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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 12:10:39 -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/t1259262674nlol1j54b1hx1ys.htm/, Retrieved Sat, 04 May 2024 21:11:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60297, Retrieved Sat, 04 May 2024 21:11:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 15:01:25] [b40728cc9f1a5ce9748a6b7b76867bb9]
-   P           [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 15:36:56] [b40728cc9f1a5ce9748a6b7b76867bb9]
-   P               [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 19:10:39] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
79.8
83.4
113.6
112.9
104
109.9
99
106.3
128.9
111.1
102.9
130
87
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137
91
90.5
122.4
123.3
124.3
120
118.1
119
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128
121.6
135.8
143.8
147.5
136.2
156.6
123.3
104.5
139.8
136.5
112.1
118.5
94.4
102.3
111.4
99.2
87.8
115.8

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=60297&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=60297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60297&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
1-0.669355-4.53982e-05
20.1156060.78410.218508
30.2212111.50030.070182
4-0.249051-1.68910.04898
50.052980.35930.360497
60.221521.50240.069912
7-0.360675-2.44620.00916
80.3009792.04130.023489
9-0.175028-1.18710.120642
100.0339890.23050.409353
110.0821840.55740.289979
12-0.111711-0.75770.226259
130.0249460.16920.433193
140.0650420.44110.330589
15-0.04528-0.30710.380075
16-0.058098-0.3940.347687
170.1091370.74020.231469
18-0.038789-0.26310.396832
19-0.058615-0.39750.346401
200.0515110.34940.364204
210.1096550.74370.230415
22-0.318114-2.15760.01811
230.3663662.48480.008331
24-0.200462-1.35960.090292
25-0.035537-0.2410.405304
260.1399650.94930.173717
27-0.068579-0.46510.322017
28-0.077-0.52220.302004
290.209181.41870.08136
30-0.254779-1.7280.045349
310.1845781.25190.108472
32-0.081145-0.55030.292371
33-0.030683-0.20810.418033
340.1177120.79840.214381
35-0.076459-0.51860.303273
36-0.067761-0.45960.323992

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.669355 & -4.5398 & 2e-05 \tabularnewline
2 & 0.115606 & 0.7841 & 0.218508 \tabularnewline
3 & 0.221211 & 1.5003 & 0.070182 \tabularnewline
4 & -0.249051 & -1.6891 & 0.04898 \tabularnewline
5 & 0.05298 & 0.3593 & 0.360497 \tabularnewline
6 & 0.22152 & 1.5024 & 0.069912 \tabularnewline
7 & -0.360675 & -2.4462 & 0.00916 \tabularnewline
8 & 0.300979 & 2.0413 & 0.023489 \tabularnewline
9 & -0.175028 & -1.1871 & 0.120642 \tabularnewline
10 & 0.033989 & 0.2305 & 0.409353 \tabularnewline
11 & 0.082184 & 0.5574 & 0.289979 \tabularnewline
12 & -0.111711 & -0.7577 & 0.226259 \tabularnewline
13 & 0.024946 & 0.1692 & 0.433193 \tabularnewline
14 & 0.065042 & 0.4411 & 0.330589 \tabularnewline
15 & -0.04528 & -0.3071 & 0.380075 \tabularnewline
16 & -0.058098 & -0.394 & 0.347687 \tabularnewline
17 & 0.109137 & 0.7402 & 0.231469 \tabularnewline
18 & -0.038789 & -0.2631 & 0.396832 \tabularnewline
19 & -0.058615 & -0.3975 & 0.346401 \tabularnewline
20 & 0.051511 & 0.3494 & 0.364204 \tabularnewline
21 & 0.109655 & 0.7437 & 0.230415 \tabularnewline
22 & -0.318114 & -2.1576 & 0.01811 \tabularnewline
23 & 0.366366 & 2.4848 & 0.008331 \tabularnewline
24 & -0.200462 & -1.3596 & 0.090292 \tabularnewline
25 & -0.035537 & -0.241 & 0.405304 \tabularnewline
26 & 0.139965 & 0.9493 & 0.173717 \tabularnewline
27 & -0.068579 & -0.4651 & 0.322017 \tabularnewline
28 & -0.077 & -0.5222 & 0.302004 \tabularnewline
29 & 0.20918 & 1.4187 & 0.08136 \tabularnewline
30 & -0.254779 & -1.728 & 0.045349 \tabularnewline
31 & 0.184578 & 1.2519 & 0.108472 \tabularnewline
32 & -0.081145 & -0.5503 & 0.292371 \tabularnewline
33 & -0.030683 & -0.2081 & 0.418033 \tabularnewline
34 & 0.117712 & 0.7984 & 0.214381 \tabularnewline
35 & -0.076459 & -0.5186 & 0.303273 \tabularnewline
36 & -0.067761 & -0.4596 & 0.323992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60297&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]-0.669355[/C][C]-4.5398[/C][C]2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.115606[/C][C]0.7841[/C][C]0.218508[/C][/ROW]
[ROW][C]3[/C][C]0.221211[/C][C]1.5003[/C][C]0.070182[/C][/ROW]
[ROW][C]4[/C][C]-0.249051[/C][C]-1.6891[/C][C]0.04898[/C][/ROW]
[ROW][C]5[/C][C]0.05298[/C][C]0.3593[/C][C]0.360497[/C][/ROW]
[ROW][C]6[/C][C]0.22152[/C][C]1.5024[/C][C]0.069912[/C][/ROW]
[ROW][C]7[/C][C]-0.360675[/C][C]-2.4462[/C][C]0.00916[/C][/ROW]
[ROW][C]8[/C][C]0.300979[/C][C]2.0413[/C][C]0.023489[/C][/ROW]
[ROW][C]9[/C][C]-0.175028[/C][C]-1.1871[/C][C]0.120642[/C][/ROW]
[ROW][C]10[/C][C]0.033989[/C][C]0.2305[/C][C]0.409353[/C][/ROW]
[ROW][C]11[/C][C]0.082184[/C][C]0.5574[/C][C]0.289979[/C][/ROW]
[ROW][C]12[/C][C]-0.111711[/C][C]-0.7577[/C][C]0.226259[/C][/ROW]
[ROW][C]13[/C][C]0.024946[/C][C]0.1692[/C][C]0.433193[/C][/ROW]
[ROW][C]14[/C][C]0.065042[/C][C]0.4411[/C][C]0.330589[/C][/ROW]
[ROW][C]15[/C][C]-0.04528[/C][C]-0.3071[/C][C]0.380075[/C][/ROW]
[ROW][C]16[/C][C]-0.058098[/C][C]-0.394[/C][C]0.347687[/C][/ROW]
[ROW][C]17[/C][C]0.109137[/C][C]0.7402[/C][C]0.231469[/C][/ROW]
[ROW][C]18[/C][C]-0.038789[/C][C]-0.2631[/C][C]0.396832[/C][/ROW]
[ROW][C]19[/C][C]-0.058615[/C][C]-0.3975[/C][C]0.346401[/C][/ROW]
[ROW][C]20[/C][C]0.051511[/C][C]0.3494[/C][C]0.364204[/C][/ROW]
[ROW][C]21[/C][C]0.109655[/C][C]0.7437[/C][C]0.230415[/C][/ROW]
[ROW][C]22[/C][C]-0.318114[/C][C]-2.1576[/C][C]0.01811[/C][/ROW]
[ROW][C]23[/C][C]0.366366[/C][C]2.4848[/C][C]0.008331[/C][/ROW]
[ROW][C]24[/C][C]-0.200462[/C][C]-1.3596[/C][C]0.090292[/C][/ROW]
[ROW][C]25[/C][C]-0.035537[/C][C]-0.241[/C][C]0.405304[/C][/ROW]
[ROW][C]26[/C][C]0.139965[/C][C]0.9493[/C][C]0.173717[/C][/ROW]
[ROW][C]27[/C][C]-0.068579[/C][C]-0.4651[/C][C]0.322017[/C][/ROW]
[ROW][C]28[/C][C]-0.077[/C][C]-0.5222[/C][C]0.302004[/C][/ROW]
[ROW][C]29[/C][C]0.20918[/C][C]1.4187[/C][C]0.08136[/C][/ROW]
[ROW][C]30[/C][C]-0.254779[/C][C]-1.728[/C][C]0.045349[/C][/ROW]
[ROW][C]31[/C][C]0.184578[/C][C]1.2519[/C][C]0.108472[/C][/ROW]
[ROW][C]32[/C][C]-0.081145[/C][C]-0.5503[/C][C]0.292371[/C][/ROW]
[ROW][C]33[/C][C]-0.030683[/C][C]-0.2081[/C][C]0.418033[/C][/ROW]
[ROW][C]34[/C][C]0.117712[/C][C]0.7984[/C][C]0.214381[/C][/ROW]
[ROW][C]35[/C][C]-0.076459[/C][C]-0.5186[/C][C]0.303273[/C][/ROW]
[ROW][C]36[/C][C]-0.067761[/C][C]-0.4596[/C][C]0.323992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60297&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
1-0.669355-4.53982e-05
20.1156060.78410.218508
30.2212111.50030.070182
4-0.249051-1.68910.04898
50.052980.35930.360497
60.221521.50240.069912
7-0.360675-2.44620.00916
80.3009792.04130.023489
9-0.175028-1.18710.120642
100.0339890.23050.409353
110.0821840.55740.289979
12-0.111711-0.75770.226259
130.0249460.16920.433193
140.0650420.44110.330589
15-0.04528-0.30710.380075
16-0.058098-0.3940.347687
170.1091370.74020.231469
18-0.038789-0.26310.396832
19-0.058615-0.39750.346401
200.0515110.34940.364204
210.1096550.74370.230415
22-0.318114-2.15760.01811
230.3663662.48480.008331
24-0.200462-1.35960.090292
25-0.035537-0.2410.405304
260.1399650.94930.173717
27-0.068579-0.46510.322017
28-0.077-0.52220.302004
290.209181.41870.08136
30-0.254779-1.7280.045349
310.1845781.25190.108472
32-0.081145-0.55030.292371
33-0.030683-0.20810.418033
340.1177120.79840.214381
35-0.076459-0.51860.303273
36-0.067761-0.45960.323992






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.669355-4.53982e-05
2-0.602267-4.08488.7e-05
3-0.164702-1.11710.134884
4-0.029399-0.19940.421416
5-0.173497-1.17670.122682
60.1855081.25820.107339
70.0111520.07560.470018
80.0928080.62950.266082
9-0.148587-1.00780.159419
10-0.116472-0.790.216804
11-0.006832-0.04630.481621
12-0.037811-0.25640.399375
13-0.061137-0.41470.340162
14-0.103587-0.70260.242934
150.1705911.1570.126622
16-0.081991-0.55610.290422
17-0.097052-0.65820.256834
180.0747310.50690.30734
190.0594910.40350.344229
20-0.134598-0.91290.18303
210.1746761.18470.121108
22-0.124521-0.84450.201368
23-0.059398-0.40290.344459
24-0.005186-0.03520.486046
25-0.042259-0.28660.387847
26-0.093658-0.63520.264216
270.0236310.16030.436684
280.0628120.4260.336043
290.0394260.26740.395178
300.0491530.33340.370183
31-0.025069-0.170.432867
32-0.155512-1.05470.148527
33-0.152205-1.03230.153664
34-0.004026-0.02730.489167
350.0743220.50410.308308
360.0501580.34020.367631

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.669355 & -4.5398 & 2e-05 \tabularnewline
2 & -0.602267 & -4.0848 & 8.7e-05 \tabularnewline
3 & -0.164702 & -1.1171 & 0.134884 \tabularnewline
4 & -0.029399 & -0.1994 & 0.421416 \tabularnewline
5 & -0.173497 & -1.1767 & 0.122682 \tabularnewline
6 & 0.185508 & 1.2582 & 0.107339 \tabularnewline
7 & 0.011152 & 0.0756 & 0.470018 \tabularnewline
8 & 0.092808 & 0.6295 & 0.266082 \tabularnewline
9 & -0.148587 & -1.0078 & 0.159419 \tabularnewline
10 & -0.116472 & -0.79 & 0.216804 \tabularnewline
11 & -0.006832 & -0.0463 & 0.481621 \tabularnewline
12 & -0.037811 & -0.2564 & 0.399375 \tabularnewline
13 & -0.061137 & -0.4147 & 0.340162 \tabularnewline
14 & -0.103587 & -0.7026 & 0.242934 \tabularnewline
15 & 0.170591 & 1.157 & 0.126622 \tabularnewline
16 & -0.081991 & -0.5561 & 0.290422 \tabularnewline
17 & -0.097052 & -0.6582 & 0.256834 \tabularnewline
18 & 0.074731 & 0.5069 & 0.30734 \tabularnewline
19 & 0.059491 & 0.4035 & 0.344229 \tabularnewline
20 & -0.134598 & -0.9129 & 0.18303 \tabularnewline
21 & 0.174676 & 1.1847 & 0.121108 \tabularnewline
22 & -0.124521 & -0.8445 & 0.201368 \tabularnewline
23 & -0.059398 & -0.4029 & 0.344459 \tabularnewline
24 & -0.005186 & -0.0352 & 0.486046 \tabularnewline
25 & -0.042259 & -0.2866 & 0.387847 \tabularnewline
26 & -0.093658 & -0.6352 & 0.264216 \tabularnewline
27 & 0.023631 & 0.1603 & 0.436684 \tabularnewline
28 & 0.062812 & 0.426 & 0.336043 \tabularnewline
29 & 0.039426 & 0.2674 & 0.395178 \tabularnewline
30 & 0.049153 & 0.3334 & 0.370183 \tabularnewline
31 & -0.025069 & -0.17 & 0.432867 \tabularnewline
32 & -0.155512 & -1.0547 & 0.148527 \tabularnewline
33 & -0.152205 & -1.0323 & 0.153664 \tabularnewline
34 & -0.004026 & -0.0273 & 0.489167 \tabularnewline
35 & 0.074322 & 0.5041 & 0.308308 \tabularnewline
36 & 0.050158 & 0.3402 & 0.367631 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60297&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]-0.669355[/C][C]-4.5398[/C][C]2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.602267[/C][C]-4.0848[/C][C]8.7e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.164702[/C][C]-1.1171[/C][C]0.134884[/C][/ROW]
[ROW][C]4[/C][C]-0.029399[/C][C]-0.1994[/C][C]0.421416[/C][/ROW]
[ROW][C]5[/C][C]-0.173497[/C][C]-1.1767[/C][C]0.122682[/C][/ROW]
[ROW][C]6[/C][C]0.185508[/C][C]1.2582[/C][C]0.107339[/C][/ROW]
[ROW][C]7[/C][C]0.011152[/C][C]0.0756[/C][C]0.470018[/C][/ROW]
[ROW][C]8[/C][C]0.092808[/C][C]0.6295[/C][C]0.266082[/C][/ROW]
[ROW][C]9[/C][C]-0.148587[/C][C]-1.0078[/C][C]0.159419[/C][/ROW]
[ROW][C]10[/C][C]-0.116472[/C][C]-0.79[/C][C]0.216804[/C][/ROW]
[ROW][C]11[/C][C]-0.006832[/C][C]-0.0463[/C][C]0.481621[/C][/ROW]
[ROW][C]12[/C][C]-0.037811[/C][C]-0.2564[/C][C]0.399375[/C][/ROW]
[ROW][C]13[/C][C]-0.061137[/C][C]-0.4147[/C][C]0.340162[/C][/ROW]
[ROW][C]14[/C][C]-0.103587[/C][C]-0.7026[/C][C]0.242934[/C][/ROW]
[ROW][C]15[/C][C]0.170591[/C][C]1.157[/C][C]0.126622[/C][/ROW]
[ROW][C]16[/C][C]-0.081991[/C][C]-0.5561[/C][C]0.290422[/C][/ROW]
[ROW][C]17[/C][C]-0.097052[/C][C]-0.6582[/C][C]0.256834[/C][/ROW]
[ROW][C]18[/C][C]0.074731[/C][C]0.5069[/C][C]0.30734[/C][/ROW]
[ROW][C]19[/C][C]0.059491[/C][C]0.4035[/C][C]0.344229[/C][/ROW]
[ROW][C]20[/C][C]-0.134598[/C][C]-0.9129[/C][C]0.18303[/C][/ROW]
[ROW][C]21[/C][C]0.174676[/C][C]1.1847[/C][C]0.121108[/C][/ROW]
[ROW][C]22[/C][C]-0.124521[/C][C]-0.8445[/C][C]0.201368[/C][/ROW]
[ROW][C]23[/C][C]-0.059398[/C][C]-0.4029[/C][C]0.344459[/C][/ROW]
[ROW][C]24[/C][C]-0.005186[/C][C]-0.0352[/C][C]0.486046[/C][/ROW]
[ROW][C]25[/C][C]-0.042259[/C][C]-0.2866[/C][C]0.387847[/C][/ROW]
[ROW][C]26[/C][C]-0.093658[/C][C]-0.6352[/C][C]0.264216[/C][/ROW]
[ROW][C]27[/C][C]0.023631[/C][C]0.1603[/C][C]0.436684[/C][/ROW]
[ROW][C]28[/C][C]0.062812[/C][C]0.426[/C][C]0.336043[/C][/ROW]
[ROW][C]29[/C][C]0.039426[/C][C]0.2674[/C][C]0.395178[/C][/ROW]
[ROW][C]30[/C][C]0.049153[/C][C]0.3334[/C][C]0.370183[/C][/ROW]
[ROW][C]31[/C][C]-0.025069[/C][C]-0.17[/C][C]0.432867[/C][/ROW]
[ROW][C]32[/C][C]-0.155512[/C][C]-1.0547[/C][C]0.148527[/C][/ROW]
[ROW][C]33[/C][C]-0.152205[/C][C]-1.0323[/C][C]0.153664[/C][/ROW]
[ROW][C]34[/C][C]-0.004026[/C][C]-0.0273[/C][C]0.489167[/C][/ROW]
[ROW][C]35[/C][C]0.074322[/C][C]0.5041[/C][C]0.308308[/C][/ROW]
[ROW][C]36[/C][C]0.050158[/C][C]0.3402[/C][C]0.367631[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60297&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60297&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
1-0.669355-4.53982e-05
2-0.602267-4.08488.7e-05
3-0.164702-1.11710.134884
4-0.029399-0.19940.421416
5-0.173497-1.17670.122682
60.1855081.25820.107339
70.0111520.07560.470018
80.0928080.62950.266082
9-0.148587-1.00780.159419
10-0.116472-0.790.216804
11-0.006832-0.04630.481621
12-0.037811-0.25640.399375
13-0.061137-0.41470.340162
14-0.103587-0.70260.242934
150.1705911.1570.126622
16-0.081991-0.55610.290422
17-0.097052-0.65820.256834
180.0747310.50690.30734
190.0594910.40350.344229
20-0.134598-0.91290.18303
210.1746761.18470.121108
22-0.124521-0.84450.201368
23-0.059398-0.40290.344459
24-0.005186-0.03520.486046
25-0.042259-0.28660.387847
26-0.093658-0.63520.264216
270.0236310.16030.436684
280.0628120.4260.336043
290.0394260.26740.395178
300.0491530.33340.370183
31-0.025069-0.170.432867
32-0.155512-1.05470.148527
33-0.152205-1.03230.153664
34-0.004026-0.02730.489167
350.0743220.50410.308308
360.0501580.34020.367631


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; par3 = 2 ; 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')