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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 computationFri, 04 Dec 2009 13:08:36 -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/04/t1259957367q3oxkjknoydzcu9.htm/, Retrieved Sat, 27 Apr 2024 19:37:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64122, Retrieved Sat, 27 Apr 2024 19:37:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS8] [2009-11-25 21:36:53] [cd6314e7e707a6546bd4604c9d1f2b69]
-               [(Partial) Autocorrelation Function] [Paper - ACF (2)] [2009-12-04 17:21:17] [cd6314e7e707a6546bd4604c9d1f2b69]
-   P               [(Partial) Autocorrelation Function] [Paper - ACF (2)] [2009-12-04 20:08:36] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186412
189226
191563
188906
186005
195309
223532
226899
214126

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=64122&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=64122&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64122&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
10.236961.9540.027406
2-0.26711-2.20260.015506
3-0.264111-2.17790.016442
4-0.126641-1.04430.150021
50.0678010.55910.288965
60.0629520.51910.302683
70.0767710.63310.264405
8-0.132935-1.09620.138428
9-0.195029-1.60830.056206
10-0.238212-1.96430.026789
110.2596342.1410.017931
120.7318196.03470
130.1420481.17140.122772
14-0.270978-2.23450.014369
15-0.259083-2.13650.018122
16-0.126193-1.04060.150871
170.0153310.12640.449886
180.0335230.27640.391526
190.0338960.27950.390351
20-0.108841-0.89750.186302
21-0.167662-1.38260.08566
22-0.196374-1.61930.055001
230.2156671.77840.039901
240.5348924.41081.9e-05
250.0579340.47770.317186
26-0.272832-2.24980.01385
27-0.226683-1.86930.032946
28-0.119651-0.98670.163653
290.02880.23750.406496
300.0410140.33820.368122
31-0.000984-0.00810.496774
32-0.106308-0.87660.191885
33-0.149792-1.23520.110501
34-0.135572-1.1180.13376
350.1792151.47780.072033
360.3950933.2580.000876

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.23696 & 1.954 & 0.027406 \tabularnewline
2 & -0.26711 & -2.2026 & 0.015506 \tabularnewline
3 & -0.264111 & -2.1779 & 0.016442 \tabularnewline
4 & -0.126641 & -1.0443 & 0.150021 \tabularnewline
5 & 0.067801 & 0.5591 & 0.288965 \tabularnewline
6 & 0.062952 & 0.5191 & 0.302683 \tabularnewline
7 & 0.076771 & 0.6331 & 0.264405 \tabularnewline
8 & -0.132935 & -1.0962 & 0.138428 \tabularnewline
9 & -0.195029 & -1.6083 & 0.056206 \tabularnewline
10 & -0.238212 & -1.9643 & 0.026789 \tabularnewline
11 & 0.259634 & 2.141 & 0.017931 \tabularnewline
12 & 0.731819 & 6.0347 & 0 \tabularnewline
13 & 0.142048 & 1.1714 & 0.122772 \tabularnewline
14 & -0.270978 & -2.2345 & 0.014369 \tabularnewline
15 & -0.259083 & -2.1365 & 0.018122 \tabularnewline
16 & -0.126193 & -1.0406 & 0.150871 \tabularnewline
17 & 0.015331 & 0.1264 & 0.449886 \tabularnewline
18 & 0.033523 & 0.2764 & 0.391526 \tabularnewline
19 & 0.033896 & 0.2795 & 0.390351 \tabularnewline
20 & -0.108841 & -0.8975 & 0.186302 \tabularnewline
21 & -0.167662 & -1.3826 & 0.08566 \tabularnewline
22 & -0.196374 & -1.6193 & 0.055001 \tabularnewline
23 & 0.215667 & 1.7784 & 0.039901 \tabularnewline
24 & 0.534892 & 4.4108 & 1.9e-05 \tabularnewline
25 & 0.057934 & 0.4777 & 0.317186 \tabularnewline
26 & -0.272832 & -2.2498 & 0.01385 \tabularnewline
27 & -0.226683 & -1.8693 & 0.032946 \tabularnewline
28 & -0.119651 & -0.9867 & 0.163653 \tabularnewline
29 & 0.0288 & 0.2375 & 0.406496 \tabularnewline
30 & 0.041014 & 0.3382 & 0.368122 \tabularnewline
31 & -0.000984 & -0.0081 & 0.496774 \tabularnewline
32 & -0.106308 & -0.8766 & 0.191885 \tabularnewline
33 & -0.149792 & -1.2352 & 0.110501 \tabularnewline
34 & -0.135572 & -1.118 & 0.13376 \tabularnewline
35 & 0.179215 & 1.4778 & 0.072033 \tabularnewline
36 & 0.395093 & 3.258 & 0.000876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64122&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]0.23696[/C][C]1.954[/C][C]0.027406[/C][/ROW]
[ROW][C]2[/C][C]-0.26711[/C][C]-2.2026[/C][C]0.015506[/C][/ROW]
[ROW][C]3[/C][C]-0.264111[/C][C]-2.1779[/C][C]0.016442[/C][/ROW]
[ROW][C]4[/C][C]-0.126641[/C][C]-1.0443[/C][C]0.150021[/C][/ROW]
[ROW][C]5[/C][C]0.067801[/C][C]0.5591[/C][C]0.288965[/C][/ROW]
[ROW][C]6[/C][C]0.062952[/C][C]0.5191[/C][C]0.302683[/C][/ROW]
[ROW][C]7[/C][C]0.076771[/C][C]0.6331[/C][C]0.264405[/C][/ROW]
[ROW][C]8[/C][C]-0.132935[/C][C]-1.0962[/C][C]0.138428[/C][/ROW]
[ROW][C]9[/C][C]-0.195029[/C][C]-1.6083[/C][C]0.056206[/C][/ROW]
[ROW][C]10[/C][C]-0.238212[/C][C]-1.9643[/C][C]0.026789[/C][/ROW]
[ROW][C]11[/C][C]0.259634[/C][C]2.141[/C][C]0.017931[/C][/ROW]
[ROW][C]12[/C][C]0.731819[/C][C]6.0347[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.142048[/C][C]1.1714[/C][C]0.122772[/C][/ROW]
[ROW][C]14[/C][C]-0.270978[/C][C]-2.2345[/C][C]0.014369[/C][/ROW]
[ROW][C]15[/C][C]-0.259083[/C][C]-2.1365[/C][C]0.018122[/C][/ROW]
[ROW][C]16[/C][C]-0.126193[/C][C]-1.0406[/C][C]0.150871[/C][/ROW]
[ROW][C]17[/C][C]0.015331[/C][C]0.1264[/C][C]0.449886[/C][/ROW]
[ROW][C]18[/C][C]0.033523[/C][C]0.2764[/C][C]0.391526[/C][/ROW]
[ROW][C]19[/C][C]0.033896[/C][C]0.2795[/C][C]0.390351[/C][/ROW]
[ROW][C]20[/C][C]-0.108841[/C][C]-0.8975[/C][C]0.186302[/C][/ROW]
[ROW][C]21[/C][C]-0.167662[/C][C]-1.3826[/C][C]0.08566[/C][/ROW]
[ROW][C]22[/C][C]-0.196374[/C][C]-1.6193[/C][C]0.055001[/C][/ROW]
[ROW][C]23[/C][C]0.215667[/C][C]1.7784[/C][C]0.039901[/C][/ROW]
[ROW][C]24[/C][C]0.534892[/C][C]4.4108[/C][C]1.9e-05[/C][/ROW]
[ROW][C]25[/C][C]0.057934[/C][C]0.4777[/C][C]0.317186[/C][/ROW]
[ROW][C]26[/C][C]-0.272832[/C][C]-2.2498[/C][C]0.01385[/C][/ROW]
[ROW][C]27[/C][C]-0.226683[/C][C]-1.8693[/C][C]0.032946[/C][/ROW]
[ROW][C]28[/C][C]-0.119651[/C][C]-0.9867[/C][C]0.163653[/C][/ROW]
[ROW][C]29[/C][C]0.0288[/C][C]0.2375[/C][C]0.406496[/C][/ROW]
[ROW][C]30[/C][C]0.041014[/C][C]0.3382[/C][C]0.368122[/C][/ROW]
[ROW][C]31[/C][C]-0.000984[/C][C]-0.0081[/C][C]0.496774[/C][/ROW]
[ROW][C]32[/C][C]-0.106308[/C][C]-0.8766[/C][C]0.191885[/C][/ROW]
[ROW][C]33[/C][C]-0.149792[/C][C]-1.2352[/C][C]0.110501[/C][/ROW]
[ROW][C]34[/C][C]-0.135572[/C][C]-1.118[/C][C]0.13376[/C][/ROW]
[ROW][C]35[/C][C]0.179215[/C][C]1.4778[/C][C]0.072033[/C][/ROW]
[ROW][C]36[/C][C]0.395093[/C][C]3.258[/C][C]0.000876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64122&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64122&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
10.236961.9540.027406
2-0.26711-2.20260.015506
3-0.264111-2.17790.016442
4-0.126641-1.04430.150021
50.0678010.55910.288965
60.0629520.51910.302683
70.0767710.63310.264405
8-0.132935-1.09620.138428
9-0.195029-1.60830.056206
10-0.238212-1.96430.026789
110.2596342.1410.017931
120.7318196.03470
130.1420481.17140.122772
14-0.270978-2.23450.014369
15-0.259083-2.13650.018122
16-0.126193-1.04060.150871
170.0153310.12640.449886
180.0335230.27640.391526
190.0338960.27950.390351
20-0.108841-0.89750.186302
21-0.167662-1.38260.08566
22-0.196374-1.61930.055001
230.2156671.77840.039901
240.5348924.41081.9e-05
250.0579340.47770.317186
26-0.272832-2.24980.01385
27-0.226683-1.86930.032946
28-0.119651-0.98670.163653
290.02880.23750.406496
300.0410140.33820.368122
31-0.000984-0.00810.496774
32-0.106308-0.87660.191885
33-0.149792-1.23520.110501
34-0.135572-1.1180.13376
350.1792151.47780.072033
360.3950933.2580.000876






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.236961.9540.027406
2-0.342491-2.82430.003106
3-0.117607-0.96980.167789
4-0.130088-1.07270.143591
50.0235960.19460.423153
6-0.074121-0.61120.271546
70.0751290.61950.268818
8-0.214466-1.76850.040728
9-0.082902-0.68360.248267
10-0.325554-2.68460.004557
110.3969983.27370.000835
120.5414774.46511.5e-05
13-0.089107-0.73480.232495
14-0.013813-0.11390.454825
150.0686590.56620.286569
16-0.127708-1.05310.14801
17-0.050763-0.41860.338414
18-0.135282-1.11560.134268
19-0.050391-0.41550.339531
20-0.057777-0.47640.317645
21-0.038023-0.31350.377413
22-0.06678-0.55070.291828
23-0.062288-0.51360.304584
24-0.040714-0.33570.369051
25-0.056644-0.46710.320962
26-0.093468-0.77080.22176
270.0186030.15340.439265
28-0.095461-0.78720.216952
290.0889250.73330.232949
30-0.0372-0.30680.379982
31-0.048449-0.39950.345381
32-0.077058-0.63540.263638
33-0.031307-0.25820.39853
34-0.054436-0.44890.32747
35-0.057251-0.47210.319182
36-0.093186-0.76840.222447

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.23696 & 1.954 & 0.027406 \tabularnewline
2 & -0.342491 & -2.8243 & 0.003106 \tabularnewline
3 & -0.117607 & -0.9698 & 0.167789 \tabularnewline
4 & -0.130088 & -1.0727 & 0.143591 \tabularnewline
5 & 0.023596 & 0.1946 & 0.423153 \tabularnewline
6 & -0.074121 & -0.6112 & 0.271546 \tabularnewline
7 & 0.075129 & 0.6195 & 0.268818 \tabularnewline
8 & -0.214466 & -1.7685 & 0.040728 \tabularnewline
9 & -0.082902 & -0.6836 & 0.248267 \tabularnewline
10 & -0.325554 & -2.6846 & 0.004557 \tabularnewline
11 & 0.396998 & 3.2737 & 0.000835 \tabularnewline
12 & 0.541477 & 4.4651 & 1.5e-05 \tabularnewline
13 & -0.089107 & -0.7348 & 0.232495 \tabularnewline
14 & -0.013813 & -0.1139 & 0.454825 \tabularnewline
15 & 0.068659 & 0.5662 & 0.286569 \tabularnewline
16 & -0.127708 & -1.0531 & 0.14801 \tabularnewline
17 & -0.050763 & -0.4186 & 0.338414 \tabularnewline
18 & -0.135282 & -1.1156 & 0.134268 \tabularnewline
19 & -0.050391 & -0.4155 & 0.339531 \tabularnewline
20 & -0.057777 & -0.4764 & 0.317645 \tabularnewline
21 & -0.038023 & -0.3135 & 0.377413 \tabularnewline
22 & -0.06678 & -0.5507 & 0.291828 \tabularnewline
23 & -0.062288 & -0.5136 & 0.304584 \tabularnewline
24 & -0.040714 & -0.3357 & 0.369051 \tabularnewline
25 & -0.056644 & -0.4671 & 0.320962 \tabularnewline
26 & -0.093468 & -0.7708 & 0.22176 \tabularnewline
27 & 0.018603 & 0.1534 & 0.439265 \tabularnewline
28 & -0.095461 & -0.7872 & 0.216952 \tabularnewline
29 & 0.088925 & 0.7333 & 0.232949 \tabularnewline
30 & -0.0372 & -0.3068 & 0.379982 \tabularnewline
31 & -0.048449 & -0.3995 & 0.345381 \tabularnewline
32 & -0.077058 & -0.6354 & 0.263638 \tabularnewline
33 & -0.031307 & -0.2582 & 0.39853 \tabularnewline
34 & -0.054436 & -0.4489 & 0.32747 \tabularnewline
35 & -0.057251 & -0.4721 & 0.319182 \tabularnewline
36 & -0.093186 & -0.7684 & 0.222447 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64122&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]0.23696[/C][C]1.954[/C][C]0.027406[/C][/ROW]
[ROW][C]2[/C][C]-0.342491[/C][C]-2.8243[/C][C]0.003106[/C][/ROW]
[ROW][C]3[/C][C]-0.117607[/C][C]-0.9698[/C][C]0.167789[/C][/ROW]
[ROW][C]4[/C][C]-0.130088[/C][C]-1.0727[/C][C]0.143591[/C][/ROW]
[ROW][C]5[/C][C]0.023596[/C][C]0.1946[/C][C]0.423153[/C][/ROW]
[ROW][C]6[/C][C]-0.074121[/C][C]-0.6112[/C][C]0.271546[/C][/ROW]
[ROW][C]7[/C][C]0.075129[/C][C]0.6195[/C][C]0.268818[/C][/ROW]
[ROW][C]8[/C][C]-0.214466[/C][C]-1.7685[/C][C]0.040728[/C][/ROW]
[ROW][C]9[/C][C]-0.082902[/C][C]-0.6836[/C][C]0.248267[/C][/ROW]
[ROW][C]10[/C][C]-0.325554[/C][C]-2.6846[/C][C]0.004557[/C][/ROW]
[ROW][C]11[/C][C]0.396998[/C][C]3.2737[/C][C]0.000835[/C][/ROW]
[ROW][C]12[/C][C]0.541477[/C][C]4.4651[/C][C]1.5e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.089107[/C][C]-0.7348[/C][C]0.232495[/C][/ROW]
[ROW][C]14[/C][C]-0.013813[/C][C]-0.1139[/C][C]0.454825[/C][/ROW]
[ROW][C]15[/C][C]0.068659[/C][C]0.5662[/C][C]0.286569[/C][/ROW]
[ROW][C]16[/C][C]-0.127708[/C][C]-1.0531[/C][C]0.14801[/C][/ROW]
[ROW][C]17[/C][C]-0.050763[/C][C]-0.4186[/C][C]0.338414[/C][/ROW]
[ROW][C]18[/C][C]-0.135282[/C][C]-1.1156[/C][C]0.134268[/C][/ROW]
[ROW][C]19[/C][C]-0.050391[/C][C]-0.4155[/C][C]0.339531[/C][/ROW]
[ROW][C]20[/C][C]-0.057777[/C][C]-0.4764[/C][C]0.317645[/C][/ROW]
[ROW][C]21[/C][C]-0.038023[/C][C]-0.3135[/C][C]0.377413[/C][/ROW]
[ROW][C]22[/C][C]-0.06678[/C][C]-0.5507[/C][C]0.291828[/C][/ROW]
[ROW][C]23[/C][C]-0.062288[/C][C]-0.5136[/C][C]0.304584[/C][/ROW]
[ROW][C]24[/C][C]-0.040714[/C][C]-0.3357[/C][C]0.369051[/C][/ROW]
[ROW][C]25[/C][C]-0.056644[/C][C]-0.4671[/C][C]0.320962[/C][/ROW]
[ROW][C]26[/C][C]-0.093468[/C][C]-0.7708[/C][C]0.22176[/C][/ROW]
[ROW][C]27[/C][C]0.018603[/C][C]0.1534[/C][C]0.439265[/C][/ROW]
[ROW][C]28[/C][C]-0.095461[/C][C]-0.7872[/C][C]0.216952[/C][/ROW]
[ROW][C]29[/C][C]0.088925[/C][C]0.7333[/C][C]0.232949[/C][/ROW]
[ROW][C]30[/C][C]-0.0372[/C][C]-0.3068[/C][C]0.379982[/C][/ROW]
[ROW][C]31[/C][C]-0.048449[/C][C]-0.3995[/C][C]0.345381[/C][/ROW]
[ROW][C]32[/C][C]-0.077058[/C][C]-0.6354[/C][C]0.263638[/C][/ROW]
[ROW][C]33[/C][C]-0.031307[/C][C]-0.2582[/C][C]0.39853[/C][/ROW]
[ROW][C]34[/C][C]-0.054436[/C][C]-0.4489[/C][C]0.32747[/C][/ROW]
[ROW][C]35[/C][C]-0.057251[/C][C]-0.4721[/C][C]0.319182[/C][/ROW]
[ROW][C]36[/C][C]-0.093186[/C][C]-0.7684[/C][C]0.222447[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64122&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64122&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
10.236961.9540.027406
2-0.342491-2.82430.003106
3-0.117607-0.96980.167789
4-0.130088-1.07270.143591
50.0235960.19460.423153
6-0.074121-0.61120.271546
70.0751290.61950.268818
8-0.214466-1.76850.040728
9-0.082902-0.68360.248267
10-0.325554-2.68460.004557
110.3969983.27370.000835
120.5414774.46511.5e-05
13-0.089107-0.73480.232495
14-0.013813-0.11390.454825
150.0686590.56620.286569
16-0.127708-1.05310.14801
17-0.050763-0.41860.338414
18-0.135282-1.11560.134268
19-0.050391-0.41550.339531
20-0.057777-0.47640.317645
21-0.038023-0.31350.377413
22-0.06678-0.55070.291828
23-0.062288-0.51360.304584
24-0.040714-0.33570.369051
25-0.056644-0.46710.320962
26-0.093468-0.77080.22176
270.0186030.15340.439265
28-0.095461-0.78720.216952
290.0889250.73330.232949
30-0.0372-0.30680.379982
31-0.048449-0.39950.345381
32-0.077058-0.63540.263638
33-0.031307-0.25820.39853
34-0.054436-0.44890.32747
35-0.057251-0.47210.319182
36-0.093186-0.76840.222447


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')