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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, 16 Dec 2011 10:43:57 -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/16/t1324050266zj9adeyztyymd6a.htm/, Retrieved Fri, 19 Apr 2024 19:23:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156064, Retrieved Fri, 19 Apr 2024 19:23:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Central Tendency] [Workshop 8 STAP 1...] [2011-11-26 13:04:08] [de8512d9b386046939a89973b76869e3]
- RMPD    [Decomposition by Loess] [Workshop 8 STAP 3...] [2011-11-26 14:09:35] [de8512d9b386046939a89973b76869e3]
- RMP       [Structural Time Series Models] [Workshop 8 STAP 3...] [2011-11-26 14:16:57] [de8512d9b386046939a89973b76869e3]
- RMPD        [Multiple Regression] [Workshop 8 STAP 5...] [2011-11-26 14:57:33] [de8512d9b386046939a89973b76869e3]
- RMPD            [(Partial) Autocorrelation Function] [Paper SHW Deel 2...] [2011-12-16 15:43:57] [5c44e6aad476a1bab98fc6774eca4c08] [Current]
- RM                [Standard Deviation-Mean Plot] [Paper SHW Deel 2 ...] [2011-12-16 15:59:09] [de8512d9b386046939a89973b76869e3]
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Dataseries X:
235.10
280.70
264.60
240.70
201.40
240.80
241.10
223.80
206.10
174.70
203.30
220.50
299.50
347.40
338.30
327.70
351.60
396.60
438.80
395.60
363.50
378.80
357.00
369.00
464.80
479.10
431.30
366.50
326.30
355.10
331.60
261.30
249.00
205.50
235.60
240.90
264.90
253.80
232.30
193.80
177.00
213.20
207.20
180.60
188.60
175.40
199.00
179.60
225.80
234.00
200.20
183.60
178.20
203.20
208.50
191.80
172.80
148.00
159.40
154.50
213.20
196.40
182.80
176.40
153.60
173.20
171.00
151.20
161.90
157.20
201.70
236.40
356.10
398.30
403.70
384.60
365.80
368.10
367.90
347.00
343.30
292.90
311.50
300.90
366.90
356.90
329.70
316.20
269.00
289.30
266.20
253.60
233.80
228.40
253.60
260.10
306.60
309.20
309.50
271.00
279.90
317.90
298.40
246.70
227.30
209.10
259.90
266.00
320.60
308.50
282.20
262.70
263.50
313.10
284.30
252.60
250.30
246.50
312.70
333.20
446.40
511.60
515.50
506.40
483.20
522.30
509.80
460.70
405.80
375.00
378.50
406.80
467.80
469.80
429.80
355.80
332.70
378.00
360.50
334.70
319.50
323.10
363.60
352.10
411.90
388.60
416.40
360.70
338.00
417.20
388.40
371.10
331.50
353.70
396.70
447.00
533.50
565.40
542.30
488.70
467.10
531.30
496.10
444.00
403.40
386.30
394.10
404.10
462.10
448.10
432.30
386.30
395.20
421.90
382.90
384.20
345.50
323.40
372.60
376.00
462.70
487.00
444.20
399.30
394.90
455.40
414.00
375.50
347.00
339.40
385.80
378.80
451.80
446.10
422.50
383.10
352.80
445.30
367.50
355.10
326.20
319.80
331.80
340.90
394.10
417.20
369.90
349.20
321.40
405.70
342.90
316.50
284.20
270.90
288.80
278.80
324.40
310.90
299.00
273.00
279.30
359.20
305.00
282.10
250.30
246.50
257.90
266.50
315.90
318.40
295.40
266.40
245.80
362.80
324.90
294.20
289.50
295.20
290.30
272.00
307.40
328.70
292.90
249.10
230.40
361.50
321.70
277.20
260.70
251.00
257.60
241.80
287.50
292.30
274.70
254.20
230.00
339.00
318.20
287.00
295.80
284.00
271.00
262.70
340.60
379.40
373.30
355.20
338.40
466.90
451.00
422.00
429.20
425.90
460.70
463.60
541.40
544.20
517.50
469.40
439.40
549.00
533.00
506.10
484.00
457.00
481.50
469.50
544.70
541.20
521.50
469.70
434.40
542.60
517.30
485.70
465.80
447.00
426.60
411.60
467.50
484.50
451.20
417.40
379.90
484.70
455.00
420.80
416.50
376.30
405.60
405.80
500.80
514.00
475.50
430.10
414.40
538.00
526.00
488.50
520.20
504.40
568.50
610.60
818.00
830.90
835.90
782.00
762.30
856.90
820.90
769.60
752.20
724.40
723.10
719.50
817.40
803.30
752.50
689.00
630.40
765.50
757.70
732.20
702.60
683.30
709.50
702.20
784.80
810.90
755.60
656.80
615.10
745.30
694.10
675.70
643.70
622.10
634.60
588.00
689.70
673.90
647.90
568.80
545.70
632.60
643.80
593.10
579.70
546.00
562.90
572.50




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=156064&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=156064&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156064&T=0

As an alternative you can also use a 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
10.2101413.98164.1e-05
20.3251316.16030
30.1532752.90410.001955
40.1672523.1690.000831
50.0991561.87870.030545
60.0645131.22230.111191
7-0.057203-1.08380.13958
8-0.023244-0.44040.329956
9-0.085115-1.61270.053845
10-0.168424-3.19120.000771
11-0.075939-1.43880.075533
12-0.475334-9.00630
13-0.179215-3.39560.000381
14-0.162819-3.0850.001097
15-0.106644-2.02060.02203
16-0.147945-2.80320.002668
17-0.091478-1.73330.041954
18-0.089745-1.70040.044958
190.0273280.51780.302458
20-0.012913-0.24470.403425
210.0241990.45850.323437
22-0.018741-0.35510.361367
230.0095670.18130.42813
24-0.022226-0.42110.336957
250.0919741.74270.041125

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.210141 & 3.9816 & 4.1e-05 \tabularnewline
2 & 0.325131 & 6.1603 & 0 \tabularnewline
3 & 0.153275 & 2.9041 & 0.001955 \tabularnewline
4 & 0.167252 & 3.169 & 0.000831 \tabularnewline
5 & 0.099156 & 1.8787 & 0.030545 \tabularnewline
6 & 0.064513 & 1.2223 & 0.111191 \tabularnewline
7 & -0.057203 & -1.0838 & 0.13958 \tabularnewline
8 & -0.023244 & -0.4404 & 0.329956 \tabularnewline
9 & -0.085115 & -1.6127 & 0.053845 \tabularnewline
10 & -0.168424 & -3.1912 & 0.000771 \tabularnewline
11 & -0.075939 & -1.4388 & 0.075533 \tabularnewline
12 & -0.475334 & -9.0063 & 0 \tabularnewline
13 & -0.179215 & -3.3956 & 0.000381 \tabularnewline
14 & -0.162819 & -3.085 & 0.001097 \tabularnewline
15 & -0.106644 & -2.0206 & 0.02203 \tabularnewline
16 & -0.147945 & -2.8032 & 0.002668 \tabularnewline
17 & -0.091478 & -1.7333 & 0.041954 \tabularnewline
18 & -0.089745 & -1.7004 & 0.044958 \tabularnewline
19 & 0.027328 & 0.5178 & 0.302458 \tabularnewline
20 & -0.012913 & -0.2447 & 0.403425 \tabularnewline
21 & 0.024199 & 0.4585 & 0.323437 \tabularnewline
22 & -0.018741 & -0.3551 & 0.361367 \tabularnewline
23 & 0.009567 & 0.1813 & 0.42813 \tabularnewline
24 & -0.022226 & -0.4211 & 0.336957 \tabularnewline
25 & 0.091974 & 1.7427 & 0.041125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156064&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]0.210141[/C][C]3.9816[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.325131[/C][C]6.1603[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.153275[/C][C]2.9041[/C][C]0.001955[/C][/ROW]
[ROW][C]4[/C][C]0.167252[/C][C]3.169[/C][C]0.000831[/C][/ROW]
[ROW][C]5[/C][C]0.099156[/C][C]1.8787[/C][C]0.030545[/C][/ROW]
[ROW][C]6[/C][C]0.064513[/C][C]1.2223[/C][C]0.111191[/C][/ROW]
[ROW][C]7[/C][C]-0.057203[/C][C]-1.0838[/C][C]0.13958[/C][/ROW]
[ROW][C]8[/C][C]-0.023244[/C][C]-0.4404[/C][C]0.329956[/C][/ROW]
[ROW][C]9[/C][C]-0.085115[/C][C]-1.6127[/C][C]0.053845[/C][/ROW]
[ROW][C]10[/C][C]-0.168424[/C][C]-3.1912[/C][C]0.000771[/C][/ROW]
[ROW][C]11[/C][C]-0.075939[/C][C]-1.4388[/C][C]0.075533[/C][/ROW]
[ROW][C]12[/C][C]-0.475334[/C][C]-9.0063[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.179215[/C][C]-3.3956[/C][C]0.000381[/C][/ROW]
[ROW][C]14[/C][C]-0.162819[/C][C]-3.085[/C][C]0.001097[/C][/ROW]
[ROW][C]15[/C][C]-0.106644[/C][C]-2.0206[/C][C]0.02203[/C][/ROW]
[ROW][C]16[/C][C]-0.147945[/C][C]-2.8032[/C][C]0.002668[/C][/ROW]
[ROW][C]17[/C][C]-0.091478[/C][C]-1.7333[/C][C]0.041954[/C][/ROW]
[ROW][C]18[/C][C]-0.089745[/C][C]-1.7004[/C][C]0.044958[/C][/ROW]
[ROW][C]19[/C][C]0.027328[/C][C]0.5178[/C][C]0.302458[/C][/ROW]
[ROW][C]20[/C][C]-0.012913[/C][C]-0.2447[/C][C]0.403425[/C][/ROW]
[ROW][C]21[/C][C]0.024199[/C][C]0.4585[/C][C]0.323437[/C][/ROW]
[ROW][C]22[/C][C]-0.018741[/C][C]-0.3551[/C][C]0.361367[/C][/ROW]
[ROW][C]23[/C][C]0.009567[/C][C]0.1813[/C][C]0.42813[/C][/ROW]
[ROW][C]24[/C][C]-0.022226[/C][C]-0.4211[/C][C]0.336957[/C][/ROW]
[ROW][C]25[/C][C]0.091974[/C][C]1.7427[/C][C]0.041125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156064&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156064&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2101413.98164.1e-05
20.3251316.16030
30.1532752.90410.001955
40.1672523.1690.000831
50.0991561.87870.030545
60.0645131.22230.111191
7-0.057203-1.08380.13958
8-0.023244-0.44040.329956
9-0.085115-1.61270.053845
10-0.168424-3.19120.000771
11-0.075939-1.43880.075533
12-0.475334-9.00630
13-0.179215-3.39560.000381
14-0.162819-3.0850.001097
15-0.106644-2.02060.02203
16-0.147945-2.80320.002668
17-0.091478-1.73330.041954
18-0.089745-1.70040.044958
190.0273280.51780.302458
20-0.012913-0.24470.403425
210.0241990.45850.323437
22-0.018741-0.35510.361367
230.0095670.18130.42813
24-0.022226-0.42110.336957
250.0919741.74270.041125







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2101413.98164.1e-05
20.2939525.56960
30.0495440.93870.174253
40.0495340.93850.174302
50.0127410.24140.404686
6-0.02095-0.39690.34582
7-0.124687-2.36250.009343
8-0.032709-0.61970.267912
9-0.045438-0.86090.194928
10-0.146092-2.7680.002966
110.0236310.44770.327306
12-0.42914-8.1310
13-0.0237-0.4490.326836
140.1508892.85890.002249
150.0297910.56450.286395
16-0.044612-0.84530.199257
17-0.012037-0.22810.40986
180.0046480.08810.464938
190.0113030.21420.415271
200.0098230.18610.426229
21-0.009818-0.1860.426268
22-0.15669-2.96890.001595
230.0121730.23060.408859
24-0.273087-5.17430
250.0532161.00830.156993

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.210141 & 3.9816 & 4.1e-05 \tabularnewline
2 & 0.293952 & 5.5696 & 0 \tabularnewline
3 & 0.049544 & 0.9387 & 0.174253 \tabularnewline
4 & 0.049534 & 0.9385 & 0.174302 \tabularnewline
5 & 0.012741 & 0.2414 & 0.404686 \tabularnewline
6 & -0.02095 & -0.3969 & 0.34582 \tabularnewline
7 & -0.124687 & -2.3625 & 0.009343 \tabularnewline
8 & -0.032709 & -0.6197 & 0.267912 \tabularnewline
9 & -0.045438 & -0.8609 & 0.194928 \tabularnewline
10 & -0.146092 & -2.768 & 0.002966 \tabularnewline
11 & 0.023631 & 0.4477 & 0.327306 \tabularnewline
12 & -0.42914 & -8.131 & 0 \tabularnewline
13 & -0.0237 & -0.449 & 0.326836 \tabularnewline
14 & 0.150889 & 2.8589 & 0.002249 \tabularnewline
15 & 0.029791 & 0.5645 & 0.286395 \tabularnewline
16 & -0.044612 & -0.8453 & 0.199257 \tabularnewline
17 & -0.012037 & -0.2281 & 0.40986 \tabularnewline
18 & 0.004648 & 0.0881 & 0.464938 \tabularnewline
19 & 0.011303 & 0.2142 & 0.415271 \tabularnewline
20 & 0.009823 & 0.1861 & 0.426229 \tabularnewline
21 & -0.009818 & -0.186 & 0.426268 \tabularnewline
22 & -0.15669 & -2.9689 & 0.001595 \tabularnewline
23 & 0.012173 & 0.2306 & 0.408859 \tabularnewline
24 & -0.273087 & -5.1743 & 0 \tabularnewline
25 & 0.053216 & 1.0083 & 0.156993 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156064&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]0.210141[/C][C]3.9816[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.293952[/C][C]5.5696[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.049544[/C][C]0.9387[/C][C]0.174253[/C][/ROW]
[ROW][C]4[/C][C]0.049534[/C][C]0.9385[/C][C]0.174302[/C][/ROW]
[ROW][C]5[/C][C]0.012741[/C][C]0.2414[/C][C]0.404686[/C][/ROW]
[ROW][C]6[/C][C]-0.02095[/C][C]-0.3969[/C][C]0.34582[/C][/ROW]
[ROW][C]7[/C][C]-0.124687[/C][C]-2.3625[/C][C]0.009343[/C][/ROW]
[ROW][C]8[/C][C]-0.032709[/C][C]-0.6197[/C][C]0.267912[/C][/ROW]
[ROW][C]9[/C][C]-0.045438[/C][C]-0.8609[/C][C]0.194928[/C][/ROW]
[ROW][C]10[/C][C]-0.146092[/C][C]-2.768[/C][C]0.002966[/C][/ROW]
[ROW][C]11[/C][C]0.023631[/C][C]0.4477[/C][C]0.327306[/C][/ROW]
[ROW][C]12[/C][C]-0.42914[/C][C]-8.131[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.0237[/C][C]-0.449[/C][C]0.326836[/C][/ROW]
[ROW][C]14[/C][C]0.150889[/C][C]2.8589[/C][C]0.002249[/C][/ROW]
[ROW][C]15[/C][C]0.029791[/C][C]0.5645[/C][C]0.286395[/C][/ROW]
[ROW][C]16[/C][C]-0.044612[/C][C]-0.8453[/C][C]0.199257[/C][/ROW]
[ROW][C]17[/C][C]-0.012037[/C][C]-0.2281[/C][C]0.40986[/C][/ROW]
[ROW][C]18[/C][C]0.004648[/C][C]0.0881[/C][C]0.464938[/C][/ROW]
[ROW][C]19[/C][C]0.011303[/C][C]0.2142[/C][C]0.415271[/C][/ROW]
[ROW][C]20[/C][C]0.009823[/C][C]0.1861[/C][C]0.426229[/C][/ROW]
[ROW][C]21[/C][C]-0.009818[/C][C]-0.186[/C][C]0.426268[/C][/ROW]
[ROW][C]22[/C][C]-0.15669[/C][C]-2.9689[/C][C]0.001595[/C][/ROW]
[ROW][C]23[/C][C]0.012173[/C][C]0.2306[/C][C]0.408859[/C][/ROW]
[ROW][C]24[/C][C]-0.273087[/C][C]-5.1743[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.053216[/C][C]1.0083[/C][C]0.156993[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156064&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156064&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2101413.98164.1e-05
20.2939525.56960
30.0495440.93870.174253
40.0495340.93850.174302
50.0127410.24140.404686
6-0.02095-0.39690.34582
7-0.124687-2.36250.009343
8-0.032709-0.61970.267912
9-0.045438-0.86090.194928
10-0.146092-2.7680.002966
110.0236310.44770.327306
12-0.42914-8.1310
13-0.0237-0.4490.326836
140.1508892.85890.002249
150.0297910.56450.286395
16-0.044612-0.84530.199257
17-0.012037-0.22810.40986
180.0046480.08810.464938
190.0113030.21420.415271
200.0098230.18610.426229
21-0.009818-0.1860.426268
22-0.15669-2.96890.001595
230.0121730.23060.408859
24-0.273087-5.17430
250.0532161.00830.156993



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')