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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, 28 Nov 2008 12:58:31 -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/2008/Nov/28/t1227902721siprf5209axja3j.htm/, Retrieved Sun, 19 May 2024 10:10:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26169, Retrieved Sun, 19 May 2024 10:10:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [(Partial) Autocorrelation Function] [Q5 - Autocorrelat...] [2008-11-28 19:54:49] [7a664918911e34206ce9d0436dd7c1c8]
-   P       [(Partial) Autocorrelation Function] [Q5 - Autocorrelat...] [2008-11-28 19:58:31] [98255691c21504803b38711776845ae0] [Current]
-   P         [(Partial) Autocorrelation Function] [Q5 - Autocorrelat...] [2008-11-28 20:06:31] [7a664918911e34206ce9d0436dd7c1c8]
F RMP           [Standard Deviation-Mean Plot] [Q5 - Standaarddev...] [2008-11-28 20:34:13] [7a664918911e34206ce9d0436dd7c1c8]
F   P           [(Partial) Autocorrelation Function] [Q5 - Autocorrelat...] [2008-12-02 16:24:50] [7a664918911e34206ce9d0436dd7c1c8]
-   P         [(Partial) Autocorrelation Function] [Q5 - Autocorrelat...] [2008-12-02 16:21:42] [7a664918911e34206ce9d0436dd7c1c8]
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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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26169&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26169&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1997512.38870.009107
2-0.120104-1.43620.076559
3-0.150772-1.8030.036749
4-0.322074-3.85148.8e-05
5-0.083975-1.00420.158492
60.0257780.30830.379165
7-0.110961-1.32690.093329
8-0.336721-4.02664.6e-05
9-0.115586-1.38220.084531
10-0.109267-1.30660.096716
110.2058522.46160.00751
120.8414310.0620
130.2150872.57210.005565
14-0.139554-1.66880.04867
15-0.115996-1.38710.083784
16-0.278943-3.33570.000542
17-0.051706-0.61830.268674
180.0124580.1490.440891
19-0.114358-1.36750.086804
20-0.337174-4.0324.5e-05
21-0.107385-1.28410.100585
22-0.075211-0.89940.184977
230.1994752.38540.009186
240.7369218.81230
250.1972622.35890.009841
26-0.123884-1.48140.070345
27-0.102699-1.22810.110713
28-0.210992-2.52310.006363
29-0.065357-0.78160.217884
300.0157280.18810.425538
31-0.11537-1.37960.084927
32-0.289256-3.4590.000357
33-0.126882-1.51730.0657
34-0.040707-0.48680.313579
350.1474111.76280.040037
360.6574387.86180

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.199751 & 2.3887 & 0.009107 \tabularnewline
2 & -0.120104 & -1.4362 & 0.076559 \tabularnewline
3 & -0.150772 & -1.803 & 0.036749 \tabularnewline
4 & -0.322074 & -3.8514 & 8.8e-05 \tabularnewline
5 & -0.083975 & -1.0042 & 0.158492 \tabularnewline
6 & 0.025778 & 0.3083 & 0.379165 \tabularnewline
7 & -0.110961 & -1.3269 & 0.093329 \tabularnewline
8 & -0.336721 & -4.0266 & 4.6e-05 \tabularnewline
9 & -0.115586 & -1.3822 & 0.084531 \tabularnewline
10 & -0.109267 & -1.3066 & 0.096716 \tabularnewline
11 & 0.205852 & 2.4616 & 0.00751 \tabularnewline
12 & 0.84143 & 10.062 & 0 \tabularnewline
13 & 0.215087 & 2.5721 & 0.005565 \tabularnewline
14 & -0.139554 & -1.6688 & 0.04867 \tabularnewline
15 & -0.115996 & -1.3871 & 0.083784 \tabularnewline
16 & -0.278943 & -3.3357 & 0.000542 \tabularnewline
17 & -0.051706 & -0.6183 & 0.268674 \tabularnewline
18 & 0.012458 & 0.149 & 0.440891 \tabularnewline
19 & -0.114358 & -1.3675 & 0.086804 \tabularnewline
20 & -0.337174 & -4.032 & 4.5e-05 \tabularnewline
21 & -0.107385 & -1.2841 & 0.100585 \tabularnewline
22 & -0.075211 & -0.8994 & 0.184977 \tabularnewline
23 & 0.199475 & 2.3854 & 0.009186 \tabularnewline
24 & 0.736921 & 8.8123 & 0 \tabularnewline
25 & 0.197262 & 2.3589 & 0.009841 \tabularnewline
26 & -0.123884 & -1.4814 & 0.070345 \tabularnewline
27 & -0.102699 & -1.2281 & 0.110713 \tabularnewline
28 & -0.210992 & -2.5231 & 0.006363 \tabularnewline
29 & -0.065357 & -0.7816 & 0.217884 \tabularnewline
30 & 0.015728 & 0.1881 & 0.425538 \tabularnewline
31 & -0.11537 & -1.3796 & 0.084927 \tabularnewline
32 & -0.289256 & -3.459 & 0.000357 \tabularnewline
33 & -0.126882 & -1.5173 & 0.0657 \tabularnewline
34 & -0.040707 & -0.4868 & 0.313579 \tabularnewline
35 & 0.147411 & 1.7628 & 0.040037 \tabularnewline
36 & 0.657438 & 7.8618 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26169&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]0.199751[/C][C]2.3887[/C][C]0.009107[/C][/ROW]
[ROW][C]2[/C][C]-0.120104[/C][C]-1.4362[/C][C]0.076559[/C][/ROW]
[ROW][C]3[/C][C]-0.150772[/C][C]-1.803[/C][C]0.036749[/C][/ROW]
[ROW][C]4[/C][C]-0.322074[/C][C]-3.8514[/C][C]8.8e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.083975[/C][C]-1.0042[/C][C]0.158492[/C][/ROW]
[ROW][C]6[/C][C]0.025778[/C][C]0.3083[/C][C]0.379165[/C][/ROW]
[ROW][C]7[/C][C]-0.110961[/C][C]-1.3269[/C][C]0.093329[/C][/ROW]
[ROW][C]8[/C][C]-0.336721[/C][C]-4.0266[/C][C]4.6e-05[/C][/ROW]
[ROW][C]9[/C][C]-0.115586[/C][C]-1.3822[/C][C]0.084531[/C][/ROW]
[ROW][C]10[/C][C]-0.109267[/C][C]-1.3066[/C][C]0.096716[/C][/ROW]
[ROW][C]11[/C][C]0.205852[/C][C]2.4616[/C][C]0.00751[/C][/ROW]
[ROW][C]12[/C][C]0.84143[/C][C]10.062[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.215087[/C][C]2.5721[/C][C]0.005565[/C][/ROW]
[ROW][C]14[/C][C]-0.139554[/C][C]-1.6688[/C][C]0.04867[/C][/ROW]
[ROW][C]15[/C][C]-0.115996[/C][C]-1.3871[/C][C]0.083784[/C][/ROW]
[ROW][C]16[/C][C]-0.278943[/C][C]-3.3357[/C][C]0.000542[/C][/ROW]
[ROW][C]17[/C][C]-0.051706[/C][C]-0.6183[/C][C]0.268674[/C][/ROW]
[ROW][C]18[/C][C]0.012458[/C][C]0.149[/C][C]0.440891[/C][/ROW]
[ROW][C]19[/C][C]-0.114358[/C][C]-1.3675[/C][C]0.086804[/C][/ROW]
[ROW][C]20[/C][C]-0.337174[/C][C]-4.032[/C][C]4.5e-05[/C][/ROW]
[ROW][C]21[/C][C]-0.107385[/C][C]-1.2841[/C][C]0.100585[/C][/ROW]
[ROW][C]22[/C][C]-0.075211[/C][C]-0.8994[/C][C]0.184977[/C][/ROW]
[ROW][C]23[/C][C]0.199475[/C][C]2.3854[/C][C]0.009186[/C][/ROW]
[ROW][C]24[/C][C]0.736921[/C][C]8.8123[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.197262[/C][C]2.3589[/C][C]0.009841[/C][/ROW]
[ROW][C]26[/C][C]-0.123884[/C][C]-1.4814[/C][C]0.070345[/C][/ROW]
[ROW][C]27[/C][C]-0.102699[/C][C]-1.2281[/C][C]0.110713[/C][/ROW]
[ROW][C]28[/C][C]-0.210992[/C][C]-2.5231[/C][C]0.006363[/C][/ROW]
[ROW][C]29[/C][C]-0.065357[/C][C]-0.7816[/C][C]0.217884[/C][/ROW]
[ROW][C]30[/C][C]0.015728[/C][C]0.1881[/C][C]0.425538[/C][/ROW]
[ROW][C]31[/C][C]-0.11537[/C][C]-1.3796[/C][C]0.084927[/C][/ROW]
[ROW][C]32[/C][C]-0.289256[/C][C]-3.459[/C][C]0.000357[/C][/ROW]
[ROW][C]33[/C][C]-0.126882[/C][C]-1.5173[/C][C]0.0657[/C][/ROW]
[ROW][C]34[/C][C]-0.040707[/C][C]-0.4868[/C][C]0.313579[/C][/ROW]
[ROW][C]35[/C][C]0.147411[/C][C]1.7628[/C][C]0.040037[/C][/ROW]
[ROW][C]36[/C][C]0.657438[/C][C]7.8618[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26169&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
10.1997512.38870.009107
2-0.120104-1.43620.076559
3-0.150772-1.8030.036749
4-0.322074-3.85148.8e-05
5-0.083975-1.00420.158492
60.0257780.30830.379165
7-0.110961-1.32690.093329
8-0.336721-4.02664.6e-05
9-0.115586-1.38220.084531
10-0.109267-1.30660.096716
110.2058522.46160.00751
120.8414310.0620
130.2150872.57210.005565
14-0.139554-1.66880.04867
15-0.115996-1.38710.083784
16-0.278943-3.33570.000542
17-0.051706-0.61830.268674
180.0124580.1490.440891
19-0.114358-1.36750.086804
20-0.337174-4.0324.5e-05
21-0.107385-1.28410.100585
22-0.075211-0.89940.184977
230.1994752.38540.009186
240.7369218.81230
250.1972622.35890.009841
26-0.123884-1.48140.070345
27-0.102699-1.22810.110713
28-0.210992-2.52310.006363
29-0.065357-0.78160.217884
300.0157280.18810.425538
31-0.11537-1.37960.084927
32-0.289256-3.4590.000357
33-0.126882-1.51730.0657
34-0.040707-0.48680.313579
350.1474111.76280.040037
360.6574387.86180






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1997512.38870.009107
2-0.166655-1.99290.024088
3-0.095875-1.14650.126751
4-0.310891-3.71770.000144
50.0077850.09310.46298
6-0.07455-0.89150.187084
7-0.210284-2.51460.006511
8-0.494757-5.91640
9-0.192295-2.29950.011462
10-0.531875-6.36030
11-0.302293-3.61490.000208
120.5860417.0080
130.0259780.31070.378257
14-0.181193-2.16670.015955
150.1200381.43550.076671
160.0004080.00490.498059
170.025260.30210.381519
18-0.124989-1.49470.068604
190.0874351.04560.148763
20-0.054471-0.65140.257923
21-0.061824-0.73930.230468
22-0.025195-0.30130.381815
230.0333310.39860.345396
24-0.009634-0.11520.45422
25-0.048057-0.57470.283204
260.0184870.22110.412677
270.0279780.33460.369219
280.0163090.1950.422822
29-0.093457-1.11760.132808
300.0084980.10160.459602
310.0714610.85460.197114
320.1095151.30960.096213
33-0.093183-1.11430.133508
340.0631340.7550.225752
35-0.092056-1.10080.136411
360.0584040.69840.243029

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.199751 & 2.3887 & 0.009107 \tabularnewline
2 & -0.166655 & -1.9929 & 0.024088 \tabularnewline
3 & -0.095875 & -1.1465 & 0.126751 \tabularnewline
4 & -0.310891 & -3.7177 & 0.000144 \tabularnewline
5 & 0.007785 & 0.0931 & 0.46298 \tabularnewline
6 & -0.07455 & -0.8915 & 0.187084 \tabularnewline
7 & -0.210284 & -2.5146 & 0.006511 \tabularnewline
8 & -0.494757 & -5.9164 & 0 \tabularnewline
9 & -0.192295 & -2.2995 & 0.011462 \tabularnewline
10 & -0.531875 & -6.3603 & 0 \tabularnewline
11 & -0.302293 & -3.6149 & 0.000208 \tabularnewline
12 & 0.586041 & 7.008 & 0 \tabularnewline
13 & 0.025978 & 0.3107 & 0.378257 \tabularnewline
14 & -0.181193 & -2.1667 & 0.015955 \tabularnewline
15 & 0.120038 & 1.4355 & 0.076671 \tabularnewline
16 & 0.000408 & 0.0049 & 0.498059 \tabularnewline
17 & 0.02526 & 0.3021 & 0.381519 \tabularnewline
18 & -0.124989 & -1.4947 & 0.068604 \tabularnewline
19 & 0.087435 & 1.0456 & 0.148763 \tabularnewline
20 & -0.054471 & -0.6514 & 0.257923 \tabularnewline
21 & -0.061824 & -0.7393 & 0.230468 \tabularnewline
22 & -0.025195 & -0.3013 & 0.381815 \tabularnewline
23 & 0.033331 & 0.3986 & 0.345396 \tabularnewline
24 & -0.009634 & -0.1152 & 0.45422 \tabularnewline
25 & -0.048057 & -0.5747 & 0.283204 \tabularnewline
26 & 0.018487 & 0.2211 & 0.412677 \tabularnewline
27 & 0.027978 & 0.3346 & 0.369219 \tabularnewline
28 & 0.016309 & 0.195 & 0.422822 \tabularnewline
29 & -0.093457 & -1.1176 & 0.132808 \tabularnewline
30 & 0.008498 & 0.1016 & 0.459602 \tabularnewline
31 & 0.071461 & 0.8546 & 0.197114 \tabularnewline
32 & 0.109515 & 1.3096 & 0.096213 \tabularnewline
33 & -0.093183 & -1.1143 & 0.133508 \tabularnewline
34 & 0.063134 & 0.755 & 0.225752 \tabularnewline
35 & -0.092056 & -1.1008 & 0.136411 \tabularnewline
36 & 0.058404 & 0.6984 & 0.243029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26169&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]0.199751[/C][C]2.3887[/C][C]0.009107[/C][/ROW]
[ROW][C]2[/C][C]-0.166655[/C][C]-1.9929[/C][C]0.024088[/C][/ROW]
[ROW][C]3[/C][C]-0.095875[/C][C]-1.1465[/C][C]0.126751[/C][/ROW]
[ROW][C]4[/C][C]-0.310891[/C][C]-3.7177[/C][C]0.000144[/C][/ROW]
[ROW][C]5[/C][C]0.007785[/C][C]0.0931[/C][C]0.46298[/C][/ROW]
[ROW][C]6[/C][C]-0.07455[/C][C]-0.8915[/C][C]0.187084[/C][/ROW]
[ROW][C]7[/C][C]-0.210284[/C][C]-2.5146[/C][C]0.006511[/C][/ROW]
[ROW][C]8[/C][C]-0.494757[/C][C]-5.9164[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]-0.192295[/C][C]-2.2995[/C][C]0.011462[/C][/ROW]
[ROW][C]10[/C][C]-0.531875[/C][C]-6.3603[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]-0.302293[/C][C]-3.6149[/C][C]0.000208[/C][/ROW]
[ROW][C]12[/C][C]0.586041[/C][C]7.008[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.025978[/C][C]0.3107[/C][C]0.378257[/C][/ROW]
[ROW][C]14[/C][C]-0.181193[/C][C]-2.1667[/C][C]0.015955[/C][/ROW]
[ROW][C]15[/C][C]0.120038[/C][C]1.4355[/C][C]0.076671[/C][/ROW]
[ROW][C]16[/C][C]0.000408[/C][C]0.0049[/C][C]0.498059[/C][/ROW]
[ROW][C]17[/C][C]0.02526[/C][C]0.3021[/C][C]0.381519[/C][/ROW]
[ROW][C]18[/C][C]-0.124989[/C][C]-1.4947[/C][C]0.068604[/C][/ROW]
[ROW][C]19[/C][C]0.087435[/C][C]1.0456[/C][C]0.148763[/C][/ROW]
[ROW][C]20[/C][C]-0.054471[/C][C]-0.6514[/C][C]0.257923[/C][/ROW]
[ROW][C]21[/C][C]-0.061824[/C][C]-0.7393[/C][C]0.230468[/C][/ROW]
[ROW][C]22[/C][C]-0.025195[/C][C]-0.3013[/C][C]0.381815[/C][/ROW]
[ROW][C]23[/C][C]0.033331[/C][C]0.3986[/C][C]0.345396[/C][/ROW]
[ROW][C]24[/C][C]-0.009634[/C][C]-0.1152[/C][C]0.45422[/C][/ROW]
[ROW][C]25[/C][C]-0.048057[/C][C]-0.5747[/C][C]0.283204[/C][/ROW]
[ROW][C]26[/C][C]0.018487[/C][C]0.2211[/C][C]0.412677[/C][/ROW]
[ROW][C]27[/C][C]0.027978[/C][C]0.3346[/C][C]0.369219[/C][/ROW]
[ROW][C]28[/C][C]0.016309[/C][C]0.195[/C][C]0.422822[/C][/ROW]
[ROW][C]29[/C][C]-0.093457[/C][C]-1.1176[/C][C]0.132808[/C][/ROW]
[ROW][C]30[/C][C]0.008498[/C][C]0.1016[/C][C]0.459602[/C][/ROW]
[ROW][C]31[/C][C]0.071461[/C][C]0.8546[/C][C]0.197114[/C][/ROW]
[ROW][C]32[/C][C]0.109515[/C][C]1.3096[/C][C]0.096213[/C][/ROW]
[ROW][C]33[/C][C]-0.093183[/C][C]-1.1143[/C][C]0.133508[/C][/ROW]
[ROW][C]34[/C][C]0.063134[/C][C]0.755[/C][C]0.225752[/C][/ROW]
[ROW][C]35[/C][C]-0.092056[/C][C]-1.1008[/C][C]0.136411[/C][/ROW]
[ROW][C]36[/C][C]0.058404[/C][C]0.6984[/C][C]0.243029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26169&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26169&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
10.1997512.38870.009107
2-0.166655-1.99290.024088
3-0.095875-1.14650.126751
4-0.310891-3.71770.000144
50.0077850.09310.46298
6-0.07455-0.89150.187084
7-0.210284-2.51460.006511
8-0.494757-5.91640
9-0.192295-2.29950.011462
10-0.531875-6.36030
11-0.302293-3.61490.000208
120.5860417.0080
130.0259780.31070.378257
14-0.181193-2.16670.015955
150.1200381.43550.076671
160.0004080.00490.498059
170.025260.30210.381519
18-0.124989-1.49470.068604
190.0874351.04560.148763
20-0.054471-0.65140.257923
21-0.061824-0.73930.230468
22-0.025195-0.30130.381815
230.0333310.39860.345396
24-0.009634-0.11520.45422
25-0.048057-0.57470.283204
260.0184870.22110.412677
270.0279780.33460.369219
280.0163090.1950.422822
29-0.093457-1.11760.132808
300.0084980.10160.459602
310.0714610.85460.197114
320.1095151.30960.096213
33-0.093183-1.11430.133508
340.0631340.7550.225752
35-0.092056-1.10080.136411
360.0584040.69840.243029


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')