050.188818
14-0.023308-0.16150.436195
15-0.021794-0.1510.440308
16-0.153654-1.06450.146203
17-0.188208-1.30390.099236
180.0746450.51720.303712
19-0.071226-0.49350.311965
20-0.070055-0.48540.314815
21-0.014588-0.10110.459958
220.0141430.0980.461175
230.0586180.40610.34323
24-0.187456-1.29870.10012
250.0456070.3160.376697
260.0048630.03370.486632
27-0.081316-0.56340.2879
28-0.096359-0.66760.253795
290.0428290.29670.383978
300.1026720.71130.240161
31-0.047056-0.3260.372915
32-0.006343-0.04390.482564
33-0.066328-0.45950.323962
340.0015970.01110.495608
35-0.062651-0.43410.333095
36-0.164621-1.14050.129862


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.4 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.4 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')