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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 computationMon, 21 Dec 2009 07:27:06 -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/21/t1261405725ea2yt16zkm1fvuh.htm/, Retrieved Sun, 05 May 2024 10:58:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70197, Retrieved Sun, 05 May 2024 10:58:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsShw; Paper toepassing ACF d = D = 1
Estimated Impact107

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]
-    D        [(Partial) Autocorrelation Function] [Ws8.1 ACF1] [2009-11-25 19:12:20] [e0fc65a5811681d807296d590d5b45de]
-    D          [(Partial) Autocorrelation Function] [Paper stationair ...] [2009-12-19 17:48:37] [e0fc65a5811681d807296d590d5b45de]
-   PD              [(Partial) Autocorrelation Function] [Paper toepassing ...] [2009-12-21 14:27:06] [51108381f3361ca8af49c4f74052c840] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.1
103.1
103.3
103.5
103.3
103.5
103.8
103.9
103.9
104.2
104.6
104.9
105.2
105.2
105.6
105.6
106.2
106.3
106.4
106.9
107.2
107.3
107.3
107.4
107.55
107.87
108.37
108.38
107.92
108.03
108.14
108.3
108.64
108.66
109.04
109.03
109.03
109.54
109.75
109.83
109.65
109.82
109.95
110.12
110.15
110.2
109.99
110.14
110.14
110.81
110.97
110.99
109.73
109.81
110.02
110.18
110.21
110.25
110.36
110.51
110.64
110.95
111.18
111.19
111.69
111.7
111.83
111.77
111.73
112.01
111.86
112.04

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=70197&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=70197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70197&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
1-0.062381-0.47920.3168
2-0.0265-0.20360.419703
3-0.17039-1.30880.09784
40.0058150.04470.482262
50.057990.44540.32882
60.037820.29050.386227
70.0368040.28270.389201
8-0.009128-0.07010.472171
90.0168550.12950.448715
100.0473790.36390.358609
11-0.016795-0.1290.448895
12-0.496018-3.810.000167
130.0243380.18690.426174
140.003420.02630.489564
150.0978670.75170.227601
160.0346540.26620.395513
170.0099980.07680.469523
18-0.050888-0.39090.348647
19-0.065173-0.50060.309256
20-0.054135-0.41580.339525
210.0543190.41720.339012
220.0048860.03750.485094
230.0458380.35210.363012
240.2575141.9780.026302
25-0.000641-0.00490.498043
26-0.083642-0.64250.261529
27-0.063429-0.48720.313958
28-0.017268-0.13260.447467
290.0372380.2860.387927
300.0409260.31440.377179
310.0209880.16120.436238
32-0.05148-0.39540.346978
33-0.069828-0.53640.296863
340.0097440.07480.470295
350.031810.24430.403908
36-0.368707-2.83210.003158

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.062381 & -0.4792 & 0.3168 \tabularnewline
2 & -0.0265 & -0.2036 & 0.419703 \tabularnewline
3 & -0.17039 & -1.3088 & 0.09784 \tabularnewline
4 & 0.005815 & 0.0447 & 0.482262 \tabularnewline
5 & 0.05799 & 0.4454 & 0.32882 \tabularnewline
6 & 0.03782 & 0.2905 & 0.386227 \tabularnewline
7 & 0.036804 & 0.2827 & 0.389201 \tabularnewline
8 & -0.009128 & -0.0701 & 0.472171 \tabularnewline
9 & 0.016855 & 0.1295 & 0.448715 \tabularnewline
10 & 0.047379 & 0.3639 & 0.358609 \tabularnewline
11 & -0.016795 & -0.129 & 0.448895 \tabularnewline
12 & -0.496018 & -3.81 & 0.000167 \tabularnewline
13 & 0.024338 & 0.1869 & 0.426174 \tabularnewline
14 & 0.00342 & 0.0263 & 0.489564 \tabularnewline
15 & 0.097867 & 0.7517 & 0.227601 \tabularnewline
16 & 0.034654 & 0.2662 & 0.395513 \tabularnewline
17 & 0.009998 & 0.0768 & 0.469523 \tabularnewline
18 & -0.050888 & -0.3909 & 0.348647 \tabularnewline
19 & -0.065173 & -0.5006 & 0.309256 \tabularnewline
20 & -0.054135 & -0.4158 & 0.339525 \tabularnewline
21 & 0.054319 & 0.4172 & 0.339012 \tabularnewline
22 & 0.004886 & 0.0375 & 0.485094 \tabularnewline
23 & 0.045838 & 0.3521 & 0.363012 \tabularnewline
24 & 0.257514 & 1.978 & 0.026302 \tabularnewline
25 & -0.000641 & -0.0049 & 0.498043 \tabularnewline
26 & -0.083642 & -0.6425 & 0.261529 \tabularnewline
27 & -0.063429 & -0.4872 & 0.313958 \tabularnewline
28 & -0.017268 & -0.1326 & 0.447467 \tabularnewline
29 & 0.037238 & 0.286 & 0.387927 \tabularnewline
30 & 0.040926 & 0.3144 & 0.377179 \tabularnewline
31 & 0.020988 & 0.1612 & 0.436238 \tabularnewline
32 & -0.05148 & -0.3954 & 0.346978 \tabularnewline
33 & -0.069828 & -0.5364 & 0.296863 \tabularnewline
34 & 0.009744 & 0.0748 & 0.470295 \tabularnewline
35 & 0.03181 & 0.2443 & 0.403908 \tabularnewline
36 & -0.368707 & -2.8321 & 0.003158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70197&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]-0.062381[/C][C]-0.4792[/C][C]0.3168[/C][/ROW]
[ROW][C]2[/C][C]-0.0265[/C][C]-0.2036[/C][C]0.419703[/C][/ROW]
[ROW][C]3[/C][C]-0.17039[/C][C]-1.3088[/C][C]0.09784[/C][/ROW]
[ROW][C]4[/C][C]0.005815[/C][C]0.0447[/C][C]0.482262[/C][/ROW]
[ROW][C]5[/C][C]0.05799[/C][C]0.4454[/C][C]0.32882[/C][/ROW]
[ROW][C]6[/C][C]0.03782[/C][C]0.2905[/C][C]0.386227[/C][/ROW]
[ROW][C]7[/C][C]0.036804[/C][C]0.2827[/C][C]0.389201[/C][/ROW]
[ROW][C]8[/C][C]-0.009128[/C][C]-0.0701[/C][C]0.472171[/C][/ROW]
[ROW][C]9[/C][C]0.016855[/C][C]0.1295[/C][C]0.448715[/C][/ROW]
[ROW][C]10[/C][C]0.047379[/C][C]0.3639[/C][C]0.358609[/C][/ROW]
[ROW][C]11[/C][C]-0.016795[/C][C]-0.129[/C][C]0.448895[/C][/ROW]
[ROW][C]12[/C][C]-0.496018[/C][C]-3.81[/C][C]0.000167[/C][/ROW]
[ROW][C]13[/C][C]0.024338[/C][C]0.1869[/C][C]0.426174[/C][/ROW]
[ROW][C]14[/C][C]0.00342[/C][C]0.0263[/C][C]0.489564[/C][/ROW]
[ROW][C]15[/C][C]0.097867[/C][C]0.7517[/C][C]0.227601[/C][/ROW]
[ROW][C]16[/C][C]0.034654[/C][C]0.2662[/C][C]0.395513[/C][/ROW]
[ROW][C]17[/C][C]0.009998[/C][C]0.0768[/C][C]0.469523[/C][/ROW]
[ROW][C]18[/C][C]-0.050888[/C][C]-0.3909[/C][C]0.348647[/C][/ROW]
[ROW][C]19[/C][C]-0.065173[/C][C]-0.5006[/C][C]0.309256[/C][/ROW]
[ROW][C]20[/C][C]-0.054135[/C][C]-0.4158[/C][C]0.339525[/C][/ROW]
[ROW][C]21[/C][C]0.054319[/C][C]0.4172[/C][C]0.339012[/C][/ROW]
[ROW][C]22[/C][C]0.004886[/C][C]0.0375[/C][C]0.485094[/C][/ROW]
[ROW][C]23[/C][C]0.045838[/C][C]0.3521[/C][C]0.363012[/C][/ROW]
[ROW][C]24[/C][C]0.257514[/C][C]1.978[/C][C]0.026302[/C][/ROW]
[ROW][C]25[/C][C]-0.000641[/C][C]-0.0049[/C][C]0.498043[/C][/ROW]
[ROW][C]26[/C][C]-0.083642[/C][C]-0.6425[/C][C]0.261529[/C][/ROW]
[ROW][C]27[/C][C]-0.063429[/C][C]-0.4872[/C][C]0.313958[/C][/ROW]
[ROW][C]28[/C][C]-0.017268[/C][C]-0.1326[/C][C]0.447467[/C][/ROW]
[ROW][C]29[/C][C]0.037238[/C][C]0.286[/C][C]0.387927[/C][/ROW]
[ROW][C]30[/C][C]0.040926[/C][C]0.3144[/C][C]0.377179[/C][/ROW]
[ROW][C]31[/C][C]0.020988[/C][C]0.1612[/C][C]0.436238[/C][/ROW]
[ROW][C]32[/C][C]-0.05148[/C][C]-0.3954[/C][C]0.346978[/C][/ROW]
[ROW][C]33[/C][C]-0.069828[/C][C]-0.5364[/C][C]0.296863[/C][/ROW]
[ROW][C]34[/C][C]0.009744[/C][C]0.0748[/C][C]0.470295[/C][/ROW]
[ROW][C]35[/C][C]0.03181[/C][C]0.2443[/C][C]0.403908[/C][/ROW]
[ROW][C]36[/C][C]-0.368707[/C][C]-2.8321[/C][C]0.003158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70197&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
1-0.062381-0.47920.3168
2-0.0265-0.20360.419703
3-0.17039-1.30880.09784
40.0058150.04470.482262
50.057990.44540.32882
60.037820.29050.386227
70.0368040.28270.389201
8-0.009128-0.07010.472171
90.0168550.12950.448715
100.0473790.36390.358609
11-0.016795-0.1290.448895
12-0.496018-3.810.000167
130.0243380.18690.426174
140.003420.02630.489564
150.0978670.75170.227601
160.0346540.26620.395513
170.0099980.07680.469523
18-0.050888-0.39090.348647
19-0.065173-0.50060.309256
20-0.054135-0.41580.339525
210.0543190.41720.339012
220.0048860.03750.485094
230.0458380.35210.363012
240.2575141.9780.026302
25-0.000641-0.00490.498043
26-0.083642-0.64250.261529
27-0.063429-0.48720.313958
28-0.017268-0.13260.447467
290.0372380.2860.387927
300.0409260.31440.377179
310.0209880.16120.436238
32-0.05148-0.39540.346978
33-0.069828-0.53640.296863
340.0097440.07480.470295
350.031810.24430.403908
36-0.368707-2.83210.003158






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.062381-0.47920.3168
2-0.03051-0.23440.407761
3-0.17484-1.3430.092213
4-0.01872-0.14380.443079
50.0470040.3610.359679
60.0156390.12010.452397
70.0439270.33740.368502
80.0172680.13260.447465
90.0309470.23770.406464
100.0647530.49740.310385
11-0.00906-0.06960.472378
12-0.514901-3.9550.000104
13-0.055204-0.4240.336544
14-0.039962-0.3070.379978
15-0.107961-0.82930.205149
160.0488790.37540.354338
170.1136020.87260.193211
180.0118780.09120.463806
190.0246070.1890.425367
20-0.054699-0.42020.337951
210.0128090.09840.460977
220.0392350.30140.382095
23-0.019488-0.14970.440759
240.0295080.22670.410737
250.0655560.50350.308227
26-0.114028-0.87590.192327
27-0.031388-0.24110.405158
280.0254450.19540.422857
290.0204670.15720.43781
300.0102660.07890.468706
31-0.024347-0.1870.426145
32-0.140775-1.08130.141979
33-0.030896-0.23730.406616
34-0.002577-0.01980.492138
350.0458230.3520.363055
36-0.304948-2.34230.011278

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.062381 & -0.4792 & 0.3168 \tabularnewline
2 & -0.03051 & -0.2344 & 0.407761 \tabularnewline
3 & -0.17484 & -1.343 & 0.092213 \tabularnewline
4 & -0.01872 & -0.1438 & 0.443079 \tabularnewline
5 & 0.047004 & 0.361 & 0.359679 \tabularnewline
6 & 0.015639 & 0.1201 & 0.452397 \tabularnewline
7 & 0.043927 & 0.3374 & 0.368502 \tabularnewline
8 & 0.017268 & 0.1326 & 0.447465 \tabularnewline
9 & 0.030947 & 0.2377 & 0.406464 \tabularnewline
10 & 0.064753 & 0.4974 & 0.310385 \tabularnewline
11 & -0.00906 & -0.0696 & 0.472378 \tabularnewline
12 & -0.514901 & -3.955 & 0.000104 \tabularnewline
13 & -0.055204 & -0.424 & 0.336544 \tabularnewline
14 & -0.039962 & -0.307 & 0.379978 \tabularnewline
15 & -0.107961 & -0.8293 & 0.205149 \tabularnewline
16 & 0.048879 & 0.3754 & 0.354338 \tabularnewline
17 & 0.113602 & 0.8726 & 0.193211 \tabularnewline
18 & 0.011878 & 0.0912 & 0.463806 \tabularnewline
19 & 0.024607 & 0.189 & 0.425367 \tabularnewline
20 & -0.054699 & -0.4202 & 0.337951 \tabularnewline
21 & 0.012809 & 0.0984 & 0.460977 \tabularnewline
22 & 0.039235 & 0.3014 & 0.382095 \tabularnewline
23 & -0.019488 & -0.1497 & 0.440759 \tabularnewline
24 & 0.029508 & 0.2267 & 0.410737 \tabularnewline
25 & 0.065556 & 0.5035 & 0.308227 \tabularnewline
26 & -0.114028 & -0.8759 & 0.192327 \tabularnewline
27 & -0.031388 & -0.2411 & 0.405158 \tabularnewline
28 & 0.025445 & 0.1954 & 0.422857 \tabularnewline
29 & 0.020467 & 0.1572 & 0.43781 \tabularnewline
30 & 0.010266 & 0.0789 & 0.468706 \tabularnewline
31 & -0.024347 & -0.187 & 0.426145 \tabularnewline
32 & -0.140775 & -1.0813 & 0.141979 \tabularnewline
33 & -0.030896 & -0.2373 & 0.406616 \tabularnewline
34 & -0.002577 & -0.0198 & 0.492138 \tabularnewline
35 & 0.045823 & 0.352 & 0.363055 \tabularnewline
36 & -0.304948 & -2.3423 & 0.011278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70197&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]-0.062381[/C][C]-0.4792[/C][C]0.3168[/C][/ROW]
[ROW][C]2[/C][C]-0.03051[/C][C]-0.2344[/C][C]0.407761[/C][/ROW]
[ROW][C]3[/C][C]-0.17484[/C][C]-1.343[/C][C]0.092213[/C][/ROW]
[ROW][C]4[/C][C]-0.01872[/C][C]-0.1438[/C][C]0.443079[/C][/ROW]
[ROW][C]5[/C][C]0.047004[/C][C]0.361[/C][C]0.359679[/C][/ROW]
[ROW][C]6[/C][C]0.015639[/C][C]0.1201[/C][C]0.452397[/C][/ROW]
[ROW][C]7[/C][C]0.043927[/C][C]0.3374[/C][C]0.368502[/C][/ROW]
[ROW][C]8[/C][C]0.017268[/C][C]0.1326[/C][C]0.447465[/C][/ROW]
[ROW][C]9[/C][C]0.030947[/C][C]0.2377[/C][C]0.406464[/C][/ROW]
[ROW][C]10[/C][C]0.064753[/C][C]0.4974[/C][C]0.310385[/C][/ROW]
[ROW][C]11[/C][C]-0.00906[/C][C]-0.0696[/C][C]0.472378[/C][/ROW]
[ROW][C]12[/C][C]-0.514901[/C][C]-3.955[/C][C]0.000104[/C][/ROW]
[ROW][C]13[/C][C]-0.055204[/C][C]-0.424[/C][C]0.336544[/C][/ROW]
[ROW][C]14[/C][C]-0.039962[/C][C]-0.307[/C][C]0.379978[/C][/ROW]
[ROW][C]15[/C][C]-0.107961[/C][C]-0.8293[/C][C]0.205149[/C][/ROW]
[ROW][C]16[/C][C]0.048879[/C][C]0.3754[/C][C]0.354338[/C][/ROW]
[ROW][C]17[/C][C]0.113602[/C][C]0.8726[/C][C]0.193211[/C][/ROW]
[ROW][C]18[/C][C]0.011878[/C][C]0.0912[/C][C]0.463806[/C][/ROW]
[ROW][C]19[/C][C]0.024607[/C][C]0.189[/C][C]0.425367[/C][/ROW]
[ROW][C]20[/C][C]-0.054699[/C][C]-0.4202[/C][C]0.337951[/C][/ROW]
[ROW][C]21[/C][C]0.012809[/C][C]0.0984[/C][C]0.460977[/C][/ROW]
[ROW][C]22[/C][C]0.039235[/C][C]0.3014[/C][C]0.382095[/C][/ROW]
[ROW][C]23[/C][C]-0.019488[/C][C]-0.1497[/C][C]0.440759[/C][/ROW]
[ROW][C]24[/C][C]0.029508[/C][C]0.2267[/C][C]0.410737[/C][/ROW]
[ROW][C]25[/C][C]0.065556[/C][C]0.5035[/C][C]0.308227[/C][/ROW]
[ROW][C]26[/C][C]-0.114028[/C][C]-0.8759[/C][C]0.192327[/C][/ROW]
[ROW][C]27[/C][C]-0.031388[/C][C]-0.2411[/C][C]0.405158[/C][/ROW]
[ROW][C]28[/C][C]0.025445[/C][C]0.1954[/C][C]0.422857[/C][/ROW]
[ROW][C]29[/C][C]0.020467[/C][C]0.1572[/C][C]0.43781[/C][/ROW]
[ROW][C]30[/C][C]0.010266[/C][C]0.0789[/C][C]0.468706[/C][/ROW]
[ROW][C]31[/C][C]-0.024347[/C][C]-0.187[/C][C]0.426145[/C][/ROW]
[ROW][C]32[/C][C]-0.140775[/C][C]-1.0813[/C][C]0.141979[/C][/ROW]
[ROW][C]33[/C][C]-0.030896[/C][C]-0.2373[/C][C]0.406616[/C][/ROW]
[ROW][C]34[/C][C]-0.002577[/C][C]-0.0198[/C][C]0.492138[/C][/ROW]
[ROW][C]35[/C][C]0.045823[/C][C]0.352[/C][C]0.363055[/C][/ROW]
[ROW][C]36[/C][C]-0.304948[/C][C]-2.3423[/C][C]0.011278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70197&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70197&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
1-0.062381-0.47920.3168
2-0.03051-0.23440.407761
3-0.17484-1.3430.092213
4-0.01872-0.14380.443079
50.0470040.3610.359679
60.0156390.12010.452397
70.0439270.33740.368502
80.0172680.13260.447465
90.0309470.23770.406464
100.0647530.49740.310385
11-0.00906-0.06960.472378
12-0.514901-3.9550.000104
13-0.055204-0.4240.336544
14-0.039962-0.3070.379978
15-0.107961-0.82930.205149
160.0488790.37540.354338
170.1136020.87260.193211
180.0118780.09120.463806
190.0246070.1890.425367
20-0.054699-0.42020.337951
210.0128090.09840.460977
220.0392350.30140.382095
23-0.019488-0.14970.440759
240.0295080.22670.410737
250.0655560.50350.308227
26-0.114028-0.87590.192327
27-0.031388-0.24110.405158
280.0254450.19540.422857
290.0204670.15720.43781
300.0102660.07890.468706
31-0.024347-0.1870.426145
32-0.140775-1.08130.141979
33-0.030896-0.23730.406616
34-0.002577-0.01980.492138
350.0458230.3520.363055
36-0.304948-2.34230.011278


Figures (Output of Computation)

Input Parameters & R Code

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