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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, 03 Dec 2009 05:15:21 -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/03/t12598425446bbzp7el37976de.htm/, Retrieved Sat, 20 Apr 2024 10:41:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62690, Retrieved Sat, 20 Apr 2024 10:41:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [] [2009-12-03 12:09:45] [875a981b2b01315c1c471abd4dd66675]
-   PD      [(Partial) Autocorrelation Function] [] [2009-12-03 12:13:55] [875a981b2b01315c1c471abd4dd66675]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 12:15:21] [8551abdd6804649d94d88b1829ac2b1a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
128.7
136.9
156.9
109.1
122.3
123.9
90.9
77.9
120.3
118.9
125.5
98.9
102.9
105.9
117.6
113.6
115.9
118.9
77.6
81.2
123.1
136.6
112.1
95.1
96.3
105.7
115.8
105.7
105.7
111.1
82.4
60
107.3
99.3
113.5
108.9
100.2
103.9
138.7
120.2
100.2
143.2
70.9
85.2
133
136.6
117.9
106.3
122.3
125.5
148.4
126.3
99.6
140.4
80.3
92.6
138.5
110.9
119.6
105
109
129.4
148.6
101.4
134.8
143.7
81.6
90.3
141.5
140.7
140.2
100.2
125.7
119.6
134.7
109
116.3
146.9
97.4
89.4
132.1
139.8
129
112.5
121.9
121.7
123.1
131.6
119.3
132.5
98.3
85.1
131.7
129.3
90.7
78.6
68.9
79.1
83.5
74.1
59.7
93.3
61.3
56.6
98.5

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=62690&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=62690&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62690&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
1-0.481223-4.61576e-06
20.0028650.02750.489069
30.0238650.22890.409725
4-0.039069-0.37470.354358
50.0673230.64570.260027
60.1353591.29830.098712
7-0.236807-2.27140.012728
80.0420990.40380.343648
90.0090090.08640.465662
100.0262980.25220.400709
110.1741141.670.049155
12-0.380274-3.64750.000219
130.1330611.27630.102535
140.0380320.36480.358054
150.0812820.77960.218805
16-0.103933-0.99690.160717
170.0174830.16770.433596
18-0.066047-0.63350.263989
190.0442970.42490.335956
200.1067321.02370.154322
210.0196480.18850.425466
22-0.245535-2.35510.010322
230.2232762.14160.017434
240.0151430.14530.442415
25-0.141633-1.35850.088813
260.1929461.85070.033713
27-0.176342-1.69140.047072
280.0229960.22060.412957
290.151881.45680.074291
30-0.108612-1.04180.150124
31-0.028624-0.27460.392138
32-0.027477-0.26350.39636
33-0.042527-0.40790.342146
340.2031091.94820.027222
35-0.095217-0.91330.181738
36-0.087953-0.84360.200535

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.481223 & -4.6157 & 6e-06 \tabularnewline
2 & 0.002865 & 0.0275 & 0.489069 \tabularnewline
3 & 0.023865 & 0.2289 & 0.409725 \tabularnewline
4 & -0.039069 & -0.3747 & 0.354358 \tabularnewline
5 & 0.067323 & 0.6457 & 0.260027 \tabularnewline
6 & 0.135359 & 1.2983 & 0.098712 \tabularnewline
7 & -0.236807 & -2.2714 & 0.012728 \tabularnewline
8 & 0.042099 & 0.4038 & 0.343648 \tabularnewline
9 & 0.009009 & 0.0864 & 0.465662 \tabularnewline
10 & 0.026298 & 0.2522 & 0.400709 \tabularnewline
11 & 0.174114 & 1.67 & 0.049155 \tabularnewline
12 & -0.380274 & -3.6475 & 0.000219 \tabularnewline
13 & 0.133061 & 1.2763 & 0.102535 \tabularnewline
14 & 0.038032 & 0.3648 & 0.358054 \tabularnewline
15 & 0.081282 & 0.7796 & 0.218805 \tabularnewline
16 & -0.103933 & -0.9969 & 0.160717 \tabularnewline
17 & 0.017483 & 0.1677 & 0.433596 \tabularnewline
18 & -0.066047 & -0.6335 & 0.263989 \tabularnewline
19 & 0.044297 & 0.4249 & 0.335956 \tabularnewline
20 & 0.106732 & 1.0237 & 0.154322 \tabularnewline
21 & 0.019648 & 0.1885 & 0.425466 \tabularnewline
22 & -0.245535 & -2.3551 & 0.010322 \tabularnewline
23 & 0.223276 & 2.1416 & 0.017434 \tabularnewline
24 & 0.015143 & 0.1453 & 0.442415 \tabularnewline
25 & -0.141633 & -1.3585 & 0.088813 \tabularnewline
26 & 0.192946 & 1.8507 & 0.033713 \tabularnewline
27 & -0.176342 & -1.6914 & 0.047072 \tabularnewline
28 & 0.022996 & 0.2206 & 0.412957 \tabularnewline
29 & 0.15188 & 1.4568 & 0.074291 \tabularnewline
30 & -0.108612 & -1.0418 & 0.150124 \tabularnewline
31 & -0.028624 & -0.2746 & 0.392138 \tabularnewline
32 & -0.027477 & -0.2635 & 0.39636 \tabularnewline
33 & -0.042527 & -0.4079 & 0.342146 \tabularnewline
34 & 0.203109 & 1.9482 & 0.027222 \tabularnewline
35 & -0.095217 & -0.9133 & 0.181738 \tabularnewline
36 & -0.087953 & -0.8436 & 0.200535 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62690&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]-0.481223[/C][C]-4.6157[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]0.002865[/C][C]0.0275[/C][C]0.489069[/C][/ROW]
[ROW][C]3[/C][C]0.023865[/C][C]0.2289[/C][C]0.409725[/C][/ROW]
[ROW][C]4[/C][C]-0.039069[/C][C]-0.3747[/C][C]0.354358[/C][/ROW]
[ROW][C]5[/C][C]0.067323[/C][C]0.6457[/C][C]0.260027[/C][/ROW]
[ROW][C]6[/C][C]0.135359[/C][C]1.2983[/C][C]0.098712[/C][/ROW]
[ROW][C]7[/C][C]-0.236807[/C][C]-2.2714[/C][C]0.012728[/C][/ROW]
[ROW][C]8[/C][C]0.042099[/C][C]0.4038[/C][C]0.343648[/C][/ROW]
[ROW][C]9[/C][C]0.009009[/C][C]0.0864[/C][C]0.465662[/C][/ROW]
[ROW][C]10[/C][C]0.026298[/C][C]0.2522[/C][C]0.400709[/C][/ROW]
[ROW][C]11[/C][C]0.174114[/C][C]1.67[/C][C]0.049155[/C][/ROW]
[ROW][C]12[/C][C]-0.380274[/C][C]-3.6475[/C][C]0.000219[/C][/ROW]
[ROW][C]13[/C][C]0.133061[/C][C]1.2763[/C][C]0.102535[/C][/ROW]
[ROW][C]14[/C][C]0.038032[/C][C]0.3648[/C][C]0.358054[/C][/ROW]
[ROW][C]15[/C][C]0.081282[/C][C]0.7796[/C][C]0.218805[/C][/ROW]
[ROW][C]16[/C][C]-0.103933[/C][C]-0.9969[/C][C]0.160717[/C][/ROW]
[ROW][C]17[/C][C]0.017483[/C][C]0.1677[/C][C]0.433596[/C][/ROW]
[ROW][C]18[/C][C]-0.066047[/C][C]-0.6335[/C][C]0.263989[/C][/ROW]
[ROW][C]19[/C][C]0.044297[/C][C]0.4249[/C][C]0.335956[/C][/ROW]
[ROW][C]20[/C][C]0.106732[/C][C]1.0237[/C][C]0.154322[/C][/ROW]
[ROW][C]21[/C][C]0.019648[/C][C]0.1885[/C][C]0.425466[/C][/ROW]
[ROW][C]22[/C][C]-0.245535[/C][C]-2.3551[/C][C]0.010322[/C][/ROW]
[ROW][C]23[/C][C]0.223276[/C][C]2.1416[/C][C]0.017434[/C][/ROW]
[ROW][C]24[/C][C]0.015143[/C][C]0.1453[/C][C]0.442415[/C][/ROW]
[ROW][C]25[/C][C]-0.141633[/C][C]-1.3585[/C][C]0.088813[/C][/ROW]
[ROW][C]26[/C][C]0.192946[/C][C]1.8507[/C][C]0.033713[/C][/ROW]
[ROW][C]27[/C][C]-0.176342[/C][C]-1.6914[/C][C]0.047072[/C][/ROW]
[ROW][C]28[/C][C]0.022996[/C][C]0.2206[/C][C]0.412957[/C][/ROW]
[ROW][C]29[/C][C]0.15188[/C][C]1.4568[/C][C]0.074291[/C][/ROW]
[ROW][C]30[/C][C]-0.108612[/C][C]-1.0418[/C][C]0.150124[/C][/ROW]
[ROW][C]31[/C][C]-0.028624[/C][C]-0.2746[/C][C]0.392138[/C][/ROW]
[ROW][C]32[/C][C]-0.027477[/C][C]-0.2635[/C][C]0.39636[/C][/ROW]
[ROW][C]33[/C][C]-0.042527[/C][C]-0.4079[/C][C]0.342146[/C][/ROW]
[ROW][C]34[/C][C]0.203109[/C][C]1.9482[/C][C]0.027222[/C][/ROW]
[ROW][C]35[/C][C]-0.095217[/C][C]-0.9133[/C][C]0.181738[/C][/ROW]
[ROW][C]36[/C][C]-0.087953[/C][C]-0.8436[/C][C]0.200535[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62690&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62690&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
1-0.481223-4.61576e-06
20.0028650.02750.489069
30.0238650.22890.409725
4-0.039069-0.37470.354358
50.0673230.64570.260027
60.1353591.29830.098712
7-0.236807-2.27140.012728
80.0420990.40380.343648
90.0090090.08640.465662
100.0262980.25220.400709
110.1741141.670.049155
12-0.380274-3.64750.000219
130.1330611.27630.102535
140.0380320.36480.358054
150.0812820.77960.218805
16-0.103933-0.99690.160717
170.0174830.16770.433596
18-0.066047-0.63350.263989
190.0442970.42490.335956
200.1067321.02370.154322
210.0196480.18850.425466
22-0.245535-2.35510.010322
230.2232762.14160.017434
240.0151430.14530.442415
25-0.141633-1.35850.088813
260.1929461.85070.033713
27-0.176342-1.69140.047072
280.0229960.22060.412957
290.151881.45680.074291
30-0.108612-1.04180.150124
31-0.028624-0.27460.392138
32-0.027477-0.26350.39636
33-0.042527-0.40790.342146
340.2031091.94820.027222
35-0.095217-0.91330.181738
36-0.087953-0.84360.200535






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.481223-4.61576e-06
2-0.297636-2.85480.00266
3-0.167881-1.61030.055384
4-0.15076-1.4460.075782
5-0.03118-0.29910.382782
60.2357092.26080.013063
7-0.011815-0.11330.455009
8-0.097979-0.93980.174896
9-0.117001-1.12220.132342
10-0.063013-0.60440.273533
110.2262892.17050.016272
12-0.23305-2.23530.013907
13-0.177157-1.69920.046328
14-0.110431-1.05920.146136
150.1041110.99860.160304
16-0.049065-0.47060.319516
17-0.060554-0.58080.281393
180.0592380.56820.285645
19-0.09587-0.91960.180106
200.0183060.17560.430501
210.1432391.37390.086405
22-0.130194-1.24880.107457
230.1752741.68120.048061
240.1036830.99450.161296
25-0.172484-1.65440.050726
260.0558540.53570.296717
270.0832480.79850.213321
28-0.006165-0.05910.476488
290.0623550.59810.275624
300.0546810.52450.300604
31-0.081365-0.78040.218572
32-0.1582-1.51740.066297
33-0.005469-0.05250.47914
340.0022360.02140.491469
350.1473411.41320.08048
360.116531.11770.133299

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.481223 & -4.6157 & 6e-06 \tabularnewline
2 & -0.297636 & -2.8548 & 0.00266 \tabularnewline
3 & -0.167881 & -1.6103 & 0.055384 \tabularnewline
4 & -0.15076 & -1.446 & 0.075782 \tabularnewline
5 & -0.03118 & -0.2991 & 0.382782 \tabularnewline
6 & 0.235709 & 2.2608 & 0.013063 \tabularnewline
7 & -0.011815 & -0.1133 & 0.455009 \tabularnewline
8 & -0.097979 & -0.9398 & 0.174896 \tabularnewline
9 & -0.117001 & -1.1222 & 0.132342 \tabularnewline
10 & -0.063013 & -0.6044 & 0.273533 \tabularnewline
11 & 0.226289 & 2.1705 & 0.016272 \tabularnewline
12 & -0.23305 & -2.2353 & 0.013907 \tabularnewline
13 & -0.177157 & -1.6992 & 0.046328 \tabularnewline
14 & -0.110431 & -1.0592 & 0.146136 \tabularnewline
15 & 0.104111 & 0.9986 & 0.160304 \tabularnewline
16 & -0.049065 & -0.4706 & 0.319516 \tabularnewline
17 & -0.060554 & -0.5808 & 0.281393 \tabularnewline
18 & 0.059238 & 0.5682 & 0.285645 \tabularnewline
19 & -0.09587 & -0.9196 & 0.180106 \tabularnewline
20 & 0.018306 & 0.1756 & 0.430501 \tabularnewline
21 & 0.143239 & 1.3739 & 0.086405 \tabularnewline
22 & -0.130194 & -1.2488 & 0.107457 \tabularnewline
23 & 0.175274 & 1.6812 & 0.048061 \tabularnewline
24 & 0.103683 & 0.9945 & 0.161296 \tabularnewline
25 & -0.172484 & -1.6544 & 0.050726 \tabularnewline
26 & 0.055854 & 0.5357 & 0.296717 \tabularnewline
27 & 0.083248 & 0.7985 & 0.213321 \tabularnewline
28 & -0.006165 & -0.0591 & 0.476488 \tabularnewline
29 & 0.062355 & 0.5981 & 0.275624 \tabularnewline
30 & 0.054681 & 0.5245 & 0.300604 \tabularnewline
31 & -0.081365 & -0.7804 & 0.218572 \tabularnewline
32 & -0.1582 & -1.5174 & 0.066297 \tabularnewline
33 & -0.005469 & -0.0525 & 0.47914 \tabularnewline
34 & 0.002236 & 0.0214 & 0.491469 \tabularnewline
35 & 0.147341 & 1.4132 & 0.08048 \tabularnewline
36 & 0.11653 & 1.1177 & 0.133299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62690&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]-0.481223[/C][C]-4.6157[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.297636[/C][C]-2.8548[/C][C]0.00266[/C][/ROW]
[ROW][C]3[/C][C]-0.167881[/C][C]-1.6103[/C][C]0.055384[/C][/ROW]
[ROW][C]4[/C][C]-0.15076[/C][C]-1.446[/C][C]0.075782[/C][/ROW]
[ROW][C]5[/C][C]-0.03118[/C][C]-0.2991[/C][C]0.382782[/C][/ROW]
[ROW][C]6[/C][C]0.235709[/C][C]2.2608[/C][C]0.013063[/C][/ROW]
[ROW][C]7[/C][C]-0.011815[/C][C]-0.1133[/C][C]0.455009[/C][/ROW]
[ROW][C]8[/C][C]-0.097979[/C][C]-0.9398[/C][C]0.174896[/C][/ROW]
[ROW][C]9[/C][C]-0.117001[/C][C]-1.1222[/C][C]0.132342[/C][/ROW]
[ROW][C]10[/C][C]-0.063013[/C][C]-0.6044[/C][C]0.273533[/C][/ROW]
[ROW][C]11[/C][C]0.226289[/C][C]2.1705[/C][C]0.016272[/C][/ROW]
[ROW][C]12[/C][C]-0.23305[/C][C]-2.2353[/C][C]0.013907[/C][/ROW]
[ROW][C]13[/C][C]-0.177157[/C][C]-1.6992[/C][C]0.046328[/C][/ROW]
[ROW][C]14[/C][C]-0.110431[/C][C]-1.0592[/C][C]0.146136[/C][/ROW]
[ROW][C]15[/C][C]0.104111[/C][C]0.9986[/C][C]0.160304[/C][/ROW]
[ROW][C]16[/C][C]-0.049065[/C][C]-0.4706[/C][C]0.319516[/C][/ROW]
[ROW][C]17[/C][C]-0.060554[/C][C]-0.5808[/C][C]0.281393[/C][/ROW]
[ROW][C]18[/C][C]0.059238[/C][C]0.5682[/C][C]0.285645[/C][/ROW]
[ROW][C]19[/C][C]-0.09587[/C][C]-0.9196[/C][C]0.180106[/C][/ROW]
[ROW][C]20[/C][C]0.018306[/C][C]0.1756[/C][C]0.430501[/C][/ROW]
[ROW][C]21[/C][C]0.143239[/C][C]1.3739[/C][C]0.086405[/C][/ROW]
[ROW][C]22[/C][C]-0.130194[/C][C]-1.2488[/C][C]0.107457[/C][/ROW]
[ROW][C]23[/C][C]0.175274[/C][C]1.6812[/C][C]0.048061[/C][/ROW]
[ROW][C]24[/C][C]0.103683[/C][C]0.9945[/C][C]0.161296[/C][/ROW]
[ROW][C]25[/C][C]-0.172484[/C][C]-1.6544[/C][C]0.050726[/C][/ROW]
[ROW][C]26[/C][C]0.055854[/C][C]0.5357[/C][C]0.296717[/C][/ROW]
[ROW][C]27[/C][C]0.083248[/C][C]0.7985[/C][C]0.213321[/C][/ROW]
[ROW][C]28[/C][C]-0.006165[/C][C]-0.0591[/C][C]0.476488[/C][/ROW]
[ROW][C]29[/C][C]0.062355[/C][C]0.5981[/C][C]0.275624[/C][/ROW]
[ROW][C]30[/C][C]0.054681[/C][C]0.5245[/C][C]0.300604[/C][/ROW]
[ROW][C]31[/C][C]-0.081365[/C][C]-0.7804[/C][C]0.218572[/C][/ROW]
[ROW][C]32[/C][C]-0.1582[/C][C]-1.5174[/C][C]0.066297[/C][/ROW]
[ROW][C]33[/C][C]-0.005469[/C][C]-0.0525[/C][C]0.47914[/C][/ROW]
[ROW][C]34[/C][C]0.002236[/C][C]0.0214[/C][C]0.491469[/C][/ROW]
[ROW][C]35[/C][C]0.147341[/C][C]1.4132[/C][C]0.08048[/C][/ROW]
[ROW][C]36[/C][C]0.11653[/C][C]1.1177[/C][C]0.133299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62690&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62690&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
1-0.481223-4.61576e-06
2-0.297636-2.85480.00266
3-0.167881-1.61030.055384
4-0.15076-1.4460.075782
5-0.03118-0.29910.382782
60.2357092.26080.013063
7-0.011815-0.11330.455009
8-0.097979-0.93980.174896
9-0.117001-1.12220.132342
10-0.063013-0.60440.273533
110.2262892.17050.016272
12-0.23305-2.23530.013907
13-0.177157-1.69920.046328
14-0.110431-1.05920.146136
150.1041110.99860.160304
16-0.049065-0.47060.319516
17-0.060554-0.58080.281393
180.0592380.56820.285645
19-0.09587-0.91960.180106
200.0183060.17560.430501
210.1432391.37390.086405
22-0.130194-1.24880.107457
230.1752741.68120.048061
240.1036830.99450.161296
25-0.172484-1.65440.050726
260.0558540.53570.296717
270.0832480.79850.213321
28-0.006165-0.05910.476488
290.0623550.59810.275624
300.0546810.52450.300604
31-0.081365-0.78040.218572
32-0.1582-1.51740.066297
33-0.005469-0.05250.47914
340.0022360.02140.491469
350.1473411.41320.08048
360.116531.11770.133299


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')