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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 computationThu, 26 Nov 2009 13:14:44 -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/Nov/26/t1259266541c3infeseh9v78g8.htm/, Retrieved Mon, 29 Apr 2024 04:58:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60360, Retrieved Mon, 29 Apr 2024 04:58:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112

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] [Workshop 8, metho...] [2009-11-26 20:14:44] [e339dd08bcbfc073ac7494f09a949034] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.6
23.7
22
21.3
20.7
20.4
20.3
20.4
19.8
19.5
23.1
23.5
23.5
22.9
21.9
21.5
20.5
20.2
19.4
19.2
18.8
18.8
22.6
23.3
23
21.4
19.9
18.8
18.6
18.4
18.6
19.9
19.2
18.4
21.1
20.5
19.1
18.1
17
17.1
17.4
16.8
15.3
14.3
13.4
15.3
22.1
23.7
22.2
19.5
16.6
17.3
19.8
21.2
21.5
20.6
19.1
19.6
23.5
24

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=60360&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=60360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60360&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
10.8723866.04410
20.5990514.15036.8e-05
30.3259932.25850.014247
40.1780071.23330.111741
50.1823841.26360.106239
60.2648971.83530.036334
70.3109932.15460.018119
80.2465871.70840.047011
90.0737040.51060.305972
10-0.142354-0.98630.164476
11-0.310378-2.15040.018296
12-0.371414-2.57320.00661
13-0.312545-2.16540.01768
14-0.193944-1.34370.092684
15-0.093012-0.64440.261191
16-0.06577-0.45570.325343
17-0.102183-0.70790.241201
18-0.174757-1.21080.115959
19-0.230655-1.5980.0583
20-0.223979-1.55180.063643
21-0.16583-1.14890.128144
22-0.078725-0.54540.293995
23-0.005624-0.0390.48454
240.0192320.13320.447279
25-0.01437-0.09960.460554
26-0.079082-0.54790.29315
27-0.145724-1.00960.158873
28-0.170082-1.17840.122231
29-0.147558-1.02230.155879
30-0.091969-0.63720.263518
31-0.030816-0.21350.41592
32-0.004336-0.030.488081
33-0.016523-0.11450.45467
34-0.048325-0.33480.369615
35-0.067566-0.46810.320913
36-0.062543-0.43330.333364

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.872386 & 6.0441 & 0 \tabularnewline
2 & 0.599051 & 4.1503 & 6.8e-05 \tabularnewline
3 & 0.325993 & 2.2585 & 0.014247 \tabularnewline
4 & 0.178007 & 1.2333 & 0.111741 \tabularnewline
5 & 0.182384 & 1.2636 & 0.106239 \tabularnewline
6 & 0.264897 & 1.8353 & 0.036334 \tabularnewline
7 & 0.310993 & 2.1546 & 0.018119 \tabularnewline
8 & 0.246587 & 1.7084 & 0.047011 \tabularnewline
9 & 0.073704 & 0.5106 & 0.305972 \tabularnewline
10 & -0.142354 & -0.9863 & 0.164476 \tabularnewline
11 & -0.310378 & -2.1504 & 0.018296 \tabularnewline
12 & -0.371414 & -2.5732 & 0.00661 \tabularnewline
13 & -0.312545 & -2.1654 & 0.01768 \tabularnewline
14 & -0.193944 & -1.3437 & 0.092684 \tabularnewline
15 & -0.093012 & -0.6444 & 0.261191 \tabularnewline
16 & -0.06577 & -0.4557 & 0.325343 \tabularnewline
17 & -0.102183 & -0.7079 & 0.241201 \tabularnewline
18 & -0.174757 & -1.2108 & 0.115959 \tabularnewline
19 & -0.230655 & -1.598 & 0.0583 \tabularnewline
20 & -0.223979 & -1.5518 & 0.063643 \tabularnewline
21 & -0.16583 & -1.1489 & 0.128144 \tabularnewline
22 & -0.078725 & -0.5454 & 0.293995 \tabularnewline
23 & -0.005624 & -0.039 & 0.48454 \tabularnewline
24 & 0.019232 & 0.1332 & 0.447279 \tabularnewline
25 & -0.01437 & -0.0996 & 0.460554 \tabularnewline
26 & -0.079082 & -0.5479 & 0.29315 \tabularnewline
27 & -0.145724 & -1.0096 & 0.158873 \tabularnewline
28 & -0.170082 & -1.1784 & 0.122231 \tabularnewline
29 & -0.147558 & -1.0223 & 0.155879 \tabularnewline
30 & -0.091969 & -0.6372 & 0.263518 \tabularnewline
31 & -0.030816 & -0.2135 & 0.41592 \tabularnewline
32 & -0.004336 & -0.03 & 0.488081 \tabularnewline
33 & -0.016523 & -0.1145 & 0.45467 \tabularnewline
34 & -0.048325 & -0.3348 & 0.369615 \tabularnewline
35 & -0.067566 & -0.4681 & 0.320913 \tabularnewline
36 & -0.062543 & -0.4333 & 0.333364 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60360&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]0.872386[/C][C]6.0441[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.599051[/C][C]4.1503[/C][C]6.8e-05[/C][/ROW]
[ROW][C]3[/C][C]0.325993[/C][C]2.2585[/C][C]0.014247[/C][/ROW]
[ROW][C]4[/C][C]0.178007[/C][C]1.2333[/C][C]0.111741[/C][/ROW]
[ROW][C]5[/C][C]0.182384[/C][C]1.2636[/C][C]0.106239[/C][/ROW]
[ROW][C]6[/C][C]0.264897[/C][C]1.8353[/C][C]0.036334[/C][/ROW]
[ROW][C]7[/C][C]0.310993[/C][C]2.1546[/C][C]0.018119[/C][/ROW]
[ROW][C]8[/C][C]0.246587[/C][C]1.7084[/C][C]0.047011[/C][/ROW]
[ROW][C]9[/C][C]0.073704[/C][C]0.5106[/C][C]0.305972[/C][/ROW]
[ROW][C]10[/C][C]-0.142354[/C][C]-0.9863[/C][C]0.164476[/C][/ROW]
[ROW][C]11[/C][C]-0.310378[/C][C]-2.1504[/C][C]0.018296[/C][/ROW]
[ROW][C]12[/C][C]-0.371414[/C][C]-2.5732[/C][C]0.00661[/C][/ROW]
[ROW][C]13[/C][C]-0.312545[/C][C]-2.1654[/C][C]0.01768[/C][/ROW]
[ROW][C]14[/C][C]-0.193944[/C][C]-1.3437[/C][C]0.092684[/C][/ROW]
[ROW][C]15[/C][C]-0.093012[/C][C]-0.6444[/C][C]0.261191[/C][/ROW]
[ROW][C]16[/C][C]-0.06577[/C][C]-0.4557[/C][C]0.325343[/C][/ROW]
[ROW][C]17[/C][C]-0.102183[/C][C]-0.7079[/C][C]0.241201[/C][/ROW]
[ROW][C]18[/C][C]-0.174757[/C][C]-1.2108[/C][C]0.115959[/C][/ROW]
[ROW][C]19[/C][C]-0.230655[/C][C]-1.598[/C][C]0.0583[/C][/ROW]
[ROW][C]20[/C][C]-0.223979[/C][C]-1.5518[/C][C]0.063643[/C][/ROW]
[ROW][C]21[/C][C]-0.16583[/C][C]-1.1489[/C][C]0.128144[/C][/ROW]
[ROW][C]22[/C][C]-0.078725[/C][C]-0.5454[/C][C]0.293995[/C][/ROW]
[ROW][C]23[/C][C]-0.005624[/C][C]-0.039[/C][C]0.48454[/C][/ROW]
[ROW][C]24[/C][C]0.019232[/C][C]0.1332[/C][C]0.447279[/C][/ROW]
[ROW][C]25[/C][C]-0.01437[/C][C]-0.0996[/C][C]0.460554[/C][/ROW]
[ROW][C]26[/C][C]-0.079082[/C][C]-0.5479[/C][C]0.29315[/C][/ROW]
[ROW][C]27[/C][C]-0.145724[/C][C]-1.0096[/C][C]0.158873[/C][/ROW]
[ROW][C]28[/C][C]-0.170082[/C][C]-1.1784[/C][C]0.122231[/C][/ROW]
[ROW][C]29[/C][C]-0.147558[/C][C]-1.0223[/C][C]0.155879[/C][/ROW]
[ROW][C]30[/C][C]-0.091969[/C][C]-0.6372[/C][C]0.263518[/C][/ROW]
[ROW][C]31[/C][C]-0.030816[/C][C]-0.2135[/C][C]0.41592[/C][/ROW]
[ROW][C]32[/C][C]-0.004336[/C][C]-0.03[/C][C]0.488081[/C][/ROW]
[ROW][C]33[/C][C]-0.016523[/C][C]-0.1145[/C][C]0.45467[/C][/ROW]
[ROW][C]34[/C][C]-0.048325[/C][C]-0.3348[/C][C]0.369615[/C][/ROW]
[ROW][C]35[/C][C]-0.067566[/C][C]-0.4681[/C][C]0.320913[/C][/ROW]
[ROW][C]36[/C][C]-0.062543[/C][C]-0.4333[/C][C]0.333364[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60360&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
10.8723866.04410
20.5990514.15036.8e-05
30.3259932.25850.014247
40.1780071.23330.111741
50.1823841.26360.106239
60.2648971.83530.036334
70.3109932.15460.018119
80.2465871.70840.047011
90.0737040.51060.305972
10-0.142354-0.98630.164476
11-0.310378-2.15040.018296
12-0.371414-2.57320.00661
13-0.312545-2.16540.01768
14-0.193944-1.34370.092684
15-0.093012-0.64440.261191
16-0.06577-0.45570.325343
17-0.102183-0.70790.241201
18-0.174757-1.21080.115959
19-0.230655-1.5980.0583
20-0.223979-1.55180.063643
21-0.16583-1.14890.128144
22-0.078725-0.54540.293995
23-0.005624-0.0390.48454
240.0192320.13320.447279
25-0.01437-0.09960.460554
26-0.079082-0.54790.29315
27-0.145724-1.00960.158873
28-0.170082-1.17840.122231
29-0.147558-1.02230.155879
30-0.091969-0.63720.263518
31-0.030816-0.21350.41592
32-0.004336-0.030.488081
33-0.016523-0.11450.45467
34-0.048325-0.33480.369615
35-0.067566-0.46810.320913
36-0.062543-0.43330.333364






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8723866.04410
2-0.678018-4.69741.1e-05
30.3140842.1760.017253
40.3348812.32010.012316
50.0524110.36310.359056
6-0.149421-1.03520.152877
7-0.175773-1.21780.114628
8-0.100555-0.69670.244686
9-0.119562-0.82840.205786
10-0.150093-1.03990.151804
11-0.035204-0.24390.404173
120.0024170.01670.493354
130.1691711.1720.123481
14-0.048594-0.33670.368916
150.0204070.14140.44408
160.021320.14770.441595
170.149571.03630.152638
18-0.233067-1.61470.056461
19-0.072798-0.50440.308157
200.1036430.71810.2381
21-0.184568-1.27870.103571
220.0532650.3690.356864
23-0.032944-0.22820.410213
24-0.037133-0.25730.399037
25-0.026386-0.18280.427859
260.0179580.12440.450754
27-0.129985-0.90060.186158
280.1059810.73430.233182
29-0.043316-0.30010.382697
30-0.030155-0.20890.417697
310.0466130.32290.374069
32-0.102509-0.71020.240506
330.1112940.77110.222222
340.008520.0590.476588
35-0.011794-0.08170.467608
36-0.06229-0.43160.333996

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.872386 & 6.0441 & 0 \tabularnewline
2 & -0.678018 & -4.6974 & 1.1e-05 \tabularnewline
3 & 0.314084 & 2.176 & 0.017253 \tabularnewline
4 & 0.334881 & 2.3201 & 0.012316 \tabularnewline
5 & 0.052411 & 0.3631 & 0.359056 \tabularnewline
6 & -0.149421 & -1.0352 & 0.152877 \tabularnewline
7 & -0.175773 & -1.2178 & 0.114628 \tabularnewline
8 & -0.100555 & -0.6967 & 0.244686 \tabularnewline
9 & -0.119562 & -0.8284 & 0.205786 \tabularnewline
10 & -0.150093 & -1.0399 & 0.151804 \tabularnewline
11 & -0.035204 & -0.2439 & 0.404173 \tabularnewline
12 & 0.002417 & 0.0167 & 0.493354 \tabularnewline
13 & 0.169171 & 1.172 & 0.123481 \tabularnewline
14 & -0.048594 & -0.3367 & 0.368916 \tabularnewline
15 & 0.020407 & 0.1414 & 0.44408 \tabularnewline
16 & 0.02132 & 0.1477 & 0.441595 \tabularnewline
17 & 0.14957 & 1.0363 & 0.152638 \tabularnewline
18 & -0.233067 & -1.6147 & 0.056461 \tabularnewline
19 & -0.072798 & -0.5044 & 0.308157 \tabularnewline
20 & 0.103643 & 0.7181 & 0.2381 \tabularnewline
21 & -0.184568 & -1.2787 & 0.103571 \tabularnewline
22 & 0.053265 & 0.369 & 0.356864 \tabularnewline
23 & -0.032944 & -0.2282 & 0.410213 \tabularnewline
24 & -0.037133 & -0.2573 & 0.399037 \tabularnewline
25 & -0.026386 & -0.1828 & 0.427859 \tabularnewline
26 & 0.017958 & 0.1244 & 0.450754 \tabularnewline
27 & -0.129985 & -0.9006 & 0.186158 \tabularnewline
28 & 0.105981 & 0.7343 & 0.233182 \tabularnewline
29 & -0.043316 & -0.3001 & 0.382697 \tabularnewline
30 & -0.030155 & -0.2089 & 0.417697 \tabularnewline
31 & 0.046613 & 0.3229 & 0.374069 \tabularnewline
32 & -0.102509 & -0.7102 & 0.240506 \tabularnewline
33 & 0.111294 & 0.7711 & 0.222222 \tabularnewline
34 & 0.00852 & 0.059 & 0.476588 \tabularnewline
35 & -0.011794 & -0.0817 & 0.467608 \tabularnewline
36 & -0.06229 & -0.4316 & 0.333996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60360&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]0.872386[/C][C]6.0441[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.678018[/C][C]-4.6974[/C][C]1.1e-05[/C][/ROW]
[ROW][C]3[/C][C]0.314084[/C][C]2.176[/C][C]0.017253[/C][/ROW]
[ROW][C]4[/C][C]0.334881[/C][C]2.3201[/C][C]0.012316[/C][/ROW]
[ROW][C]5[/C][C]0.052411[/C][C]0.3631[/C][C]0.359056[/C][/ROW]
[ROW][C]6[/C][C]-0.149421[/C][C]-1.0352[/C][C]0.152877[/C][/ROW]
[ROW][C]7[/C][C]-0.175773[/C][C]-1.2178[/C][C]0.114628[/C][/ROW]
[ROW][C]8[/C][C]-0.100555[/C][C]-0.6967[/C][C]0.244686[/C][/ROW]
[ROW][C]9[/C][C]-0.119562[/C][C]-0.8284[/C][C]0.205786[/C][/ROW]
[ROW][C]10[/C][C]-0.150093[/C][C]-1.0399[/C][C]0.151804[/C][/ROW]
[ROW][C]11[/C][C]-0.035204[/C][C]-0.2439[/C][C]0.404173[/C][/ROW]
[ROW][C]12[/C][C]0.002417[/C][C]0.0167[/C][C]0.493354[/C][/ROW]
[ROW][C]13[/C][C]0.169171[/C][C]1.172[/C][C]0.123481[/C][/ROW]
[ROW][C]14[/C][C]-0.048594[/C][C]-0.3367[/C][C]0.368916[/C][/ROW]
[ROW][C]15[/C][C]0.020407[/C][C]0.1414[/C][C]0.44408[/C][/ROW]
[ROW][C]16[/C][C]0.02132[/C][C]0.1477[/C][C]0.441595[/C][/ROW]
[ROW][C]17[/C][C]0.14957[/C][C]1.0363[/C][C]0.152638[/C][/ROW]
[ROW][C]18[/C][C]-0.233067[/C][C]-1.6147[/C][C]0.056461[/C][/ROW]
[ROW][C]19[/C][C]-0.072798[/C][C]-0.5044[/C][C]0.308157[/C][/ROW]
[ROW][C]20[/C][C]0.103643[/C][C]0.7181[/C][C]0.2381[/C][/ROW]
[ROW][C]21[/C][C]-0.184568[/C][C]-1.2787[/C][C]0.103571[/C][/ROW]
[ROW][C]22[/C][C]0.053265[/C][C]0.369[/C][C]0.356864[/C][/ROW]
[ROW][C]23[/C][C]-0.032944[/C][C]-0.2282[/C][C]0.410213[/C][/ROW]
[ROW][C]24[/C][C]-0.037133[/C][C]-0.2573[/C][C]0.399037[/C][/ROW]
[ROW][C]25[/C][C]-0.026386[/C][C]-0.1828[/C][C]0.427859[/C][/ROW]
[ROW][C]26[/C][C]0.017958[/C][C]0.1244[/C][C]0.450754[/C][/ROW]
[ROW][C]27[/C][C]-0.129985[/C][C]-0.9006[/C][C]0.186158[/C][/ROW]
[ROW][C]28[/C][C]0.105981[/C][C]0.7343[/C][C]0.233182[/C][/ROW]
[ROW][C]29[/C][C]-0.043316[/C][C]-0.3001[/C][C]0.382697[/C][/ROW]
[ROW][C]30[/C][C]-0.030155[/C][C]-0.2089[/C][C]0.417697[/C][/ROW]
[ROW][C]31[/C][C]0.046613[/C][C]0.3229[/C][C]0.374069[/C][/ROW]
[ROW][C]32[/C][C]-0.102509[/C][C]-0.7102[/C][C]0.240506[/C][/ROW]
[ROW][C]33[/C][C]0.111294[/C][C]0.7711[/C][C]0.222222[/C][/ROW]
[ROW][C]34[/C][C]0.00852[/C][C]0.059[/C][C]0.476588[/C][/ROW]
[ROW][C]35[/C][C]-0.011794[/C][C]-0.0817[/C][C]0.467608[/C][/ROW]
[ROW][C]36[/C][C]-0.06229[/C][C]-0.4316[/C][C]0.333996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60360&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60360&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
10.8723866.04410
2-0.678018-4.69741.1e-05
30.3140842.1760.017253
40.3348812.32010.012316
50.0524110.36310.359056
6-0.149421-1.03520.152877
7-0.175773-1.21780.114628
8-0.100555-0.69670.244686
9-0.119562-0.82840.205786
10-0.150093-1.03990.151804
11-0.035204-0.24390.404173
120.0024170.01670.493354
130.1691711.1720.123481
14-0.048594-0.33670.368916
150.0204070.14140.44408
160.021320.14770.441595
170.149571.03630.152638
18-0.233067-1.61470.056461
19-0.072798-0.50440.308157
200.1036430.71810.2381
21-0.184568-1.27870.103571
220.0532650.3690.356864
23-0.032944-0.22820.410213
24-0.037133-0.25730.399037
25-0.026386-0.18280.427859
260.0179580.12440.450754
27-0.129985-0.90060.186158
280.1059810.73430.233182
29-0.043316-0.30010.382697
30-0.030155-0.20890.417697
310.0466130.32290.374069
32-0.102509-0.71020.240506
330.1112940.77110.222222
340.008520.0590.476588
35-0.011794-0.08170.467608
36-0.06229-0.43160.333996


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; 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')