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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 computationMon, 08 Dec 2008 08:28:54 -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/Dec/08/t1228750149bbdzasmlopx89qj.htm/, Retrieved Thu, 16 May 2024 14:37:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30540, Retrieved Thu, 16 May 2024 14:37:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact242

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] [Taak 7 -Q6 (1)] [2008-11-28 12:13:38] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-         [(Partial) Autocorrelation Function] [Taak 7 -Q6 (4)] [2008-11-28 12:34:42] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-           [(Partial) Autocorrelation Function] [Taak 7 -Q6 (6)] [2008-11-28 12:57:42] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-   P           [(Partial) Autocorrelation Function] [Verbetering Q6] [2008-12-08 15:28:54] [2ae704d6b0222e84f58032588d68322b] [Current]
-   P             [(Partial) Autocorrelation Function] [Verbetering Q6 no...] [2008-12-08 18:38:27] [3754dd41128068acfc463ebbabce5a9c]
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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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30540&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30540&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30540&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'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.332039-3.80040.00011
20.083440.9550.170664
3-0.210458-2.40880.008698
40.0391540.44810.327398
50.0499150.57130.284388
60.0440820.50450.307362
7-0.062545-0.71590.237675
8-0.001067-0.01220.495139
90.1627181.86240.032394
10-0.05311-0.60790.272161
110.0764850.87540.191476
12-0.410552-4.6993e-06
130.1696681.94190.027145
14-0.070911-0.81160.209242
150.1448061.65740.049917
16-0.148873-1.70390.045382
170.0941441.07750.141611
180.0087220.09980.460318
190.0024560.02810.48881
20-0.112715-1.29010.099646
210.0223840.25620.399102
22-0.069491-0.79540.213922
230.211752.42360.008367
24-0.013944-0.15960.436724
25-0.11199-1.28180.10109
260.0404430.46290.322105
27-0.026113-0.29890.382756
280.061910.70860.23992
29-0.026866-0.30750.379477
30-0.053749-0.61520.269748
31-0.039517-0.45230.325905
320.1937132.21710.014169
33-0.123472-1.41320.079983
340.0792220.90670.183105
35-0.178556-2.04370.021495
360.0072280.08270.467096

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.332039 & -3.8004 & 0.00011 \tabularnewline
2 & 0.08344 & 0.955 & 0.170664 \tabularnewline
3 & -0.210458 & -2.4088 & 0.008698 \tabularnewline
4 & 0.039154 & 0.4481 & 0.327398 \tabularnewline
5 & 0.049915 & 0.5713 & 0.284388 \tabularnewline
6 & 0.044082 & 0.5045 & 0.307362 \tabularnewline
7 & -0.062545 & -0.7159 & 0.237675 \tabularnewline
8 & -0.001067 & -0.0122 & 0.495139 \tabularnewline
9 & 0.162718 & 1.8624 & 0.032394 \tabularnewline
10 & -0.05311 & -0.6079 & 0.272161 \tabularnewline
11 & 0.076485 & 0.8754 & 0.191476 \tabularnewline
12 & -0.410552 & -4.699 & 3e-06 \tabularnewline
13 & 0.169668 & 1.9419 & 0.027145 \tabularnewline
14 & -0.070911 & -0.8116 & 0.209242 \tabularnewline
15 & 0.144806 & 1.6574 & 0.049917 \tabularnewline
16 & -0.148873 & -1.7039 & 0.045382 \tabularnewline
17 & 0.094144 & 1.0775 & 0.141611 \tabularnewline
18 & 0.008722 & 0.0998 & 0.460318 \tabularnewline
19 & 0.002456 & 0.0281 & 0.48881 \tabularnewline
20 & -0.112715 & -1.2901 & 0.099646 \tabularnewline
21 & 0.022384 & 0.2562 & 0.399102 \tabularnewline
22 & -0.069491 & -0.7954 & 0.213922 \tabularnewline
23 & 0.21175 & 2.4236 & 0.008367 \tabularnewline
24 & -0.013944 & -0.1596 & 0.436724 \tabularnewline
25 & -0.11199 & -1.2818 & 0.10109 \tabularnewline
26 & 0.040443 & 0.4629 & 0.322105 \tabularnewline
27 & -0.026113 & -0.2989 & 0.382756 \tabularnewline
28 & 0.06191 & 0.7086 & 0.23992 \tabularnewline
29 & -0.026866 & -0.3075 & 0.379477 \tabularnewline
30 & -0.053749 & -0.6152 & 0.269748 \tabularnewline
31 & -0.039517 & -0.4523 & 0.325905 \tabularnewline
32 & 0.193713 & 2.2171 & 0.014169 \tabularnewline
33 & -0.123472 & -1.4132 & 0.079983 \tabularnewline
34 & 0.079222 & 0.9067 & 0.183105 \tabularnewline
35 & -0.178556 & -2.0437 & 0.021495 \tabularnewline
36 & 0.007228 & 0.0827 & 0.467096 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30540&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]-0.332039[/C][C]-3.8004[/C][C]0.00011[/C][/ROW]
[ROW][C]2[/C][C]0.08344[/C][C]0.955[/C][C]0.170664[/C][/ROW]
[ROW][C]3[/C][C]-0.210458[/C][C]-2.4088[/C][C]0.008698[/C][/ROW]
[ROW][C]4[/C][C]0.039154[/C][C]0.4481[/C][C]0.327398[/C][/ROW]
[ROW][C]5[/C][C]0.049915[/C][C]0.5713[/C][C]0.284388[/C][/ROW]
[ROW][C]6[/C][C]0.044082[/C][C]0.5045[/C][C]0.307362[/C][/ROW]
[ROW][C]7[/C][C]-0.062545[/C][C]-0.7159[/C][C]0.237675[/C][/ROW]
[ROW][C]8[/C][C]-0.001067[/C][C]-0.0122[/C][C]0.495139[/C][/ROW]
[ROW][C]9[/C][C]0.162718[/C][C]1.8624[/C][C]0.032394[/C][/ROW]
[ROW][C]10[/C][C]-0.05311[/C][C]-0.6079[/C][C]0.272161[/C][/ROW]
[ROW][C]11[/C][C]0.076485[/C][C]0.8754[/C][C]0.191476[/C][/ROW]
[ROW][C]12[/C][C]-0.410552[/C][C]-4.699[/C][C]3e-06[/C][/ROW]
[ROW][C]13[/C][C]0.169668[/C][C]1.9419[/C][C]0.027145[/C][/ROW]
[ROW][C]14[/C][C]-0.070911[/C][C]-0.8116[/C][C]0.209242[/C][/ROW]
[ROW][C]15[/C][C]0.144806[/C][C]1.6574[/C][C]0.049917[/C][/ROW]
[ROW][C]16[/C][C]-0.148873[/C][C]-1.7039[/C][C]0.045382[/C][/ROW]
[ROW][C]17[/C][C]0.094144[/C][C]1.0775[/C][C]0.141611[/C][/ROW]
[ROW][C]18[/C][C]0.008722[/C][C]0.0998[/C][C]0.460318[/C][/ROW]
[ROW][C]19[/C][C]0.002456[/C][C]0.0281[/C][C]0.48881[/C][/ROW]
[ROW][C]20[/C][C]-0.112715[/C][C]-1.2901[/C][C]0.099646[/C][/ROW]
[ROW][C]21[/C][C]0.022384[/C][C]0.2562[/C][C]0.399102[/C][/ROW]
[ROW][C]22[/C][C]-0.069491[/C][C]-0.7954[/C][C]0.213922[/C][/ROW]
[ROW][C]23[/C][C]0.21175[/C][C]2.4236[/C][C]0.008367[/C][/ROW]
[ROW][C]24[/C][C]-0.013944[/C][C]-0.1596[/C][C]0.436724[/C][/ROW]
[ROW][C]25[/C][C]-0.11199[/C][C]-1.2818[/C][C]0.10109[/C][/ROW]
[ROW][C]26[/C][C]0.040443[/C][C]0.4629[/C][C]0.322105[/C][/ROW]
[ROW][C]27[/C][C]-0.026113[/C][C]-0.2989[/C][C]0.382756[/C][/ROW]
[ROW][C]28[/C][C]0.06191[/C][C]0.7086[/C][C]0.23992[/C][/ROW]
[ROW][C]29[/C][C]-0.026866[/C][C]-0.3075[/C][C]0.379477[/C][/ROW]
[ROW][C]30[/C][C]-0.053749[/C][C]-0.6152[/C][C]0.269748[/C][/ROW]
[ROW][C]31[/C][C]-0.039517[/C][C]-0.4523[/C][C]0.325905[/C][/ROW]
[ROW][C]32[/C][C]0.193713[/C][C]2.2171[/C][C]0.014169[/C][/ROW]
[ROW][C]33[/C][C]-0.123472[/C][C]-1.4132[/C][C]0.079983[/C][/ROW]
[ROW][C]34[/C][C]0.079222[/C][C]0.9067[/C][C]0.183105[/C][/ROW]
[ROW][C]35[/C][C]-0.178556[/C][C]-2.0437[/C][C]0.021495[/C][/ROW]
[ROW][C]36[/C][C]0.007228[/C][C]0.0827[/C][C]0.467096[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30540&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30540&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
1-0.332039-3.80040.00011
20.083440.9550.170664
3-0.210458-2.40880.008698
40.0391540.44810.327398
50.0499150.57130.284388
60.0440820.50450.307362
7-0.062545-0.71590.237675
8-0.001067-0.01220.495139
90.1627181.86240.032394
10-0.05311-0.60790.272161
110.0764850.87540.191476
12-0.410552-4.6993e-06
130.1696681.94190.027145
14-0.070911-0.81160.209242
150.1448061.65740.049917
16-0.148873-1.70390.045382
170.0941441.07750.141611
180.0087220.09980.460318
190.0024560.02810.48881
20-0.112715-1.29010.099646
210.0223840.25620.399102
22-0.069491-0.79540.213922
230.211752.42360.008367
24-0.013944-0.15960.436724
25-0.11199-1.28180.10109
260.0404430.46290.322105
27-0.026113-0.29890.382756
280.061910.70860.23992
29-0.026866-0.30750.379477
30-0.053749-0.61520.269748
31-0.039517-0.45230.325905
320.1937132.21710.014169
33-0.123472-1.41320.079983
340.0792220.90670.183105
35-0.178556-2.04370.021495
360.0072280.08270.467096






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.332039-3.80040.00011
2-0.030132-0.34490.365372
3-0.215899-2.47110.007377
4-0.114704-1.31280.095766
50.0279820.32030.374638
60.0378550.43330.332767
7-0.052061-0.59590.276146
8-0.016784-0.19210.423981
90.2092842.39540.009009
100.0593970.67980.248906
110.0915281.04760.14838
12-0.351236-4.02014.9e-05
13-0.09691-1.10920.134691
14-0.088253-1.01010.157154
15-0.063526-0.72710.234235
16-0.170035-1.94610.026889
170.0397630.45510.32489
180.1321321.51230.06643
19-0.003849-0.04410.482464
20-0.127537-1.45970.07338
210.1340731.53450.063655
22-0.039893-0.45660.324357
230.1820592.08380.019562
24-0.074983-0.85820.19617
25-0.107887-1.23480.109553
26-0.038152-0.43670.331534
27-0.004094-0.04690.48135
28-0.125009-1.43080.077436
290.0383610.43910.33067
300.0057170.06540.473964
31-0.061196-0.70040.242453
320.0375050.42930.334219
330.0249780.28590.387709
340.0120340.13770.44533
350.0294660.33730.368232
36-0.165042-1.8890.030552

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.332039 & -3.8004 & 0.00011 \tabularnewline
2 & -0.030132 & -0.3449 & 0.365372 \tabularnewline
3 & -0.215899 & -2.4711 & 0.007377 \tabularnewline
4 & -0.114704 & -1.3128 & 0.095766 \tabularnewline
5 & 0.027982 & 0.3203 & 0.374638 \tabularnewline
6 & 0.037855 & 0.4333 & 0.332767 \tabularnewline
7 & -0.052061 & -0.5959 & 0.276146 \tabularnewline
8 & -0.016784 & -0.1921 & 0.423981 \tabularnewline
9 & 0.209284 & 2.3954 & 0.009009 \tabularnewline
10 & 0.059397 & 0.6798 & 0.248906 \tabularnewline
11 & 0.091528 & 1.0476 & 0.14838 \tabularnewline
12 & -0.351236 & -4.0201 & 4.9e-05 \tabularnewline
13 & -0.09691 & -1.1092 & 0.134691 \tabularnewline
14 & -0.088253 & -1.0101 & 0.157154 \tabularnewline
15 & -0.063526 & -0.7271 & 0.234235 \tabularnewline
16 & -0.170035 & -1.9461 & 0.026889 \tabularnewline
17 & 0.039763 & 0.4551 & 0.32489 \tabularnewline
18 & 0.132132 & 1.5123 & 0.06643 \tabularnewline
19 & -0.003849 & -0.0441 & 0.482464 \tabularnewline
20 & -0.127537 & -1.4597 & 0.07338 \tabularnewline
21 & 0.134073 & 1.5345 & 0.063655 \tabularnewline
22 & -0.039893 & -0.4566 & 0.324357 \tabularnewline
23 & 0.182059 & 2.0838 & 0.019562 \tabularnewline
24 & -0.074983 & -0.8582 & 0.19617 \tabularnewline
25 & -0.107887 & -1.2348 & 0.109553 \tabularnewline
26 & -0.038152 & -0.4367 & 0.331534 \tabularnewline
27 & -0.004094 & -0.0469 & 0.48135 \tabularnewline
28 & -0.125009 & -1.4308 & 0.077436 \tabularnewline
29 & 0.038361 & 0.4391 & 0.33067 \tabularnewline
30 & 0.005717 & 0.0654 & 0.473964 \tabularnewline
31 & -0.061196 & -0.7004 & 0.242453 \tabularnewline
32 & 0.037505 & 0.4293 & 0.334219 \tabularnewline
33 & 0.024978 & 0.2859 & 0.387709 \tabularnewline
34 & 0.012034 & 0.1377 & 0.44533 \tabularnewline
35 & 0.029466 & 0.3373 & 0.368232 \tabularnewline
36 & -0.165042 & -1.889 & 0.030552 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30540&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]-0.332039[/C][C]-3.8004[/C][C]0.00011[/C][/ROW]
[ROW][C]2[/C][C]-0.030132[/C][C]-0.3449[/C][C]0.365372[/C][/ROW]
[ROW][C]3[/C][C]-0.215899[/C][C]-2.4711[/C][C]0.007377[/C][/ROW]
[ROW][C]4[/C][C]-0.114704[/C][C]-1.3128[/C][C]0.095766[/C][/ROW]
[ROW][C]5[/C][C]0.027982[/C][C]0.3203[/C][C]0.374638[/C][/ROW]
[ROW][C]6[/C][C]0.037855[/C][C]0.4333[/C][C]0.332767[/C][/ROW]
[ROW][C]7[/C][C]-0.052061[/C][C]-0.5959[/C][C]0.276146[/C][/ROW]
[ROW][C]8[/C][C]-0.016784[/C][C]-0.1921[/C][C]0.423981[/C][/ROW]
[ROW][C]9[/C][C]0.209284[/C][C]2.3954[/C][C]0.009009[/C][/ROW]
[ROW][C]10[/C][C]0.059397[/C][C]0.6798[/C][C]0.248906[/C][/ROW]
[ROW][C]11[/C][C]0.091528[/C][C]1.0476[/C][C]0.14838[/C][/ROW]
[ROW][C]12[/C][C]-0.351236[/C][C]-4.0201[/C][C]4.9e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.09691[/C][C]-1.1092[/C][C]0.134691[/C][/ROW]
[ROW][C]14[/C][C]-0.088253[/C][C]-1.0101[/C][C]0.157154[/C][/ROW]
[ROW][C]15[/C][C]-0.063526[/C][C]-0.7271[/C][C]0.234235[/C][/ROW]
[ROW][C]16[/C][C]-0.170035[/C][C]-1.9461[/C][C]0.026889[/C][/ROW]
[ROW][C]17[/C][C]0.039763[/C][C]0.4551[/C][C]0.32489[/C][/ROW]
[ROW][C]18[/C][C]0.132132[/C][C]1.5123[/C][C]0.06643[/C][/ROW]
[ROW][C]19[/C][C]-0.003849[/C][C]-0.0441[/C][C]0.482464[/C][/ROW]
[ROW][C]20[/C][C]-0.127537[/C][C]-1.4597[/C][C]0.07338[/C][/ROW]
[ROW][C]21[/C][C]0.134073[/C][C]1.5345[/C][C]0.063655[/C][/ROW]
[ROW][C]22[/C][C]-0.039893[/C][C]-0.4566[/C][C]0.324357[/C][/ROW]
[ROW][C]23[/C][C]0.182059[/C][C]2.0838[/C][C]0.019562[/C][/ROW]
[ROW][C]24[/C][C]-0.074983[/C][C]-0.8582[/C][C]0.19617[/C][/ROW]
[ROW][C]25[/C][C]-0.107887[/C][C]-1.2348[/C][C]0.109553[/C][/ROW]
[ROW][C]26[/C][C]-0.038152[/C][C]-0.4367[/C][C]0.331534[/C][/ROW]
[ROW][C]27[/C][C]-0.004094[/C][C]-0.0469[/C][C]0.48135[/C][/ROW]
[ROW][C]28[/C][C]-0.125009[/C][C]-1.4308[/C][C]0.077436[/C][/ROW]
[ROW][C]29[/C][C]0.038361[/C][C]0.4391[/C][C]0.33067[/C][/ROW]
[ROW][C]30[/C][C]0.005717[/C][C]0.0654[/C][C]0.473964[/C][/ROW]
[ROW][C]31[/C][C]-0.061196[/C][C]-0.7004[/C][C]0.242453[/C][/ROW]
[ROW][C]32[/C][C]0.037505[/C][C]0.4293[/C][C]0.334219[/C][/ROW]
[ROW][C]33[/C][C]0.024978[/C][C]0.2859[/C][C]0.387709[/C][/ROW]
[ROW][C]34[/C][C]0.012034[/C][C]0.1377[/C][C]0.44533[/C][/ROW]
[ROW][C]35[/C][C]0.029466[/C][C]0.3373[/C][C]0.368232[/C][/ROW]
[ROW][C]36[/C][C]-0.165042[/C][C]-1.889[/C][C]0.030552[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30540&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30540&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
1-0.332039-3.80040.00011
2-0.030132-0.34490.365372
3-0.215899-2.47110.007377
4-0.114704-1.31280.095766
50.0279820.32030.374638
60.0378550.43330.332767
7-0.052061-0.59590.276146
8-0.016784-0.19210.423981
90.2092842.39540.009009
100.0593970.67980.248906
110.0915281.04760.14838
12-0.351236-4.02014.9e-05
13-0.09691-1.10920.134691
14-0.088253-1.01010.157154
15-0.063526-0.72710.234235
16-0.170035-1.94610.026889
170.0397630.45510.32489
180.1321321.51230.06643
19-0.003849-0.04410.482464
20-0.127537-1.45970.07338
210.1340731.53450.063655
22-0.039893-0.45660.324357
230.1820592.08380.019562
24-0.074983-0.85820.19617
25-0.107887-1.23480.109553
26-0.038152-0.43670.331534
27-0.004094-0.04690.48135
28-0.125009-1.43080.077436
290.0383610.43910.33067
300.0057170.06540.473964
31-0.061196-0.70040.242453
320.0375050.42930.334219
330.0249780.28590.387709
340.0120340.13770.44533
350.0294660.33730.368232
36-0.165042-1.8890.030552


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -0.3 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = -0.3 ; par3 = 1 ; par4 = 1 ; 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')