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 computationFri, 27 Nov 2009 08:55:14 -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/27/t1259337377gbbwk08vlqxg9v5.htm/, Retrieved Mon, 29 Apr 2024 00:18:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60919, Retrieved Mon, 29 Apr 2024 00:18:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
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]
-   P           [(Partial) Autocorrelation Function] [] [2009-11-27 15:55:14] [9f6463b67b1eb7bae5c03a796abf0348] [Current]
Feedback Forum

Post a new message
Dataseries X:
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556




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=60919&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=60919&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60919&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
1-0.63921-4.99243e-06
20.1429241.11630.134342
30.06190.48350.315253
4-0.185494-1.44880.076263
50.209231.63410.05369
6-0.046209-0.36090.359709
7-0.026914-0.21020.417103
8-0.146737-1.1460.128125
90.3101652.42250.009201
10-0.253737-1.98170.026009
110.1345011.05050.14882
12-0.020133-0.15720.437787
13-0.237947-1.85840.033968
140.4344513.39320.000609
15-0.30399-2.37420.010374
160.0749810.58560.280146
17-0.022457-0.17540.430675
180.0294160.22970.40953
190.0102350.07990.468274
200.0049010.03830.484796
210.002650.02070.491778
22-0.1768-1.38090.086181
230.3145592.45680.00844
24-0.230763-1.80230.038218
250.1102820.86130.196214
26-0.06655-0.51980.302553
27-0.029112-0.22740.410446
280.1512341.18120.121059
29-0.154464-1.20640.11616
300.1308831.02220.155355
31-0.178676-1.39550.083962
320.1312091.02480.154758
330.0126970.09920.460666
34-0.056287-0.43960.330884
350.0604120.47180.319365
36-0.14723-1.14990.127337

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.63921 & -4.9924 & 3e-06 \tabularnewline
2 & 0.142924 & 1.1163 & 0.134342 \tabularnewline
3 & 0.0619 & 0.4835 & 0.315253 \tabularnewline
4 & -0.185494 & -1.4488 & 0.076263 \tabularnewline
5 & 0.20923 & 1.6341 & 0.05369 \tabularnewline
6 & -0.046209 & -0.3609 & 0.359709 \tabularnewline
7 & -0.026914 & -0.2102 & 0.417103 \tabularnewline
8 & -0.146737 & -1.146 & 0.128125 \tabularnewline
9 & 0.310165 & 2.4225 & 0.009201 \tabularnewline
10 & -0.253737 & -1.9817 & 0.026009 \tabularnewline
11 & 0.134501 & 1.0505 & 0.14882 \tabularnewline
12 & -0.020133 & -0.1572 & 0.437787 \tabularnewline
13 & -0.237947 & -1.8584 & 0.033968 \tabularnewline
14 & 0.434451 & 3.3932 & 0.000609 \tabularnewline
15 & -0.30399 & -2.3742 & 0.010374 \tabularnewline
16 & 0.074981 & 0.5856 & 0.280146 \tabularnewline
17 & -0.022457 & -0.1754 & 0.430675 \tabularnewline
18 & 0.029416 & 0.2297 & 0.40953 \tabularnewline
19 & 0.010235 & 0.0799 & 0.468274 \tabularnewline
20 & 0.004901 & 0.0383 & 0.484796 \tabularnewline
21 & 0.00265 & 0.0207 & 0.491778 \tabularnewline
22 & -0.1768 & -1.3809 & 0.086181 \tabularnewline
23 & 0.314559 & 2.4568 & 0.00844 \tabularnewline
24 & -0.230763 & -1.8023 & 0.038218 \tabularnewline
25 & 0.110282 & 0.8613 & 0.196214 \tabularnewline
26 & -0.06655 & -0.5198 & 0.302553 \tabularnewline
27 & -0.029112 & -0.2274 & 0.410446 \tabularnewline
28 & 0.151234 & 1.1812 & 0.121059 \tabularnewline
29 & -0.154464 & -1.2064 & 0.11616 \tabularnewline
30 & 0.130883 & 1.0222 & 0.155355 \tabularnewline
31 & -0.178676 & -1.3955 & 0.083962 \tabularnewline
32 & 0.131209 & 1.0248 & 0.154758 \tabularnewline
33 & 0.012697 & 0.0992 & 0.460666 \tabularnewline
34 & -0.056287 & -0.4396 & 0.330884 \tabularnewline
35 & 0.060412 & 0.4718 & 0.319365 \tabularnewline
36 & -0.14723 & -1.1499 & 0.127337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60919&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]-0.63921[/C][C]-4.9924[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.142924[/C][C]1.1163[/C][C]0.134342[/C][/ROW]
[ROW][C]3[/C][C]0.0619[/C][C]0.4835[/C][C]0.315253[/C][/ROW]
[ROW][C]4[/C][C]-0.185494[/C][C]-1.4488[/C][C]0.076263[/C][/ROW]
[ROW][C]5[/C][C]0.20923[/C][C]1.6341[/C][C]0.05369[/C][/ROW]
[ROW][C]6[/C][C]-0.046209[/C][C]-0.3609[/C][C]0.359709[/C][/ROW]
[ROW][C]7[/C][C]-0.026914[/C][C]-0.2102[/C][C]0.417103[/C][/ROW]
[ROW][C]8[/C][C]-0.146737[/C][C]-1.146[/C][C]0.128125[/C][/ROW]
[ROW][C]9[/C][C]0.310165[/C][C]2.4225[/C][C]0.009201[/C][/ROW]
[ROW][C]10[/C][C]-0.253737[/C][C]-1.9817[/C][C]0.026009[/C][/ROW]
[ROW][C]11[/C][C]0.134501[/C][C]1.0505[/C][C]0.14882[/C][/ROW]
[ROW][C]12[/C][C]-0.020133[/C][C]-0.1572[/C][C]0.437787[/C][/ROW]
[ROW][C]13[/C][C]-0.237947[/C][C]-1.8584[/C][C]0.033968[/C][/ROW]
[ROW][C]14[/C][C]0.434451[/C][C]3.3932[/C][C]0.000609[/C][/ROW]
[ROW][C]15[/C][C]-0.30399[/C][C]-2.3742[/C][C]0.010374[/C][/ROW]
[ROW][C]16[/C][C]0.074981[/C][C]0.5856[/C][C]0.280146[/C][/ROW]
[ROW][C]17[/C][C]-0.022457[/C][C]-0.1754[/C][C]0.430675[/C][/ROW]
[ROW][C]18[/C][C]0.029416[/C][C]0.2297[/C][C]0.40953[/C][/ROW]
[ROW][C]19[/C][C]0.010235[/C][C]0.0799[/C][C]0.468274[/C][/ROW]
[ROW][C]20[/C][C]0.004901[/C][C]0.0383[/C][C]0.484796[/C][/ROW]
[ROW][C]21[/C][C]0.00265[/C][C]0.0207[/C][C]0.491778[/C][/ROW]
[ROW][C]22[/C][C]-0.1768[/C][C]-1.3809[/C][C]0.086181[/C][/ROW]
[ROW][C]23[/C][C]0.314559[/C][C]2.4568[/C][C]0.00844[/C][/ROW]
[ROW][C]24[/C][C]-0.230763[/C][C]-1.8023[/C][C]0.038218[/C][/ROW]
[ROW][C]25[/C][C]0.110282[/C][C]0.8613[/C][C]0.196214[/C][/ROW]
[ROW][C]26[/C][C]-0.06655[/C][C]-0.5198[/C][C]0.302553[/C][/ROW]
[ROW][C]27[/C][C]-0.029112[/C][C]-0.2274[/C][C]0.410446[/C][/ROW]
[ROW][C]28[/C][C]0.151234[/C][C]1.1812[/C][C]0.121059[/C][/ROW]
[ROW][C]29[/C][C]-0.154464[/C][C]-1.2064[/C][C]0.11616[/C][/ROW]
[ROW][C]30[/C][C]0.130883[/C][C]1.0222[/C][C]0.155355[/C][/ROW]
[ROW][C]31[/C][C]-0.178676[/C][C]-1.3955[/C][C]0.083962[/C][/ROW]
[ROW][C]32[/C][C]0.131209[/C][C]1.0248[/C][C]0.154758[/C][/ROW]
[ROW][C]33[/C][C]0.012697[/C][C]0.0992[/C][C]0.460666[/C][/ROW]
[ROW][C]34[/C][C]-0.056287[/C][C]-0.4396[/C][C]0.330884[/C][/ROW]
[ROW][C]35[/C][C]0.060412[/C][C]0.4718[/C][C]0.319365[/C][/ROW]
[ROW][C]36[/C][C]-0.14723[/C][C]-1.1499[/C][C]0.127337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60919&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60919&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
1-0.63921-4.99243e-06
20.1429241.11630.134342
30.06190.48350.315253
4-0.185494-1.44880.076263
50.209231.63410.05369
6-0.046209-0.36090.359709
7-0.026914-0.21020.417103
8-0.146737-1.1460.128125
90.3101652.42250.009201
10-0.253737-1.98170.026009
110.1345011.05050.14882
12-0.020133-0.15720.437787
13-0.237947-1.85840.033968
140.4344513.39320.000609
15-0.30399-2.37420.010374
160.0749810.58560.280146
17-0.022457-0.17540.430675
180.0294160.22970.40953
190.0102350.07990.468274
200.0049010.03830.484796
210.002650.02070.491778
22-0.1768-1.38090.086181
230.3145592.45680.00844
24-0.230763-1.80230.038218
250.1102820.86130.196214
26-0.06655-0.51980.302553
27-0.029112-0.22740.410446
280.1512341.18120.121059
29-0.154464-1.20640.11616
300.1308831.02220.155355
31-0.178676-1.39550.083962
320.1312091.02480.154758
330.0126970.09920.460666
34-0.056287-0.43960.330884
350.0604120.47180.319365
36-0.14723-1.14990.127337







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.63921-4.99243e-06
2-0.449208-3.50840.000426
3-0.196668-1.5360.064852
4-0.348507-2.72190.004224
5-0.208478-1.62830.054311
60.0269980.21090.416849
70.1679681.31190.097239
8-0.254153-1.9850.025823
90.0915410.7150.238682
100.1024740.80030.213308
110.0871980.6810.249214
120.0584230.45630.324897
13-0.288259-2.25140.013987
140.0499880.39040.348795
150.0633570.49480.311246
16-0.048809-0.38120.352187
17-0.139998-1.09340.139254
180.0462340.36110.359637
190.0951190.74290.230195
20-0.033518-0.26180.397184
210.0465670.36370.35867
22-0.037763-0.29490.38452
23-0.000653-0.00510.497974
24-0.018937-0.14790.441453
250.0242660.18950.425155
26-0.051122-0.39930.345542
270.0119760.09350.462894
280.0464320.36260.359062
29-0.068765-0.53710.296586
300.0927040.7240.235905
310.0501940.3920.348201
32-0.165214-1.29040.100898
33-0.025481-0.1990.421457
340.0263580.20590.418792
350.0668570.52220.301721
36-0.04731-0.36950.356516

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.63921 & -4.9924 & 3e-06 \tabularnewline
2 & -0.449208 & -3.5084 & 0.000426 \tabularnewline
3 & -0.196668 & -1.536 & 0.064852 \tabularnewline
4 & -0.348507 & -2.7219 & 0.004224 \tabularnewline
5 & -0.208478 & -1.6283 & 0.054311 \tabularnewline
6 & 0.026998 & 0.2109 & 0.416849 \tabularnewline
7 & 0.167968 & 1.3119 & 0.097239 \tabularnewline
8 & -0.254153 & -1.985 & 0.025823 \tabularnewline
9 & 0.091541 & 0.715 & 0.238682 \tabularnewline
10 & 0.102474 & 0.8003 & 0.213308 \tabularnewline
11 & 0.087198 & 0.681 & 0.249214 \tabularnewline
12 & 0.058423 & 0.4563 & 0.324897 \tabularnewline
13 & -0.288259 & -2.2514 & 0.013987 \tabularnewline
14 & 0.049988 & 0.3904 & 0.348795 \tabularnewline
15 & 0.063357 & 0.4948 & 0.311246 \tabularnewline
16 & -0.048809 & -0.3812 & 0.352187 \tabularnewline
17 & -0.139998 & -1.0934 & 0.139254 \tabularnewline
18 & 0.046234 & 0.3611 & 0.359637 \tabularnewline
19 & 0.095119 & 0.7429 & 0.230195 \tabularnewline
20 & -0.033518 & -0.2618 & 0.397184 \tabularnewline
21 & 0.046567 & 0.3637 & 0.35867 \tabularnewline
22 & -0.037763 & -0.2949 & 0.38452 \tabularnewline
23 & -0.000653 & -0.0051 & 0.497974 \tabularnewline
24 & -0.018937 & -0.1479 & 0.441453 \tabularnewline
25 & 0.024266 & 0.1895 & 0.425155 \tabularnewline
26 & -0.051122 & -0.3993 & 0.345542 \tabularnewline
27 & 0.011976 & 0.0935 & 0.462894 \tabularnewline
28 & 0.046432 & 0.3626 & 0.359062 \tabularnewline
29 & -0.068765 & -0.5371 & 0.296586 \tabularnewline
30 & 0.092704 & 0.724 & 0.235905 \tabularnewline
31 & 0.050194 & 0.392 & 0.348201 \tabularnewline
32 & -0.165214 & -1.2904 & 0.100898 \tabularnewline
33 & -0.025481 & -0.199 & 0.421457 \tabularnewline
34 & 0.026358 & 0.2059 & 0.418792 \tabularnewline
35 & 0.066857 & 0.5222 & 0.301721 \tabularnewline
36 & -0.04731 & -0.3695 & 0.356516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60919&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]-0.63921[/C][C]-4.9924[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.449208[/C][C]-3.5084[/C][C]0.000426[/C][/ROW]
[ROW][C]3[/C][C]-0.196668[/C][C]-1.536[/C][C]0.064852[/C][/ROW]
[ROW][C]4[/C][C]-0.348507[/C][C]-2.7219[/C][C]0.004224[/C][/ROW]
[ROW][C]5[/C][C]-0.208478[/C][C]-1.6283[/C][C]0.054311[/C][/ROW]
[ROW][C]6[/C][C]0.026998[/C][C]0.2109[/C][C]0.416849[/C][/ROW]
[ROW][C]7[/C][C]0.167968[/C][C]1.3119[/C][C]0.097239[/C][/ROW]
[ROW][C]8[/C][C]-0.254153[/C][C]-1.985[/C][C]0.025823[/C][/ROW]
[ROW][C]9[/C][C]0.091541[/C][C]0.715[/C][C]0.238682[/C][/ROW]
[ROW][C]10[/C][C]0.102474[/C][C]0.8003[/C][C]0.213308[/C][/ROW]
[ROW][C]11[/C][C]0.087198[/C][C]0.681[/C][C]0.249214[/C][/ROW]
[ROW][C]12[/C][C]0.058423[/C][C]0.4563[/C][C]0.324897[/C][/ROW]
[ROW][C]13[/C][C]-0.288259[/C][C]-2.2514[/C][C]0.013987[/C][/ROW]
[ROW][C]14[/C][C]0.049988[/C][C]0.3904[/C][C]0.348795[/C][/ROW]
[ROW][C]15[/C][C]0.063357[/C][C]0.4948[/C][C]0.311246[/C][/ROW]
[ROW][C]16[/C][C]-0.048809[/C][C]-0.3812[/C][C]0.352187[/C][/ROW]
[ROW][C]17[/C][C]-0.139998[/C][C]-1.0934[/C][C]0.139254[/C][/ROW]
[ROW][C]18[/C][C]0.046234[/C][C]0.3611[/C][C]0.359637[/C][/ROW]
[ROW][C]19[/C][C]0.095119[/C][C]0.7429[/C][C]0.230195[/C][/ROW]
[ROW][C]20[/C][C]-0.033518[/C][C]-0.2618[/C][C]0.397184[/C][/ROW]
[ROW][C]21[/C][C]0.046567[/C][C]0.3637[/C][C]0.35867[/C][/ROW]
[ROW][C]22[/C][C]-0.037763[/C][C]-0.2949[/C][C]0.38452[/C][/ROW]
[ROW][C]23[/C][C]-0.000653[/C][C]-0.0051[/C][C]0.497974[/C][/ROW]
[ROW][C]24[/C][C]-0.018937[/C][C]-0.1479[/C][C]0.441453[/C][/ROW]
[ROW][C]25[/C][C]0.024266[/C][C]0.1895[/C][C]0.425155[/C][/ROW]
[ROW][C]26[/C][C]-0.051122[/C][C]-0.3993[/C][C]0.345542[/C][/ROW]
[ROW][C]27[/C][C]0.011976[/C][C]0.0935[/C][C]0.462894[/C][/ROW]
[ROW][C]28[/C][C]0.046432[/C][C]0.3626[/C][C]0.359062[/C][/ROW]
[ROW][C]29[/C][C]-0.068765[/C][C]-0.5371[/C][C]0.296586[/C][/ROW]
[ROW][C]30[/C][C]0.092704[/C][C]0.724[/C][C]0.235905[/C][/ROW]
[ROW][C]31[/C][C]0.050194[/C][C]0.392[/C][C]0.348201[/C][/ROW]
[ROW][C]32[/C][C]-0.165214[/C][C]-1.2904[/C][C]0.100898[/C][/ROW]
[ROW][C]33[/C][C]-0.025481[/C][C]-0.199[/C][C]0.421457[/C][/ROW]
[ROW][C]34[/C][C]0.026358[/C][C]0.2059[/C][C]0.418792[/C][/ROW]
[ROW][C]35[/C][C]0.066857[/C][C]0.5222[/C][C]0.301721[/C][/ROW]
[ROW][C]36[/C][C]-0.04731[/C][C]-0.3695[/C][C]0.356516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60919&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60919&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
1-0.63921-4.99243e-06
2-0.449208-3.50840.000426
3-0.196668-1.5360.064852
4-0.348507-2.72190.004224
5-0.208478-1.62830.054311
60.0269980.21090.416849
70.1679681.31190.097239
8-0.254153-1.9850.025823
90.0915410.7150.238682
100.1024740.80030.213308
110.0871980.6810.249214
120.0584230.45630.324897
13-0.288259-2.25140.013987
140.0499880.39040.348795
150.0633570.49480.311246
16-0.048809-0.38120.352187
17-0.139998-1.09340.139254
180.0462340.36110.359637
190.0951190.74290.230195
20-0.033518-0.26180.397184
210.0465670.36370.35867
22-0.037763-0.29490.38452
23-0.000653-0.00510.497974
24-0.018937-0.14790.441453
250.0242660.18950.425155
26-0.051122-0.39930.345542
270.0119760.09350.462894
280.0464320.36260.359062
29-0.068765-0.53710.296586
300.0927040.7240.235905
310.0501940.3920.348201
32-0.165214-1.29040.100898
33-0.025481-0.1990.421457
340.0263580.20590.418792
350.0668570.52220.301721
36-0.04731-0.36950.356516



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; 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')