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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 computationSun, 11 Dec 2011 08:08:49 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/11/t1323608940k1lij5l53d6wt4x.htm/, Retrieved Sun, 28 Apr 2024 21:11:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153707, Retrieved Sun, 28 Apr 2024 21:11:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2011-12-11 13:08:49] [8a7cc4cdacda1fa59fc196ea0735b051] [Current]
- R  D    [(Partial) Autocorrelation Function] [] [2011-12-11 13:14:03] [d49626b9c7bd91ce0b695b5077c2942f]
- RMPD    [Spectral Analysis] [] [2011-12-11 13:19:20] [d49626b9c7bd91ce0b695b5077c2942f]
- RMP       [ARIMA Backward Selection] [] [2011-12-16 10:58:13] [d49626b9c7bd91ce0b695b5077c2942f]
- RMPD      [Central Tendency] [] [2011-12-16 11:26:59] [d49626b9c7bd91ce0b695b5077c2942f]
- RMPD      [Central Tendency] [] [2011-12-16 11:31:12] [d49626b9c7bd91ce0b695b5077c2942f]
- RMPD      [Univariate Data Series] [] [2011-12-16 11:52:46] [d49626b9c7bd91ce0b695b5077c2942f]
- RMP       [ARIMA Forecasting] [] [2011-12-16 12:05:44] [d49626b9c7bd91ce0b695b5077c2942f]
- RM          [ARIMA Forecasting] [] [2011-12-16 12:06:48] [d49626b9c7bd91ce0b695b5077c2942f]
- RMPD    [Standard Deviation-Mean Plot] [] [2011-12-11 14:08:53] [d49626b9c7bd91ce0b695b5077c2942f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112
118
132
129
121
135
148
148
136
119
104
118
115
126
141
135
125
149
170
170
158
133
114
140
145
150
178
163
172
178
199
199
184
162
146
166
171
180
193
181
183
218
230
242
209
191
172
194
196
196
236
235
229
243
264
272
237
211
180
201
204
188
235
227
234
264
302
293
259
229
203
229
242
233
267
269
270
315
364
347
312
274
237
278
284
277
317
313
318
374
413
405
355
306
271
306
315
301
356
348
355
422
465
467
404
347
305
336
340
318
362
348
363
435
491
505
404
359
310
337
360
342
406
396
420
472
548
559
463
407
362
405
417
391
419
461
472
535
622
606
508
461
390
432

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153707&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153707&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153707&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 time2 seconds
R Server'AstonUniversity' @ aston.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.329629-3.59580.000236
20.1784321.94650.026978
3-0.230428-2.51370.006642
40.0347320.37890.352726
50.0390930.42650.335274
60.0046610.05080.479768
7-0.005397-0.05890.476577
8-0.002115-0.02310.490815
90.184322.01070.023309
10-0.084244-0.9190.179979
110.0305150.33290.369905
12-0.47527-5.18460
130.1938662.11480.018265
14-0.08359-0.91190.181845
150.1478391.61270.054726
16-0.080622-0.87950.190457
17-0.010919-0.11910.452692
180.0205480.22420.411512
190.0307630.33560.368886
20-0.132702-1.44760.075178
210.0468140.51070.305262
22-0.113142-1.23420.109773
230.1671171.8230.035404
240.0832440.90810.182835
25-0.135599-1.47920.070862
260.0716440.78150.218016
27-0.084005-0.91640.180658
280.047420.51730.302955
290.0520340.56760.285678
30-0.031459-0.34320.366034
31-0.063029-0.68760.246531
320.1369051.49350.068982
33-0.081533-0.88940.187786
340.0916340.99960.159765
35-0.112415-1.22630.111252
36-0.009871-0.10770.457213

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.329629 & -3.5958 & 0.000236 \tabularnewline
2 & 0.178432 & 1.9465 & 0.026978 \tabularnewline
3 & -0.230428 & -2.5137 & 0.006642 \tabularnewline
4 & 0.034732 & 0.3789 & 0.352726 \tabularnewline
5 & 0.039093 & 0.4265 & 0.335274 \tabularnewline
6 & 0.004661 & 0.0508 & 0.479768 \tabularnewline
7 & -0.005397 & -0.0589 & 0.476577 \tabularnewline
8 & -0.002115 & -0.0231 & 0.490815 \tabularnewline
9 & 0.18432 & 2.0107 & 0.023309 \tabularnewline
10 & -0.084244 & -0.919 & 0.179979 \tabularnewline
11 & 0.030515 & 0.3329 & 0.369905 \tabularnewline
12 & -0.47527 & -5.1846 & 0 \tabularnewline
13 & 0.193866 & 2.1148 & 0.018265 \tabularnewline
14 & -0.08359 & -0.9119 & 0.181845 \tabularnewline
15 & 0.147839 & 1.6127 & 0.054726 \tabularnewline
16 & -0.080622 & -0.8795 & 0.190457 \tabularnewline
17 & -0.010919 & -0.1191 & 0.452692 \tabularnewline
18 & 0.020548 & 0.2242 & 0.411512 \tabularnewline
19 & 0.030763 & 0.3356 & 0.368886 \tabularnewline
20 & -0.132702 & -1.4476 & 0.075178 \tabularnewline
21 & 0.046814 & 0.5107 & 0.305262 \tabularnewline
22 & -0.113142 & -1.2342 & 0.109773 \tabularnewline
23 & 0.167117 & 1.823 & 0.035404 \tabularnewline
24 & 0.083244 & 0.9081 & 0.182835 \tabularnewline
25 & -0.135599 & -1.4792 & 0.070862 \tabularnewline
26 & 0.071644 & 0.7815 & 0.218016 \tabularnewline
27 & -0.084005 & -0.9164 & 0.180658 \tabularnewline
28 & 0.04742 & 0.5173 & 0.302955 \tabularnewline
29 & 0.052034 & 0.5676 & 0.285678 \tabularnewline
30 & -0.031459 & -0.3432 & 0.366034 \tabularnewline
31 & -0.063029 & -0.6876 & 0.246531 \tabularnewline
32 & 0.136905 & 1.4935 & 0.068982 \tabularnewline
33 & -0.081533 & -0.8894 & 0.187786 \tabularnewline
34 & 0.091634 & 0.9996 & 0.159765 \tabularnewline
35 & -0.112415 & -1.2263 & 0.111252 \tabularnewline
36 & -0.009871 & -0.1077 & 0.457213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153707&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]-0.329629[/C][C]-3.5958[/C][C]0.000236[/C][/ROW]
[ROW][C]2[/C][C]0.178432[/C][C]1.9465[/C][C]0.026978[/C][/ROW]
[ROW][C]3[/C][C]-0.230428[/C][C]-2.5137[/C][C]0.006642[/C][/ROW]
[ROW][C]4[/C][C]0.034732[/C][C]0.3789[/C][C]0.352726[/C][/ROW]
[ROW][C]5[/C][C]0.039093[/C][C]0.4265[/C][C]0.335274[/C][/ROW]
[ROW][C]6[/C][C]0.004661[/C][C]0.0508[/C][C]0.479768[/C][/ROW]
[ROW][C]7[/C][C]-0.005397[/C][C]-0.0589[/C][C]0.476577[/C][/ROW]
[ROW][C]8[/C][C]-0.002115[/C][C]-0.0231[/C][C]0.490815[/C][/ROW]
[ROW][C]9[/C][C]0.18432[/C][C]2.0107[/C][C]0.023309[/C][/ROW]
[ROW][C]10[/C][C]-0.084244[/C][C]-0.919[/C][C]0.179979[/C][/ROW]
[ROW][C]11[/C][C]0.030515[/C][C]0.3329[/C][C]0.369905[/C][/ROW]
[ROW][C]12[/C][C]-0.47527[/C][C]-5.1846[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.193866[/C][C]2.1148[/C][C]0.018265[/C][/ROW]
[ROW][C]14[/C][C]-0.08359[/C][C]-0.9119[/C][C]0.181845[/C][/ROW]
[ROW][C]15[/C][C]0.147839[/C][C]1.6127[/C][C]0.054726[/C][/ROW]
[ROW][C]16[/C][C]-0.080622[/C][C]-0.8795[/C][C]0.190457[/C][/ROW]
[ROW][C]17[/C][C]-0.010919[/C][C]-0.1191[/C][C]0.452692[/C][/ROW]
[ROW][C]18[/C][C]0.020548[/C][C]0.2242[/C][C]0.411512[/C][/ROW]
[ROW][C]19[/C][C]0.030763[/C][C]0.3356[/C][C]0.368886[/C][/ROW]
[ROW][C]20[/C][C]-0.132702[/C][C]-1.4476[/C][C]0.075178[/C][/ROW]
[ROW][C]21[/C][C]0.046814[/C][C]0.5107[/C][C]0.305262[/C][/ROW]
[ROW][C]22[/C][C]-0.113142[/C][C]-1.2342[/C][C]0.109773[/C][/ROW]
[ROW][C]23[/C][C]0.167117[/C][C]1.823[/C][C]0.035404[/C][/ROW]
[ROW][C]24[/C][C]0.083244[/C][C]0.9081[/C][C]0.182835[/C][/ROW]
[ROW][C]25[/C][C]-0.135599[/C][C]-1.4792[/C][C]0.070862[/C][/ROW]
[ROW][C]26[/C][C]0.071644[/C][C]0.7815[/C][C]0.218016[/C][/ROW]
[ROW][C]27[/C][C]-0.084005[/C][C]-0.9164[/C][C]0.180658[/C][/ROW]
[ROW][C]28[/C][C]0.04742[/C][C]0.5173[/C][C]0.302955[/C][/ROW]
[ROW][C]29[/C][C]0.052034[/C][C]0.5676[/C][C]0.285678[/C][/ROW]
[ROW][C]30[/C][C]-0.031459[/C][C]-0.3432[/C][C]0.366034[/C][/ROW]
[ROW][C]31[/C][C]-0.063029[/C][C]-0.6876[/C][C]0.246531[/C][/ROW]
[ROW][C]32[/C][C]0.136905[/C][C]1.4935[/C][C]0.068982[/C][/ROW]
[ROW][C]33[/C][C]-0.081533[/C][C]-0.8894[/C][C]0.187786[/C][/ROW]
[ROW][C]34[/C][C]0.091634[/C][C]0.9996[/C][C]0.159765[/C][/ROW]
[ROW][C]35[/C][C]-0.112415[/C][C]-1.2263[/C][C]0.111252[/C][/ROW]
[ROW][C]36[/C][C]-0.009871[/C][C]-0.1077[/C][C]0.457213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153707&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153707&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
1-0.329629-3.59580.000236
20.1784321.94650.026978
3-0.230428-2.51370.006642
40.0347320.37890.352726
50.0390930.42650.335274
60.0046610.05080.479768
7-0.005397-0.05890.476577
8-0.002115-0.02310.490815
90.184322.01070.023309
10-0.084244-0.9190.179979
110.0305150.33290.369905
12-0.47527-5.18460
130.1938662.11480.018265
14-0.08359-0.91190.181845
150.1478391.61270.054726
16-0.080622-0.87950.190457
17-0.010919-0.11910.452692
180.0205480.22420.411512
190.0307630.33560.368886
20-0.132702-1.44760.075178
210.0468140.51070.305262
22-0.113142-1.23420.109773
230.1671171.8230.035404
240.0832440.90810.182835
25-0.135599-1.47920.070862
260.0716440.78150.218016
27-0.084005-0.91640.180658
280.047420.51730.302955
290.0520340.56760.285678
30-0.031459-0.34320.366034
31-0.063029-0.68760.246531
320.1369051.49350.068982
33-0.081533-0.88940.187786
340.0916340.99960.159765
35-0.112415-1.22630.111252
36-0.009871-0.10770.457213






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.329629-3.59580.000236
20.0782830.8540.197421
3-0.169788-1.85220.03324
4-0.108033-1.17850.120475
50.0669440.73030.233331
60.006850.07470.470278
7-0.03419-0.3730.354919
80.0152890.16680.433911
90.2310822.52080.006516
100.022490.24530.403309
11-0.028475-0.31060.378314
12-0.477566-5.20960
13-0.124903-1.36250.087802
140.0002150.00230.499064
15-0.04792-0.52270.301063
16-0.075143-0.81970.207008
178.4e-059e-040.499636
180.0548910.59880.275227
190.0785450.85680.196633
20-0.127948-1.39580.082694
210.1753981.91340.029052
22-0.073161-0.79810.213205
23-0.020337-0.22190.412405
24-0.102572-1.11890.132711
25-0.169383-1.84780.033561
260.0003610.00390.498433
27-0.001823-0.01990.492084
28-0.119813-1.3070.096866
290.1413391.54180.062886
300.0855050.93280.176419
31-0.061376-0.66950.252227
320.00150.01640.493487
330.0712270.7770.219353
34-0.018495-0.20180.420227
35-0.006699-0.07310.470932
36-0.138925-1.51550.066149

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.329629 & -3.5958 & 0.000236 \tabularnewline
2 & 0.078283 & 0.854 & 0.197421 \tabularnewline
3 & -0.169788 & -1.8522 & 0.03324 \tabularnewline
4 & -0.108033 & -1.1785 & 0.120475 \tabularnewline
5 & 0.066944 & 0.7303 & 0.233331 \tabularnewline
6 & 0.00685 & 0.0747 & 0.470278 \tabularnewline
7 & -0.03419 & -0.373 & 0.354919 \tabularnewline
8 & 0.015289 & 0.1668 & 0.433911 \tabularnewline
9 & 0.231082 & 2.5208 & 0.006516 \tabularnewline
10 & 0.02249 & 0.2453 & 0.403309 \tabularnewline
11 & -0.028475 & -0.3106 & 0.378314 \tabularnewline
12 & -0.477566 & -5.2096 & 0 \tabularnewline
13 & -0.124903 & -1.3625 & 0.087802 \tabularnewline
14 & 0.000215 & 0.0023 & 0.499064 \tabularnewline
15 & -0.04792 & -0.5227 & 0.301063 \tabularnewline
16 & -0.075143 & -0.8197 & 0.207008 \tabularnewline
17 & 8.4e-05 & 9e-04 & 0.499636 \tabularnewline
18 & 0.054891 & 0.5988 & 0.275227 \tabularnewline
19 & 0.078545 & 0.8568 & 0.196633 \tabularnewline
20 & -0.127948 & -1.3958 & 0.082694 \tabularnewline
21 & 0.175398 & 1.9134 & 0.029052 \tabularnewline
22 & -0.073161 & -0.7981 & 0.213205 \tabularnewline
23 & -0.020337 & -0.2219 & 0.412405 \tabularnewline
24 & -0.102572 & -1.1189 & 0.132711 \tabularnewline
25 & -0.169383 & -1.8478 & 0.033561 \tabularnewline
26 & 0.000361 & 0.0039 & 0.498433 \tabularnewline
27 & -0.001823 & -0.0199 & 0.492084 \tabularnewline
28 & -0.119813 & -1.307 & 0.096866 \tabularnewline
29 & 0.141339 & 1.5418 & 0.062886 \tabularnewline
30 & 0.085505 & 0.9328 & 0.176419 \tabularnewline
31 & -0.061376 & -0.6695 & 0.252227 \tabularnewline
32 & 0.0015 & 0.0164 & 0.493487 \tabularnewline
33 & 0.071227 & 0.777 & 0.219353 \tabularnewline
34 & -0.018495 & -0.2018 & 0.420227 \tabularnewline
35 & -0.006699 & -0.0731 & 0.470932 \tabularnewline
36 & -0.138925 & -1.5155 & 0.066149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153707&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]-0.329629[/C][C]-3.5958[/C][C]0.000236[/C][/ROW]
[ROW][C]2[/C][C]0.078283[/C][C]0.854[/C][C]0.197421[/C][/ROW]
[ROW][C]3[/C][C]-0.169788[/C][C]-1.8522[/C][C]0.03324[/C][/ROW]
[ROW][C]4[/C][C]-0.108033[/C][C]-1.1785[/C][C]0.120475[/C][/ROW]
[ROW][C]5[/C][C]0.066944[/C][C]0.7303[/C][C]0.233331[/C][/ROW]
[ROW][C]6[/C][C]0.00685[/C][C]0.0747[/C][C]0.470278[/C][/ROW]
[ROW][C]7[/C][C]-0.03419[/C][C]-0.373[/C][C]0.354919[/C][/ROW]
[ROW][C]8[/C][C]0.015289[/C][C]0.1668[/C][C]0.433911[/C][/ROW]
[ROW][C]9[/C][C]0.231082[/C][C]2.5208[/C][C]0.006516[/C][/ROW]
[ROW][C]10[/C][C]0.02249[/C][C]0.2453[/C][C]0.403309[/C][/ROW]
[ROW][C]11[/C][C]-0.028475[/C][C]-0.3106[/C][C]0.378314[/C][/ROW]
[ROW][C]12[/C][C]-0.477566[/C][C]-5.2096[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.124903[/C][C]-1.3625[/C][C]0.087802[/C][/ROW]
[ROW][C]14[/C][C]0.000215[/C][C]0.0023[/C][C]0.499064[/C][/ROW]
[ROW][C]15[/C][C]-0.04792[/C][C]-0.5227[/C][C]0.301063[/C][/ROW]
[ROW][C]16[/C][C]-0.075143[/C][C]-0.8197[/C][C]0.207008[/C][/ROW]
[ROW][C]17[/C][C]8.4e-05[/C][C]9e-04[/C][C]0.499636[/C][/ROW]
[ROW][C]18[/C][C]0.054891[/C][C]0.5988[/C][C]0.275227[/C][/ROW]
[ROW][C]19[/C][C]0.078545[/C][C]0.8568[/C][C]0.196633[/C][/ROW]
[ROW][C]20[/C][C]-0.127948[/C][C]-1.3958[/C][C]0.082694[/C][/ROW]
[ROW][C]21[/C][C]0.175398[/C][C]1.9134[/C][C]0.029052[/C][/ROW]
[ROW][C]22[/C][C]-0.073161[/C][C]-0.7981[/C][C]0.213205[/C][/ROW]
[ROW][C]23[/C][C]-0.020337[/C][C]-0.2219[/C][C]0.412405[/C][/ROW]
[ROW][C]24[/C][C]-0.102572[/C][C]-1.1189[/C][C]0.132711[/C][/ROW]
[ROW][C]25[/C][C]-0.169383[/C][C]-1.8478[/C][C]0.033561[/C][/ROW]
[ROW][C]26[/C][C]0.000361[/C][C]0.0039[/C][C]0.498433[/C][/ROW]
[ROW][C]27[/C][C]-0.001823[/C][C]-0.0199[/C][C]0.492084[/C][/ROW]
[ROW][C]28[/C][C]-0.119813[/C][C]-1.307[/C][C]0.096866[/C][/ROW]
[ROW][C]29[/C][C]0.141339[/C][C]1.5418[/C][C]0.062886[/C][/ROW]
[ROW][C]30[/C][C]0.085505[/C][C]0.9328[/C][C]0.176419[/C][/ROW]
[ROW][C]31[/C][C]-0.061376[/C][C]-0.6695[/C][C]0.252227[/C][/ROW]
[ROW][C]32[/C][C]0.0015[/C][C]0.0164[/C][C]0.493487[/C][/ROW]
[ROW][C]33[/C][C]0.071227[/C][C]0.777[/C][C]0.219353[/C][/ROW]
[ROW][C]34[/C][C]-0.018495[/C][C]-0.2018[/C][C]0.420227[/C][/ROW]
[ROW][C]35[/C][C]-0.006699[/C][C]-0.0731[/C][C]0.470932[/C][/ROW]
[ROW][C]36[/C][C]-0.138925[/C][C]-1.5155[/C][C]0.066149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153707&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153707&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
1-0.329629-3.59580.000236
20.0782830.8540.197421
3-0.169788-1.85220.03324
4-0.108033-1.17850.120475
50.0669440.73030.233331
60.006850.07470.470278
7-0.03419-0.3730.354919
80.0152890.16680.433911
90.2310822.52080.006516
100.022490.24530.403309
11-0.028475-0.31060.378314
12-0.477566-5.20960
13-0.124903-1.36250.087802
140.0002150.00230.499064
15-0.04792-0.52270.301063
16-0.075143-0.81970.207008
178.4e-059e-040.499636
180.0548910.59880.275227
190.0785450.85680.196633
20-0.127948-1.39580.082694
210.1753981.91340.029052
22-0.073161-0.79810.213205
23-0.020337-0.22190.412405
24-0.102572-1.11890.132711
25-0.169383-1.84780.033561
260.0003610.00390.498433
27-0.001823-0.01990.492084
28-0.119813-1.3070.096866
290.1413391.54180.062886
300.0855050.93280.176419
31-0.061376-0.66950.252227
320.00150.01640.493487
330.0712270.7770.219353
34-0.018495-0.20180.420227
35-0.006699-0.07310.470932
36-0.138925-1.51550.066149


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')