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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 computationThu, 03 Dec 2009 08:04:47 -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/Dec/03/t1259852767s7t0wisidsvun3v.htm/, Retrieved Thu, 28 Mar 2024 20:08:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62821, Retrieved Thu, 28 Mar 2024 20:08:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
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 PD        [(Partial) Autocorrelation Function] [] [2009-12-02 16:17:17] [74be16979710d4c4e7c6647856088456]
-   P             [(Partial) Autocorrelation Function] [d=2] [2009-12-03 15:04:47] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataseries X:
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710




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=62821&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=62821&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62821&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
1-0.615461-4.48062e-05
20.1172360.85350.198615
30.0457720.33320.37014
40.0513630.37390.354974
5-0.157697-1.1480.128052
60.1247660.90830.183913
7-0.100471-0.73140.233866
80.0679890.4950.311335
90.0653820.4760.318021
10-0.342444-2.4930.007912
110.520023.78580.000196
12-0.375653-2.73480.004235
130.0749340.54550.29384
140.0146960.1070.4576
150.093150.67810.250315
16-0.165414-1.20420.116926
170.2051751.49370.070593
18-0.187455-1.36470.089058
190.1258170.9160.181918
20-0.028897-0.21040.417093
21-0.097995-0.71340.239359
220.1384371.00780.159056
23-0.088463-0.6440.261169
240.005130.03730.485174
25-0.022819-0.16610.434347
260.0986950.71850.237799
27-0.096028-0.69910.243775
280.0257440.18740.426022
29-0.037209-0.27090.393767
300.0391890.28530.388262
310.0060090.04370.482637
32-0.052094-0.37930.353008
330.0827860.60270.274643
34-0.07008-0.51020.306017
350.0661690.48170.315995
36-0.049055-0.35710.361207

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.615461 & -4.4806 & 2e-05 \tabularnewline
2 & 0.117236 & 0.8535 & 0.198615 \tabularnewline
3 & 0.045772 & 0.3332 & 0.37014 \tabularnewline
4 & 0.051363 & 0.3739 & 0.354974 \tabularnewline
5 & -0.157697 & -1.148 & 0.128052 \tabularnewline
6 & 0.124766 & 0.9083 & 0.183913 \tabularnewline
7 & -0.100471 & -0.7314 & 0.233866 \tabularnewline
8 & 0.067989 & 0.495 & 0.311335 \tabularnewline
9 & 0.065382 & 0.476 & 0.318021 \tabularnewline
10 & -0.342444 & -2.493 & 0.007912 \tabularnewline
11 & 0.52002 & 3.7858 & 0.000196 \tabularnewline
12 & -0.375653 & -2.7348 & 0.004235 \tabularnewline
13 & 0.074934 & 0.5455 & 0.29384 \tabularnewline
14 & 0.014696 & 0.107 & 0.4576 \tabularnewline
15 & 0.09315 & 0.6781 & 0.250315 \tabularnewline
16 & -0.165414 & -1.2042 & 0.116926 \tabularnewline
17 & 0.205175 & 1.4937 & 0.070593 \tabularnewline
18 & -0.187455 & -1.3647 & 0.089058 \tabularnewline
19 & 0.125817 & 0.916 & 0.181918 \tabularnewline
20 & -0.028897 & -0.2104 & 0.417093 \tabularnewline
21 & -0.097995 & -0.7134 & 0.239359 \tabularnewline
22 & 0.138437 & 1.0078 & 0.159056 \tabularnewline
23 & -0.088463 & -0.644 & 0.261169 \tabularnewline
24 & 0.00513 & 0.0373 & 0.485174 \tabularnewline
25 & -0.022819 & -0.1661 & 0.434347 \tabularnewline
26 & 0.098695 & 0.7185 & 0.237799 \tabularnewline
27 & -0.096028 & -0.6991 & 0.243775 \tabularnewline
28 & 0.025744 & 0.1874 & 0.426022 \tabularnewline
29 & -0.037209 & -0.2709 & 0.393767 \tabularnewline
30 & 0.039189 & 0.2853 & 0.388262 \tabularnewline
31 & 0.006009 & 0.0437 & 0.482637 \tabularnewline
32 & -0.052094 & -0.3793 & 0.353008 \tabularnewline
33 & 0.082786 & 0.6027 & 0.274643 \tabularnewline
34 & -0.07008 & -0.5102 & 0.306017 \tabularnewline
35 & 0.066169 & 0.4817 & 0.315995 \tabularnewline
36 & -0.049055 & -0.3571 & 0.361207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62821&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]-0.615461[/C][C]-4.4806[/C][C]2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.117236[/C][C]0.8535[/C][C]0.198615[/C][/ROW]
[ROW][C]3[/C][C]0.045772[/C][C]0.3332[/C][C]0.37014[/C][/ROW]
[ROW][C]4[/C][C]0.051363[/C][C]0.3739[/C][C]0.354974[/C][/ROW]
[ROW][C]5[/C][C]-0.157697[/C][C]-1.148[/C][C]0.128052[/C][/ROW]
[ROW][C]6[/C][C]0.124766[/C][C]0.9083[/C][C]0.183913[/C][/ROW]
[ROW][C]7[/C][C]-0.100471[/C][C]-0.7314[/C][C]0.233866[/C][/ROW]
[ROW][C]8[/C][C]0.067989[/C][C]0.495[/C][C]0.311335[/C][/ROW]
[ROW][C]9[/C][C]0.065382[/C][C]0.476[/C][C]0.318021[/C][/ROW]
[ROW][C]10[/C][C]-0.342444[/C][C]-2.493[/C][C]0.007912[/C][/ROW]
[ROW][C]11[/C][C]0.52002[/C][C]3.7858[/C][C]0.000196[/C][/ROW]
[ROW][C]12[/C][C]-0.375653[/C][C]-2.7348[/C][C]0.004235[/C][/ROW]
[ROW][C]13[/C][C]0.074934[/C][C]0.5455[/C][C]0.29384[/C][/ROW]
[ROW][C]14[/C][C]0.014696[/C][C]0.107[/C][C]0.4576[/C][/ROW]
[ROW][C]15[/C][C]0.09315[/C][C]0.6781[/C][C]0.250315[/C][/ROW]
[ROW][C]16[/C][C]-0.165414[/C][C]-1.2042[/C][C]0.116926[/C][/ROW]
[ROW][C]17[/C][C]0.205175[/C][C]1.4937[/C][C]0.070593[/C][/ROW]
[ROW][C]18[/C][C]-0.187455[/C][C]-1.3647[/C][C]0.089058[/C][/ROW]
[ROW][C]19[/C][C]0.125817[/C][C]0.916[/C][C]0.181918[/C][/ROW]
[ROW][C]20[/C][C]-0.028897[/C][C]-0.2104[/C][C]0.417093[/C][/ROW]
[ROW][C]21[/C][C]-0.097995[/C][C]-0.7134[/C][C]0.239359[/C][/ROW]
[ROW][C]22[/C][C]0.138437[/C][C]1.0078[/C][C]0.159056[/C][/ROW]
[ROW][C]23[/C][C]-0.088463[/C][C]-0.644[/C][C]0.261169[/C][/ROW]
[ROW][C]24[/C][C]0.00513[/C][C]0.0373[/C][C]0.485174[/C][/ROW]
[ROW][C]25[/C][C]-0.022819[/C][C]-0.1661[/C][C]0.434347[/C][/ROW]
[ROW][C]26[/C][C]0.098695[/C][C]0.7185[/C][C]0.237799[/C][/ROW]
[ROW][C]27[/C][C]-0.096028[/C][C]-0.6991[/C][C]0.243775[/C][/ROW]
[ROW][C]28[/C][C]0.025744[/C][C]0.1874[/C][C]0.426022[/C][/ROW]
[ROW][C]29[/C][C]-0.037209[/C][C]-0.2709[/C][C]0.393767[/C][/ROW]
[ROW][C]30[/C][C]0.039189[/C][C]0.2853[/C][C]0.388262[/C][/ROW]
[ROW][C]31[/C][C]0.006009[/C][C]0.0437[/C][C]0.482637[/C][/ROW]
[ROW][C]32[/C][C]-0.052094[/C][C]-0.3793[/C][C]0.353008[/C][/ROW]
[ROW][C]33[/C][C]0.082786[/C][C]0.6027[/C][C]0.274643[/C][/ROW]
[ROW][C]34[/C][C]-0.07008[/C][C]-0.5102[/C][C]0.306017[/C][/ROW]
[ROW][C]35[/C][C]0.066169[/C][C]0.4817[/C][C]0.315995[/C][/ROW]
[ROW][C]36[/C][C]-0.049055[/C][C]-0.3571[/C][C]0.361207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62821&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62821&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
1-0.615461-4.48062e-05
20.1172360.85350.198615
30.0457720.33320.37014
40.0513630.37390.354974
5-0.157697-1.1480.128052
60.1247660.90830.183913
7-0.100471-0.73140.233866
80.0679890.4950.311335
90.0653820.4760.318021
10-0.342444-2.4930.007912
110.520023.78580.000196
12-0.375653-2.73480.004235
130.0749340.54550.29384
140.0146960.1070.4576
150.093150.67810.250315
16-0.165414-1.20420.116926
170.2051751.49370.070593
18-0.187455-1.36470.089058
190.1258170.9160.181918
20-0.028897-0.21040.417093
21-0.097995-0.71340.239359
220.1384371.00780.159056
23-0.088463-0.6440.261169
240.005130.03730.485174
25-0.022819-0.16610.434347
260.0986950.71850.237799
27-0.096028-0.69910.243775
280.0257440.18740.426022
29-0.037209-0.27090.393767
300.0391890.28530.388262
310.0060090.04370.482637
32-0.052094-0.37930.353008
330.0827860.60270.274643
34-0.07008-0.51020.306017
350.0661690.48170.315995
36-0.049055-0.35710.361207







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.615461-4.48062e-05
2-0.421044-3.06520.001709
3-0.216855-1.57870.060175
40.0692030.50380.308243
5-0.046746-0.34030.367482
6-0.038683-0.28160.389667
7-0.160125-1.16570.124472
8-0.106955-0.77860.219825
90.1664821.2120.115443
10-0.3831-2.7890.003664
110.1603081.16710.124204
120.0032230.02350.490684
13-0.084416-0.61460.270739
14-0.126136-0.91830.181315
15-0.09891-0.72010.23732
160.057290.41710.339153
170.1532841.11590.134744
180.0243120.1770.430094
190.0086430.06290.475034
20-0.099304-0.72290.236446
210.0641870.46730.321105
22-0.094364-0.6870.247545
23-0.045911-0.33420.36976
240.0203970.14850.44126
25-0.097464-0.70950.240547
26-0.013978-0.10180.459664
270.0622020.45280.326256
28-0.172239-1.25390.107687
29-0.051415-0.37430.354834
30-0.195574-1.42380.080182
31-0.010829-0.07880.468729
32-0.083523-0.60810.272874
330.000530.00390.498467
34-0.09208-0.67040.252772
35-0.04339-0.31590.376666
360.0764970.55690.289968

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.615461 & -4.4806 & 2e-05 \tabularnewline
2 & -0.421044 & -3.0652 & 0.001709 \tabularnewline
3 & -0.216855 & -1.5787 & 0.060175 \tabularnewline
4 & 0.069203 & 0.5038 & 0.308243 \tabularnewline
5 & -0.046746 & -0.3403 & 0.367482 \tabularnewline
6 & -0.038683 & -0.2816 & 0.389667 \tabularnewline
7 & -0.160125 & -1.1657 & 0.124472 \tabularnewline
8 & -0.106955 & -0.7786 & 0.219825 \tabularnewline
9 & 0.166482 & 1.212 & 0.115443 \tabularnewline
10 & -0.3831 & -2.789 & 0.003664 \tabularnewline
11 & 0.160308 & 1.1671 & 0.124204 \tabularnewline
12 & 0.003223 & 0.0235 & 0.490684 \tabularnewline
13 & -0.084416 & -0.6146 & 0.270739 \tabularnewline
14 & -0.126136 & -0.9183 & 0.181315 \tabularnewline
15 & -0.09891 & -0.7201 & 0.23732 \tabularnewline
16 & 0.05729 & 0.4171 & 0.339153 \tabularnewline
17 & 0.153284 & 1.1159 & 0.134744 \tabularnewline
18 & 0.024312 & 0.177 & 0.430094 \tabularnewline
19 & 0.008643 & 0.0629 & 0.475034 \tabularnewline
20 & -0.099304 & -0.7229 & 0.236446 \tabularnewline
21 & 0.064187 & 0.4673 & 0.321105 \tabularnewline
22 & -0.094364 & -0.687 & 0.247545 \tabularnewline
23 & -0.045911 & -0.3342 & 0.36976 \tabularnewline
24 & 0.020397 & 0.1485 & 0.44126 \tabularnewline
25 & -0.097464 & -0.7095 & 0.240547 \tabularnewline
26 & -0.013978 & -0.1018 & 0.459664 \tabularnewline
27 & 0.062202 & 0.4528 & 0.326256 \tabularnewline
28 & -0.172239 & -1.2539 & 0.107687 \tabularnewline
29 & -0.051415 & -0.3743 & 0.354834 \tabularnewline
30 & -0.195574 & -1.4238 & 0.080182 \tabularnewline
31 & -0.010829 & -0.0788 & 0.468729 \tabularnewline
32 & -0.083523 & -0.6081 & 0.272874 \tabularnewline
33 & 0.00053 & 0.0039 & 0.498467 \tabularnewline
34 & -0.09208 & -0.6704 & 0.252772 \tabularnewline
35 & -0.04339 & -0.3159 & 0.376666 \tabularnewline
36 & 0.076497 & 0.5569 & 0.289968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62821&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]-0.615461[/C][C]-4.4806[/C][C]2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.421044[/C][C]-3.0652[/C][C]0.001709[/C][/ROW]
[ROW][C]3[/C][C]-0.216855[/C][C]-1.5787[/C][C]0.060175[/C][/ROW]
[ROW][C]4[/C][C]0.069203[/C][C]0.5038[/C][C]0.308243[/C][/ROW]
[ROW][C]5[/C][C]-0.046746[/C][C]-0.3403[/C][C]0.367482[/C][/ROW]
[ROW][C]6[/C][C]-0.038683[/C][C]-0.2816[/C][C]0.389667[/C][/ROW]
[ROW][C]7[/C][C]-0.160125[/C][C]-1.1657[/C][C]0.124472[/C][/ROW]
[ROW][C]8[/C][C]-0.106955[/C][C]-0.7786[/C][C]0.219825[/C][/ROW]
[ROW][C]9[/C][C]0.166482[/C][C]1.212[/C][C]0.115443[/C][/ROW]
[ROW][C]10[/C][C]-0.3831[/C][C]-2.789[/C][C]0.003664[/C][/ROW]
[ROW][C]11[/C][C]0.160308[/C][C]1.1671[/C][C]0.124204[/C][/ROW]
[ROW][C]12[/C][C]0.003223[/C][C]0.0235[/C][C]0.490684[/C][/ROW]
[ROW][C]13[/C][C]-0.084416[/C][C]-0.6146[/C][C]0.270739[/C][/ROW]
[ROW][C]14[/C][C]-0.126136[/C][C]-0.9183[/C][C]0.181315[/C][/ROW]
[ROW][C]15[/C][C]-0.09891[/C][C]-0.7201[/C][C]0.23732[/C][/ROW]
[ROW][C]16[/C][C]0.05729[/C][C]0.4171[/C][C]0.339153[/C][/ROW]
[ROW][C]17[/C][C]0.153284[/C][C]1.1159[/C][C]0.134744[/C][/ROW]
[ROW][C]18[/C][C]0.024312[/C][C]0.177[/C][C]0.430094[/C][/ROW]
[ROW][C]19[/C][C]0.008643[/C][C]0.0629[/C][C]0.475034[/C][/ROW]
[ROW][C]20[/C][C]-0.099304[/C][C]-0.7229[/C][C]0.236446[/C][/ROW]
[ROW][C]21[/C][C]0.064187[/C][C]0.4673[/C][C]0.321105[/C][/ROW]
[ROW][C]22[/C][C]-0.094364[/C][C]-0.687[/C][C]0.247545[/C][/ROW]
[ROW][C]23[/C][C]-0.045911[/C][C]-0.3342[/C][C]0.36976[/C][/ROW]
[ROW][C]24[/C][C]0.020397[/C][C]0.1485[/C][C]0.44126[/C][/ROW]
[ROW][C]25[/C][C]-0.097464[/C][C]-0.7095[/C][C]0.240547[/C][/ROW]
[ROW][C]26[/C][C]-0.013978[/C][C]-0.1018[/C][C]0.459664[/C][/ROW]
[ROW][C]27[/C][C]0.062202[/C][C]0.4528[/C][C]0.326256[/C][/ROW]
[ROW][C]28[/C][C]-0.172239[/C][C]-1.2539[/C][C]0.107687[/C][/ROW]
[ROW][C]29[/C][C]-0.051415[/C][C]-0.3743[/C][C]0.354834[/C][/ROW]
[ROW][C]30[/C][C]-0.195574[/C][C]-1.4238[/C][C]0.080182[/C][/ROW]
[ROW][C]31[/C][C]-0.010829[/C][C]-0.0788[/C][C]0.468729[/C][/ROW]
[ROW][C]32[/C][C]-0.083523[/C][C]-0.6081[/C][C]0.272874[/C][/ROW]
[ROW][C]33[/C][C]0.00053[/C][C]0.0039[/C][C]0.498467[/C][/ROW]
[ROW][C]34[/C][C]-0.09208[/C][C]-0.6704[/C][C]0.252772[/C][/ROW]
[ROW][C]35[/C][C]-0.04339[/C][C]-0.3159[/C][C]0.376666[/C][/ROW]
[ROW][C]36[/C][C]0.076497[/C][C]0.5569[/C][C]0.289968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62821&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62821&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
1-0.615461-4.48062e-05
2-0.421044-3.06520.001709
3-0.216855-1.57870.060175
40.0692030.50380.308243
5-0.046746-0.34030.367482
6-0.038683-0.28160.389667
7-0.160125-1.16570.124472
8-0.106955-0.77860.219825
90.1664821.2120.115443
10-0.3831-2.7890.003664
110.1603081.16710.124204
120.0032230.02350.490684
13-0.084416-0.61460.270739
14-0.126136-0.91830.181315
15-0.09891-0.72010.23732
160.057290.41710.339153
170.1532841.11590.134744
180.0243120.1770.430094
190.0086430.06290.475034
20-0.099304-0.72290.236446
210.0641870.46730.321105
22-0.094364-0.6870.247545
23-0.045911-0.33420.36976
240.0203970.14850.44126
25-0.097464-0.70950.240547
26-0.013978-0.10180.459664
270.0622020.45280.326256
28-0.172239-1.25390.107687
29-0.051415-0.37430.354834
30-0.195574-1.42380.080182
31-0.010829-0.07880.468729
32-0.083523-0.60810.272874
330.000530.00390.498467
34-0.09208-0.67040.252772
35-0.04339-0.31590.376666
360.0764970.55690.289968



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')