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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 computationTue, 01 Dec 2009 09:52:15 -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/01/t1259686395lb7zma9y0eydio2.htm/, Retrieved Fri, 26 Apr 2024 22:09:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62123, Retrieved Fri, 26 Apr 2024 22:09:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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 berekening 2 TVD] [2009-11-25 11:17:40] [42ad1186d39724f834063794eac7cea3]
-               [(Partial) Autocorrelation Function] [BDM2] [2009-11-25 17:12:44] [f5d341d4bbba73282fc6e80153a6d315]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-01 16:52:15] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.3
106.3
94
102.8
102
105.1
92.4
81.4
105.8
120.3
100.7
88.8
94.3
99.9
103.4
103.3
98.8
104.2
91.2
74.7
108.5
114.5
96.9
89.6
97.1
100.3
122.6
115.4
109
129.1
102.8
96.2
127.7
128.9
126.5
119.8
113.2
114.1
134.1
130
121.8
132.1
105.3
103
117.1
126.3
138.1
119.5
138
135.5
178.6
162.2
176.9
204.9
132.2
142.5
164.3
174.9
175.4
143

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=62123&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=62123&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62123&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
1-0.242672-1.8640.03365
2-0.28492-2.18850.016302
30.0575080.44170.330149
4-0.136823-1.0510.148781
50.2147631.64960.052167
6-0.025234-0.19380.42349
70.0501960.38560.350602
8-0.007801-0.05990.47621
9-0.006827-0.05240.479177
10-0.312357-2.39930.009803
11-0.039862-0.30620.380272
120.4854863.72910.000217
13-0.149931-1.15160.127058
14-0.097795-0.75120.227765
15-0.036765-0.28240.389312
16-0.104813-0.80510.212001
170.1206480.92670.178924
180.060620.46560.321598
19-0.016288-0.12510.45043
200.0475030.36490.358253
210.0620390.47650.317727
22-0.324734-2.49430.00772
230.0354520.27230.393167
240.3321992.55170.006666
25-0.090342-0.69390.245224
26-0.001772-0.01360.494592
27-0.094618-0.72680.235118
28-0.063764-0.48980.313054
290.099150.76160.224671
30-0.012766-0.09810.461109
31-0.025231-0.19380.423497
320.1218610.9360.176536
33-0.01356-0.10420.458698
34-0.253288-1.94550.02824
350.0577920.44390.329365
360.1400951.07610.143135

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.242672 & -1.864 & 0.03365 \tabularnewline
2 & -0.28492 & -2.1885 & 0.016302 \tabularnewline
3 & 0.057508 & 0.4417 & 0.330149 \tabularnewline
4 & -0.136823 & -1.051 & 0.148781 \tabularnewline
5 & 0.214763 & 1.6496 & 0.052167 \tabularnewline
6 & -0.025234 & -0.1938 & 0.42349 \tabularnewline
7 & 0.050196 & 0.3856 & 0.350602 \tabularnewline
8 & -0.007801 & -0.0599 & 0.47621 \tabularnewline
9 & -0.006827 & -0.0524 & 0.479177 \tabularnewline
10 & -0.312357 & -2.3993 & 0.009803 \tabularnewline
11 & -0.039862 & -0.3062 & 0.380272 \tabularnewline
12 & 0.485486 & 3.7291 & 0.000217 \tabularnewline
13 & -0.149931 & -1.1516 & 0.127058 \tabularnewline
14 & -0.097795 & -0.7512 & 0.227765 \tabularnewline
15 & -0.036765 & -0.2824 & 0.389312 \tabularnewline
16 & -0.104813 & -0.8051 & 0.212001 \tabularnewline
17 & 0.120648 & 0.9267 & 0.178924 \tabularnewline
18 & 0.06062 & 0.4656 & 0.321598 \tabularnewline
19 & -0.016288 & -0.1251 & 0.45043 \tabularnewline
20 & 0.047503 & 0.3649 & 0.358253 \tabularnewline
21 & 0.062039 & 0.4765 & 0.317727 \tabularnewline
22 & -0.324734 & -2.4943 & 0.00772 \tabularnewline
23 & 0.035452 & 0.2723 & 0.393167 \tabularnewline
24 & 0.332199 & 2.5517 & 0.006666 \tabularnewline
25 & -0.090342 & -0.6939 & 0.245224 \tabularnewline
26 & -0.001772 & -0.0136 & 0.494592 \tabularnewline
27 & -0.094618 & -0.7268 & 0.235118 \tabularnewline
28 & -0.063764 & -0.4898 & 0.313054 \tabularnewline
29 & 0.09915 & 0.7616 & 0.224671 \tabularnewline
30 & -0.012766 & -0.0981 & 0.461109 \tabularnewline
31 & -0.025231 & -0.1938 & 0.423497 \tabularnewline
32 & 0.121861 & 0.936 & 0.176536 \tabularnewline
33 & -0.01356 & -0.1042 & 0.458698 \tabularnewline
34 & -0.253288 & -1.9455 & 0.02824 \tabularnewline
35 & 0.057792 & 0.4439 & 0.329365 \tabularnewline
36 & 0.140095 & 1.0761 & 0.143135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62123&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]-0.242672[/C][C]-1.864[/C][C]0.03365[/C][/ROW]
[ROW][C]2[/C][C]-0.28492[/C][C]-2.1885[/C][C]0.016302[/C][/ROW]
[ROW][C]3[/C][C]0.057508[/C][C]0.4417[/C][C]0.330149[/C][/ROW]
[ROW][C]4[/C][C]-0.136823[/C][C]-1.051[/C][C]0.148781[/C][/ROW]
[ROW][C]5[/C][C]0.214763[/C][C]1.6496[/C][C]0.052167[/C][/ROW]
[ROW][C]6[/C][C]-0.025234[/C][C]-0.1938[/C][C]0.42349[/C][/ROW]
[ROW][C]7[/C][C]0.050196[/C][C]0.3856[/C][C]0.350602[/C][/ROW]
[ROW][C]8[/C][C]-0.007801[/C][C]-0.0599[/C][C]0.47621[/C][/ROW]
[ROW][C]9[/C][C]-0.006827[/C][C]-0.0524[/C][C]0.479177[/C][/ROW]
[ROW][C]10[/C][C]-0.312357[/C][C]-2.3993[/C][C]0.009803[/C][/ROW]
[ROW][C]11[/C][C]-0.039862[/C][C]-0.3062[/C][C]0.380272[/C][/ROW]
[ROW][C]12[/C][C]0.485486[/C][C]3.7291[/C][C]0.000217[/C][/ROW]
[ROW][C]13[/C][C]-0.149931[/C][C]-1.1516[/C][C]0.127058[/C][/ROW]
[ROW][C]14[/C][C]-0.097795[/C][C]-0.7512[/C][C]0.227765[/C][/ROW]
[ROW][C]15[/C][C]-0.036765[/C][C]-0.2824[/C][C]0.389312[/C][/ROW]
[ROW][C]16[/C][C]-0.104813[/C][C]-0.8051[/C][C]0.212001[/C][/ROW]
[ROW][C]17[/C][C]0.120648[/C][C]0.9267[/C][C]0.178924[/C][/ROW]
[ROW][C]18[/C][C]0.06062[/C][C]0.4656[/C][C]0.321598[/C][/ROW]
[ROW][C]19[/C][C]-0.016288[/C][C]-0.1251[/C][C]0.45043[/C][/ROW]
[ROW][C]20[/C][C]0.047503[/C][C]0.3649[/C][C]0.358253[/C][/ROW]
[ROW][C]21[/C][C]0.062039[/C][C]0.4765[/C][C]0.317727[/C][/ROW]
[ROW][C]22[/C][C]-0.324734[/C][C]-2.4943[/C][C]0.00772[/C][/ROW]
[ROW][C]23[/C][C]0.035452[/C][C]0.2723[/C][C]0.393167[/C][/ROW]
[ROW][C]24[/C][C]0.332199[/C][C]2.5517[/C][C]0.006666[/C][/ROW]
[ROW][C]25[/C][C]-0.090342[/C][C]-0.6939[/C][C]0.245224[/C][/ROW]
[ROW][C]26[/C][C]-0.001772[/C][C]-0.0136[/C][C]0.494592[/C][/ROW]
[ROW][C]27[/C][C]-0.094618[/C][C]-0.7268[/C][C]0.235118[/C][/ROW]
[ROW][C]28[/C][C]-0.063764[/C][C]-0.4898[/C][C]0.313054[/C][/ROW]
[ROW][C]29[/C][C]0.09915[/C][C]0.7616[/C][C]0.224671[/C][/ROW]
[ROW][C]30[/C][C]-0.012766[/C][C]-0.0981[/C][C]0.461109[/C][/ROW]
[ROW][C]31[/C][C]-0.025231[/C][C]-0.1938[/C][C]0.423497[/C][/ROW]
[ROW][C]32[/C][C]0.121861[/C][C]0.936[/C][C]0.176536[/C][/ROW]
[ROW][C]33[/C][C]-0.01356[/C][C]-0.1042[/C][C]0.458698[/C][/ROW]
[ROW][C]34[/C][C]-0.253288[/C][C]-1.9455[/C][C]0.02824[/C][/ROW]
[ROW][C]35[/C][C]0.057792[/C][C]0.4439[/C][C]0.329365[/C][/ROW]
[ROW][C]36[/C][C]0.140095[/C][C]1.0761[/C][C]0.143135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62123&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62123&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
1-0.242672-1.8640.03365
2-0.28492-2.18850.016302
30.0575080.44170.330149
4-0.136823-1.0510.148781
50.2147631.64960.052167
6-0.025234-0.19380.42349
70.0501960.38560.350602
8-0.007801-0.05990.47621
9-0.006827-0.05240.479177
10-0.312357-2.39930.009803
11-0.039862-0.30620.380272
120.4854863.72910.000217
13-0.149931-1.15160.127058
14-0.097795-0.75120.227765
15-0.036765-0.28240.389312
16-0.104813-0.80510.212001
170.1206480.92670.178924
180.060620.46560.321598
19-0.016288-0.12510.45043
200.0475030.36490.358253
210.0620390.47650.317727
22-0.324734-2.49430.00772
230.0354520.27230.393167
240.3321992.55170.006666
25-0.090342-0.69390.245224
26-0.001772-0.01360.494592
27-0.094618-0.72680.235118
28-0.063764-0.48980.313054
290.099150.76160.224671
30-0.012766-0.09810.461109
31-0.025231-0.19380.423497
320.1218610.9360.176536
33-0.01356-0.10420.458698
34-0.253288-1.94550.02824
350.0577920.44390.329365
360.1400951.07610.143135






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.242672-1.8640.03365
2-0.365324-2.80610.003391
3-0.153949-1.18250.120874
4-0.339766-2.60980.005732
50.0324040.24890.40215
6-0.110409-0.84810.199914
70.1661821.27650.103396
80.0387390.29760.383542
90.2331911.79120.039197
10-0.424608-3.26150.000922
11-0.286821-2.20310.015752
120.0469490.36060.359836
13-0.033531-0.25760.398822
14-0.0526-0.4040.343826
150.0265610.2040.419519
16-0.028952-0.22240.41239
17-0.105581-0.8110.210317
180.0390610.30.382604
19-0.078638-0.6040.27407
20-0.03725-0.28610.387894
210.0935160.71830.237701
22-0.079653-0.61180.271502
23-0.102112-0.78430.21799
240.0608460.46740.320978
250.0230730.17720.429968
260.0021190.01630.493535
270.0158780.1220.451673
280.0757580.58190.281424
29-0.025375-0.19490.423068
30-0.044649-0.3430.366427
31-0.065194-0.50080.309199
32-0.001093-0.00840.496665
33-0.076508-0.58770.279497
340.0249990.1920.424192
35-0.016685-0.12820.449229
36-0.040012-0.30730.379834

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.242672 & -1.864 & 0.03365 \tabularnewline
2 & -0.365324 & -2.8061 & 0.003391 \tabularnewline
3 & -0.153949 & -1.1825 & 0.120874 \tabularnewline
4 & -0.339766 & -2.6098 & 0.005732 \tabularnewline
5 & 0.032404 & 0.2489 & 0.40215 \tabularnewline
6 & -0.110409 & -0.8481 & 0.199914 \tabularnewline
7 & 0.166182 & 1.2765 & 0.103396 \tabularnewline
8 & 0.038739 & 0.2976 & 0.383542 \tabularnewline
9 & 0.233191 & 1.7912 & 0.039197 \tabularnewline
10 & -0.424608 & -3.2615 & 0.000922 \tabularnewline
11 & -0.286821 & -2.2031 & 0.015752 \tabularnewline
12 & 0.046949 & 0.3606 & 0.359836 \tabularnewline
13 & -0.033531 & -0.2576 & 0.398822 \tabularnewline
14 & -0.0526 & -0.404 & 0.343826 \tabularnewline
15 & 0.026561 & 0.204 & 0.419519 \tabularnewline
16 & -0.028952 & -0.2224 & 0.41239 \tabularnewline
17 & -0.105581 & -0.811 & 0.210317 \tabularnewline
18 & 0.039061 & 0.3 & 0.382604 \tabularnewline
19 & -0.078638 & -0.604 & 0.27407 \tabularnewline
20 & -0.03725 & -0.2861 & 0.387894 \tabularnewline
21 & 0.093516 & 0.7183 & 0.237701 \tabularnewline
22 & -0.079653 & -0.6118 & 0.271502 \tabularnewline
23 & -0.102112 & -0.7843 & 0.21799 \tabularnewline
24 & 0.060846 & 0.4674 & 0.320978 \tabularnewline
25 & 0.023073 & 0.1772 & 0.429968 \tabularnewline
26 & 0.002119 & 0.0163 & 0.493535 \tabularnewline
27 & 0.015878 & 0.122 & 0.451673 \tabularnewline
28 & 0.075758 & 0.5819 & 0.281424 \tabularnewline
29 & -0.025375 & -0.1949 & 0.423068 \tabularnewline
30 & -0.044649 & -0.343 & 0.366427 \tabularnewline
31 & -0.065194 & -0.5008 & 0.309199 \tabularnewline
32 & -0.001093 & -0.0084 & 0.496665 \tabularnewline
33 & -0.076508 & -0.5877 & 0.279497 \tabularnewline
34 & 0.024999 & 0.192 & 0.424192 \tabularnewline
35 & -0.016685 & -0.1282 & 0.449229 \tabularnewline
36 & -0.040012 & -0.3073 & 0.379834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62123&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]-0.242672[/C][C]-1.864[/C][C]0.03365[/C][/ROW]
[ROW][C]2[/C][C]-0.365324[/C][C]-2.8061[/C][C]0.003391[/C][/ROW]
[ROW][C]3[/C][C]-0.153949[/C][C]-1.1825[/C][C]0.120874[/C][/ROW]
[ROW][C]4[/C][C]-0.339766[/C][C]-2.6098[/C][C]0.005732[/C][/ROW]
[ROW][C]5[/C][C]0.032404[/C][C]0.2489[/C][C]0.40215[/C][/ROW]
[ROW][C]6[/C][C]-0.110409[/C][C]-0.8481[/C][C]0.199914[/C][/ROW]
[ROW][C]7[/C][C]0.166182[/C][C]1.2765[/C][C]0.103396[/C][/ROW]
[ROW][C]8[/C][C]0.038739[/C][C]0.2976[/C][C]0.383542[/C][/ROW]
[ROW][C]9[/C][C]0.233191[/C][C]1.7912[/C][C]0.039197[/C][/ROW]
[ROW][C]10[/C][C]-0.424608[/C][C]-3.2615[/C][C]0.000922[/C][/ROW]
[ROW][C]11[/C][C]-0.286821[/C][C]-2.2031[/C][C]0.015752[/C][/ROW]
[ROW][C]12[/C][C]0.046949[/C][C]0.3606[/C][C]0.359836[/C][/ROW]
[ROW][C]13[/C][C]-0.033531[/C][C]-0.2576[/C][C]0.398822[/C][/ROW]
[ROW][C]14[/C][C]-0.0526[/C][C]-0.404[/C][C]0.343826[/C][/ROW]
[ROW][C]15[/C][C]0.026561[/C][C]0.204[/C][C]0.419519[/C][/ROW]
[ROW][C]16[/C][C]-0.028952[/C][C]-0.2224[/C][C]0.41239[/C][/ROW]
[ROW][C]17[/C][C]-0.105581[/C][C]-0.811[/C][C]0.210317[/C][/ROW]
[ROW][C]18[/C][C]0.039061[/C][C]0.3[/C][C]0.382604[/C][/ROW]
[ROW][C]19[/C][C]-0.078638[/C][C]-0.604[/C][C]0.27407[/C][/ROW]
[ROW][C]20[/C][C]-0.03725[/C][C]-0.2861[/C][C]0.387894[/C][/ROW]
[ROW][C]21[/C][C]0.093516[/C][C]0.7183[/C][C]0.237701[/C][/ROW]
[ROW][C]22[/C][C]-0.079653[/C][C]-0.6118[/C][C]0.271502[/C][/ROW]
[ROW][C]23[/C][C]-0.102112[/C][C]-0.7843[/C][C]0.21799[/C][/ROW]
[ROW][C]24[/C][C]0.060846[/C][C]0.4674[/C][C]0.320978[/C][/ROW]
[ROW][C]25[/C][C]0.023073[/C][C]0.1772[/C][C]0.429968[/C][/ROW]
[ROW][C]26[/C][C]0.002119[/C][C]0.0163[/C][C]0.493535[/C][/ROW]
[ROW][C]27[/C][C]0.015878[/C][C]0.122[/C][C]0.451673[/C][/ROW]
[ROW][C]28[/C][C]0.075758[/C][C]0.5819[/C][C]0.281424[/C][/ROW]
[ROW][C]29[/C][C]-0.025375[/C][C]-0.1949[/C][C]0.423068[/C][/ROW]
[ROW][C]30[/C][C]-0.044649[/C][C]-0.343[/C][C]0.366427[/C][/ROW]
[ROW][C]31[/C][C]-0.065194[/C][C]-0.5008[/C][C]0.309199[/C][/ROW]
[ROW][C]32[/C][C]-0.001093[/C][C]-0.0084[/C][C]0.496665[/C][/ROW]
[ROW][C]33[/C][C]-0.076508[/C][C]-0.5877[/C][C]0.279497[/C][/ROW]
[ROW][C]34[/C][C]0.024999[/C][C]0.192[/C][C]0.424192[/C][/ROW]
[ROW][C]35[/C][C]-0.016685[/C][C]-0.1282[/C][C]0.449229[/C][/ROW]
[ROW][C]36[/C][C]-0.040012[/C][C]-0.3073[/C][C]0.379834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62123&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62123&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
1-0.242672-1.8640.03365
2-0.365324-2.80610.003391
3-0.153949-1.18250.120874
4-0.339766-2.60980.005732
50.0324040.24890.40215
6-0.110409-0.84810.199914
70.1661821.27650.103396
80.0387390.29760.383542
90.2331911.79120.039197
10-0.424608-3.26150.000922
11-0.286821-2.20310.015752
120.0469490.36060.359836
13-0.033531-0.25760.398822
14-0.0526-0.4040.343826
150.0265610.2040.419519
16-0.028952-0.22240.41239
17-0.105581-0.8110.210317
180.0390610.30.382604
19-0.078638-0.6040.27407
20-0.03725-0.28610.387894
210.0935160.71830.237701
22-0.079653-0.61180.271502
23-0.102112-0.78430.21799
240.0608460.46740.320978
250.0230730.17720.429968
260.0021190.01630.493535
270.0158780.1220.451673
280.0757580.58190.281424
29-0.025375-0.19490.423068
30-0.044649-0.3430.366427
31-0.065194-0.50080.309199
32-0.001093-0.00840.496665
33-0.076508-0.58770.279497
340.0249990.1920.424192
35-0.016685-0.12820.449229
36-0.040012-0.30730.379834


Figures (Output of Computation)

Input Parameters & R Code

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