Free Statistics

of Irreproducible Research!

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 computationTue, 24 Nov 2009 11:17:52 -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/Nov/24/t1259086765r3m7v3lgar9nyod.htm/, Retrieved Sun, 16 Jun 2024 21:40:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59202, Retrieved Sun, 16 Jun 2024 21:40:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
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 12:16:10] [b98453cac15ba1066b407e146608df68]
- R  D          [(Partial) Autocorrelation Function] [Autocorrelatie ; ...] [2009-11-24 18:17:52] [a931a0a30926b49d162330b43e89b999] [Current]
Feedback Forum

Post a new message
Dataseries X:
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
310631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224




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=59202&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=59202&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59202&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9013097.09690
20.7462615.87610
30.635135.0012e-06
40.5856184.61121e-05
50.5704444.49171.6e-05
60.5527154.35212.6e-05
70.506273.98649e-05
80.4552073.58430.000333
90.4512683.55330.000367
100.5016093.94970.000101
110.5811484.5761.2e-05
120.5771594.54461.3e-05
130.4475213.52380.000403
140.2794312.20020.015762
150.1625021.27950.102737
160.0983210.77420.220882
170.0620740.48880.313364
180.028830.2270.410583
19-0.023539-0.18530.426782
20-0.073793-0.58110.281656
21-0.085167-0.67060.252481
22-0.051063-0.40210.344509
23-0.006172-0.04860.480698
24-0.01739-0.13690.445765
25-0.123633-0.97350.167046
26-0.248766-1.95880.02732
27-0.322942-2.54290.006753
28-0.359163-2.82810.00315
29-0.371269-2.92340.002414
30-0.382665-3.01310.001871
31-0.401816-3.16390.001206
32-0.416133-3.27660.000862
33-0.394455-3.10590.00143
34-0.337757-2.65950.004973
35-0.274022-2.15760.017419
36-0.262278-2.06520.021547

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.901309 & 7.0969 & 0 \tabularnewline
2 & 0.746261 & 5.8761 & 0 \tabularnewline
3 & 0.63513 & 5.001 & 2e-06 \tabularnewline
4 & 0.585618 & 4.6112 & 1e-05 \tabularnewline
5 & 0.570444 & 4.4917 & 1.6e-05 \tabularnewline
6 & 0.552715 & 4.3521 & 2.6e-05 \tabularnewline
7 & 0.50627 & 3.9864 & 9e-05 \tabularnewline
8 & 0.455207 & 3.5843 & 0.000333 \tabularnewline
9 & 0.451268 & 3.5533 & 0.000367 \tabularnewline
10 & 0.501609 & 3.9497 & 0.000101 \tabularnewline
11 & 0.581148 & 4.576 & 1.2e-05 \tabularnewline
12 & 0.577159 & 4.5446 & 1.3e-05 \tabularnewline
13 & 0.447521 & 3.5238 & 0.000403 \tabularnewline
14 & 0.279431 & 2.2002 & 0.015762 \tabularnewline
15 & 0.162502 & 1.2795 & 0.102737 \tabularnewline
16 & 0.098321 & 0.7742 & 0.220882 \tabularnewline
17 & 0.062074 & 0.4888 & 0.313364 \tabularnewline
18 & 0.02883 & 0.227 & 0.410583 \tabularnewline
19 & -0.023539 & -0.1853 & 0.426782 \tabularnewline
20 & -0.073793 & -0.5811 & 0.281656 \tabularnewline
21 & -0.085167 & -0.6706 & 0.252481 \tabularnewline
22 & -0.051063 & -0.4021 & 0.344509 \tabularnewline
23 & -0.006172 & -0.0486 & 0.480698 \tabularnewline
24 & -0.01739 & -0.1369 & 0.445765 \tabularnewline
25 & -0.123633 & -0.9735 & 0.167046 \tabularnewline
26 & -0.248766 & -1.9588 & 0.02732 \tabularnewline
27 & -0.322942 & -2.5429 & 0.006753 \tabularnewline
28 & -0.359163 & -2.8281 & 0.00315 \tabularnewline
29 & -0.371269 & -2.9234 & 0.002414 \tabularnewline
30 & -0.382665 & -3.0131 & 0.001871 \tabularnewline
31 & -0.401816 & -3.1639 & 0.001206 \tabularnewline
32 & -0.416133 & -3.2766 & 0.000862 \tabularnewline
33 & -0.394455 & -3.1059 & 0.00143 \tabularnewline
34 & -0.337757 & -2.6595 & 0.004973 \tabularnewline
35 & -0.274022 & -2.1576 & 0.017419 \tabularnewline
36 & -0.262278 & -2.0652 & 0.021547 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59202&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]0.901309[/C][C]7.0969[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.746261[/C][C]5.8761[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.63513[/C][C]5.001[/C][C]2e-06[/C][/ROW]
[ROW][C]4[/C][C]0.585618[/C][C]4.6112[/C][C]1e-05[/C][/ROW]
[ROW][C]5[/C][C]0.570444[/C][C]4.4917[/C][C]1.6e-05[/C][/ROW]
[ROW][C]6[/C][C]0.552715[/C][C]4.3521[/C][C]2.6e-05[/C][/ROW]
[ROW][C]7[/C][C]0.50627[/C][C]3.9864[/C][C]9e-05[/C][/ROW]
[ROW][C]8[/C][C]0.455207[/C][C]3.5843[/C][C]0.000333[/C][/ROW]
[ROW][C]9[/C][C]0.451268[/C][C]3.5533[/C][C]0.000367[/C][/ROW]
[ROW][C]10[/C][C]0.501609[/C][C]3.9497[/C][C]0.000101[/C][/ROW]
[ROW][C]11[/C][C]0.581148[/C][C]4.576[/C][C]1.2e-05[/C][/ROW]
[ROW][C]12[/C][C]0.577159[/C][C]4.5446[/C][C]1.3e-05[/C][/ROW]
[ROW][C]13[/C][C]0.447521[/C][C]3.5238[/C][C]0.000403[/C][/ROW]
[ROW][C]14[/C][C]0.279431[/C][C]2.2002[/C][C]0.015762[/C][/ROW]
[ROW][C]15[/C][C]0.162502[/C][C]1.2795[/C][C]0.102737[/C][/ROW]
[ROW][C]16[/C][C]0.098321[/C][C]0.7742[/C][C]0.220882[/C][/ROW]
[ROW][C]17[/C][C]0.062074[/C][C]0.4888[/C][C]0.313364[/C][/ROW]
[ROW][C]18[/C][C]0.02883[/C][C]0.227[/C][C]0.410583[/C][/ROW]
[ROW][C]19[/C][C]-0.023539[/C][C]-0.1853[/C][C]0.426782[/C][/ROW]
[ROW][C]20[/C][C]-0.073793[/C][C]-0.5811[/C][C]0.281656[/C][/ROW]
[ROW][C]21[/C][C]-0.085167[/C][C]-0.6706[/C][C]0.252481[/C][/ROW]
[ROW][C]22[/C][C]-0.051063[/C][C]-0.4021[/C][C]0.344509[/C][/ROW]
[ROW][C]23[/C][C]-0.006172[/C][C]-0.0486[/C][C]0.480698[/C][/ROW]
[ROW][C]24[/C][C]-0.01739[/C][C]-0.1369[/C][C]0.445765[/C][/ROW]
[ROW][C]25[/C][C]-0.123633[/C][C]-0.9735[/C][C]0.167046[/C][/ROW]
[ROW][C]26[/C][C]-0.248766[/C][C]-1.9588[/C][C]0.02732[/C][/ROW]
[ROW][C]27[/C][C]-0.322942[/C][C]-2.5429[/C][C]0.006753[/C][/ROW]
[ROW][C]28[/C][C]-0.359163[/C][C]-2.8281[/C][C]0.00315[/C][/ROW]
[ROW][C]29[/C][C]-0.371269[/C][C]-2.9234[/C][C]0.002414[/C][/ROW]
[ROW][C]30[/C][C]-0.382665[/C][C]-3.0131[/C][C]0.001871[/C][/ROW]
[ROW][C]31[/C][C]-0.401816[/C][C]-3.1639[/C][C]0.001206[/C][/ROW]
[ROW][C]32[/C][C]-0.416133[/C][C]-3.2766[/C][C]0.000862[/C][/ROW]
[ROW][C]33[/C][C]-0.394455[/C][C]-3.1059[/C][C]0.00143[/C][/ROW]
[ROW][C]34[/C][C]-0.337757[/C][C]-2.6595[/C][C]0.004973[/C][/ROW]
[ROW][C]35[/C][C]-0.274022[/C][C]-2.1576[/C][C]0.017419[/C][/ROW]
[ROW][C]36[/C][C]-0.262278[/C][C]-2.0652[/C][C]0.021547[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59202&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59202&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
10.9013097.09690
20.7462615.87610
30.635135.0012e-06
40.5856184.61121e-05
50.5704444.49171.6e-05
60.5527154.35212.6e-05
70.506273.98649e-05
80.4552073.58430.000333
90.4512683.55330.000367
100.5016093.94970.000101
110.5811484.5761.2e-05
120.5771594.54461.3e-05
130.4475213.52380.000403
140.2794312.20020.015762
150.1625021.27950.102737
160.0983210.77420.220882
170.0620740.48880.313364
180.028830.2270.410583
19-0.023539-0.18530.426782
20-0.073793-0.58110.281656
21-0.085167-0.67060.252481
22-0.051063-0.40210.344509
23-0.006172-0.04860.480698
24-0.01739-0.13690.445765
25-0.123633-0.97350.167046
26-0.248766-1.95880.02732
27-0.322942-2.54290.006753
28-0.359163-2.82810.00315
29-0.371269-2.92340.002414
30-0.382665-3.01310.001871
31-0.401816-3.16390.001206
32-0.416133-3.27660.000862
33-0.394455-3.10590.00143
34-0.337757-2.65950.004973
35-0.274022-2.15760.017419
36-0.262278-2.06520.021547







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9013097.09690
2-0.352252-2.77360.003657
30.2620932.06370.021618
40.1170460.92160.180149
50.0709330.55850.289249
6-0.002383-0.01880.492544
7-0.076804-0.60480.273776
80.0796250.6270.266492
90.2251131.77250.040609
100.165851.30590.098205
110.2013781.58560.058953
12-0.424408-3.34180.000707
13-0.422962-3.33040.000732
14-0.145046-1.14210.128904
15-0.023954-0.18860.425506
16-0.118409-0.93240.177384
17-0.044852-0.35320.362581
180.0482080.37960.352773
190.039820.31350.377459
20-0.047444-0.37360.354997
21-0.058822-0.46320.322433
22-0.110192-0.86770.194466
230.060590.47710.31749
240.1315421.03580.152167
25-0.107554-0.84690.200159
260.0335420.26410.396287
270.0595870.46920.320291
28-0.096097-0.75670.226057
290.0093130.07330.47089
30-0.117163-0.92250.179911
310.0626090.4930.311884
320.0312860.24630.403113
330.0315560.24850.402297
340.0303440.23890.405973
350.0098430.07750.469235
36-0.014425-0.11360.454968

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.901309 & 7.0969 & 0 \tabularnewline
2 & -0.352252 & -2.7736 & 0.003657 \tabularnewline
3 & 0.262093 & 2.0637 & 0.021618 \tabularnewline
4 & 0.117046 & 0.9216 & 0.180149 \tabularnewline
5 & 0.070933 & 0.5585 & 0.289249 \tabularnewline
6 & -0.002383 & -0.0188 & 0.492544 \tabularnewline
7 & -0.076804 & -0.6048 & 0.273776 \tabularnewline
8 & 0.079625 & 0.627 & 0.266492 \tabularnewline
9 & 0.225113 & 1.7725 & 0.040609 \tabularnewline
10 & 0.16585 & 1.3059 & 0.098205 \tabularnewline
11 & 0.201378 & 1.5856 & 0.058953 \tabularnewline
12 & -0.424408 & -3.3418 & 0.000707 \tabularnewline
13 & -0.422962 & -3.3304 & 0.000732 \tabularnewline
14 & -0.145046 & -1.1421 & 0.128904 \tabularnewline
15 & -0.023954 & -0.1886 & 0.425506 \tabularnewline
16 & -0.118409 & -0.9324 & 0.177384 \tabularnewline
17 & -0.044852 & -0.3532 & 0.362581 \tabularnewline
18 & 0.048208 & 0.3796 & 0.352773 \tabularnewline
19 & 0.03982 & 0.3135 & 0.377459 \tabularnewline
20 & -0.047444 & -0.3736 & 0.354997 \tabularnewline
21 & -0.058822 & -0.4632 & 0.322433 \tabularnewline
22 & -0.110192 & -0.8677 & 0.194466 \tabularnewline
23 & 0.06059 & 0.4771 & 0.31749 \tabularnewline
24 & 0.131542 & 1.0358 & 0.152167 \tabularnewline
25 & -0.107554 & -0.8469 & 0.200159 \tabularnewline
26 & 0.033542 & 0.2641 & 0.396287 \tabularnewline
27 & 0.059587 & 0.4692 & 0.320291 \tabularnewline
28 & -0.096097 & -0.7567 & 0.226057 \tabularnewline
29 & 0.009313 & 0.0733 & 0.47089 \tabularnewline
30 & -0.117163 & -0.9225 & 0.179911 \tabularnewline
31 & 0.062609 & 0.493 & 0.311884 \tabularnewline
32 & 0.031286 & 0.2463 & 0.403113 \tabularnewline
33 & 0.031556 & 0.2485 & 0.402297 \tabularnewline
34 & 0.030344 & 0.2389 & 0.405973 \tabularnewline
35 & 0.009843 & 0.0775 & 0.469235 \tabularnewline
36 & -0.014425 & -0.1136 & 0.454968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59202&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]0.901309[/C][C]7.0969[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.352252[/C][C]-2.7736[/C][C]0.003657[/C][/ROW]
[ROW][C]3[/C][C]0.262093[/C][C]2.0637[/C][C]0.021618[/C][/ROW]
[ROW][C]4[/C][C]0.117046[/C][C]0.9216[/C][C]0.180149[/C][/ROW]
[ROW][C]5[/C][C]0.070933[/C][C]0.5585[/C][C]0.289249[/C][/ROW]
[ROW][C]6[/C][C]-0.002383[/C][C]-0.0188[/C][C]0.492544[/C][/ROW]
[ROW][C]7[/C][C]-0.076804[/C][C]-0.6048[/C][C]0.273776[/C][/ROW]
[ROW][C]8[/C][C]0.079625[/C][C]0.627[/C][C]0.266492[/C][/ROW]
[ROW][C]9[/C][C]0.225113[/C][C]1.7725[/C][C]0.040609[/C][/ROW]
[ROW][C]10[/C][C]0.16585[/C][C]1.3059[/C][C]0.098205[/C][/ROW]
[ROW][C]11[/C][C]0.201378[/C][C]1.5856[/C][C]0.058953[/C][/ROW]
[ROW][C]12[/C][C]-0.424408[/C][C]-3.3418[/C][C]0.000707[/C][/ROW]
[ROW][C]13[/C][C]-0.422962[/C][C]-3.3304[/C][C]0.000732[/C][/ROW]
[ROW][C]14[/C][C]-0.145046[/C][C]-1.1421[/C][C]0.128904[/C][/ROW]
[ROW][C]15[/C][C]-0.023954[/C][C]-0.1886[/C][C]0.425506[/C][/ROW]
[ROW][C]16[/C][C]-0.118409[/C][C]-0.9324[/C][C]0.177384[/C][/ROW]
[ROW][C]17[/C][C]-0.044852[/C][C]-0.3532[/C][C]0.362581[/C][/ROW]
[ROW][C]18[/C][C]0.048208[/C][C]0.3796[/C][C]0.352773[/C][/ROW]
[ROW][C]19[/C][C]0.03982[/C][C]0.3135[/C][C]0.377459[/C][/ROW]
[ROW][C]20[/C][C]-0.047444[/C][C]-0.3736[/C][C]0.354997[/C][/ROW]
[ROW][C]21[/C][C]-0.058822[/C][C]-0.4632[/C][C]0.322433[/C][/ROW]
[ROW][C]22[/C][C]-0.110192[/C][C]-0.8677[/C][C]0.194466[/C][/ROW]
[ROW][C]23[/C][C]0.06059[/C][C]0.4771[/C][C]0.31749[/C][/ROW]
[ROW][C]24[/C][C]0.131542[/C][C]1.0358[/C][C]0.152167[/C][/ROW]
[ROW][C]25[/C][C]-0.107554[/C][C]-0.8469[/C][C]0.200159[/C][/ROW]
[ROW][C]26[/C][C]0.033542[/C][C]0.2641[/C][C]0.396287[/C][/ROW]
[ROW][C]27[/C][C]0.059587[/C][C]0.4692[/C][C]0.320291[/C][/ROW]
[ROW][C]28[/C][C]-0.096097[/C][C]-0.7567[/C][C]0.226057[/C][/ROW]
[ROW][C]29[/C][C]0.009313[/C][C]0.0733[/C][C]0.47089[/C][/ROW]
[ROW][C]30[/C][C]-0.117163[/C][C]-0.9225[/C][C]0.179911[/C][/ROW]
[ROW][C]31[/C][C]0.062609[/C][C]0.493[/C][C]0.311884[/C][/ROW]
[ROW][C]32[/C][C]0.031286[/C][C]0.2463[/C][C]0.403113[/C][/ROW]
[ROW][C]33[/C][C]0.031556[/C][C]0.2485[/C][C]0.402297[/C][/ROW]
[ROW][C]34[/C][C]0.030344[/C][C]0.2389[/C][C]0.405973[/C][/ROW]
[ROW][C]35[/C][C]0.009843[/C][C]0.0775[/C][C]0.469235[/C][/ROW]
[ROW][C]36[/C][C]-0.014425[/C][C]-0.1136[/C][C]0.454968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59202&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59202&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
10.9013097.09690
2-0.352252-2.77360.003657
30.2620932.06370.021618
40.1170460.92160.180149
50.0709330.55850.289249
6-0.002383-0.01880.492544
7-0.076804-0.60480.273776
80.0796250.6270.266492
90.2251131.77250.040609
100.165851.30590.098205
110.2013781.58560.058953
12-0.424408-3.34180.000707
13-0.422962-3.33040.000732
14-0.145046-1.14210.128904
15-0.023954-0.18860.425506
16-0.118409-0.93240.177384
17-0.044852-0.35320.362581
180.0482080.37960.352773
190.039820.31350.377459
20-0.047444-0.37360.354997
21-0.058822-0.46320.322433
22-0.110192-0.86770.194466
230.060590.47710.31749
240.1315421.03580.152167
25-0.107554-0.84690.200159
260.0335420.26410.396287
270.0595870.46920.320291
28-0.096097-0.75670.226057
290.0093130.07330.47089
30-0.117163-0.92250.179911
310.0626090.4930.311884
320.0312860.24630.403113
330.0315560.24850.402297
340.0303440.23890.405973
350.0098430.07750.469235
36-0.014425-0.11360.454968



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')