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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 computationFri, 04 Dec 2009 10:21:17 -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/04/t12599473160gr3eajssmam6gg.htm/, Retrieved Sun, 28 Apr 2024 08:41:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63932, Retrieved Sun, 28 Apr 2024 08:41:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

Tree of Dependent Computations

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS8] [2009-11-25 21:36:53] [cd6314e7e707a6546bd4604c9d1f2b69]
-                 [(Partial) Autocorrelation Function] [Paper - ACF (2)] [2009-12-04 17:21:17] [ea241b681aafed79da4b5b99fad98471] [Current]
-   P               [(Partial) Autocorrelation Function] [Paper - ACF (2)] [2009-12-04 20:08:36] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186412
189226
191563
188906
186005
195309
223532
226899
214126

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'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=63932&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=63932&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63932&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9279217.00570
20.8615466.50450
30.7780035.87380
40.6946345.24441e-06
50.5984264.5181.6e-05
60.5031463.79870.000178
70.4067193.07070.001635
80.3159332.38520.010208
90.2423511.82970.036262
100.1724781.30220.099046
110.1114440.84140.201825
120.0382870.28910.386791
13-0.009484-0.07160.471586
14-0.060387-0.45590.325093
15-0.115515-0.87210.193401
16-0.191593-1.44650.076758
17-0.255833-1.93150.029199
18-0.321062-2.4240.009274
19-0.378382-2.85670.002982
20-0.421374-3.18130.001187
21-0.468712-3.53870.000404
22-0.501506-3.78630.000185
23-0.522388-3.94390.000111
24-0.525728-3.96920.000102
25-0.520021-3.92610.000118
26-0.517729-3.90880.000124
27-0.50614-3.82130.000165
28-0.468603-3.53790.000405
29-0.425122-3.20960.001092
30-0.376381-2.84160.003108
31-0.337357-2.5470.006795
32-0.295753-2.23290.01475
33-0.253491-1.91380.030335
34-0.205629-1.55250.063043
35-0.163229-1.23240.111439
36-0.124761-0.94190.175102

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.927921 & 7.0057 & 0 \tabularnewline
2 & 0.861546 & 6.5045 & 0 \tabularnewline
3 & 0.778003 & 5.8738 & 0 \tabularnewline
4 & 0.694634 & 5.2444 & 1e-06 \tabularnewline
5 & 0.598426 & 4.518 & 1.6e-05 \tabularnewline
6 & 0.503146 & 3.7987 & 0.000178 \tabularnewline
7 & 0.406719 & 3.0707 & 0.001635 \tabularnewline
8 & 0.315933 & 2.3852 & 0.010208 \tabularnewline
9 & 0.242351 & 1.8297 & 0.036262 \tabularnewline
10 & 0.172478 & 1.3022 & 0.099046 \tabularnewline
11 & 0.111444 & 0.8414 & 0.201825 \tabularnewline
12 & 0.038287 & 0.2891 & 0.386791 \tabularnewline
13 & -0.009484 & -0.0716 & 0.471586 \tabularnewline
14 & -0.060387 & -0.4559 & 0.325093 \tabularnewline
15 & -0.115515 & -0.8721 & 0.193401 \tabularnewline
16 & -0.191593 & -1.4465 & 0.076758 \tabularnewline
17 & -0.255833 & -1.9315 & 0.029199 \tabularnewline
18 & -0.321062 & -2.424 & 0.009274 \tabularnewline
19 & -0.378382 & -2.8567 & 0.002982 \tabularnewline
20 & -0.421374 & -3.1813 & 0.001187 \tabularnewline
21 & -0.468712 & -3.5387 & 0.000404 \tabularnewline
22 & -0.501506 & -3.7863 & 0.000185 \tabularnewline
23 & -0.522388 & -3.9439 & 0.000111 \tabularnewline
24 & -0.525728 & -3.9692 & 0.000102 \tabularnewline
25 & -0.520021 & -3.9261 & 0.000118 \tabularnewline
26 & -0.517729 & -3.9088 & 0.000124 \tabularnewline
27 & -0.50614 & -3.8213 & 0.000165 \tabularnewline
28 & -0.468603 & -3.5379 & 0.000405 \tabularnewline
29 & -0.425122 & -3.2096 & 0.001092 \tabularnewline
30 & -0.376381 & -2.8416 & 0.003108 \tabularnewline
31 & -0.337357 & -2.547 & 0.006795 \tabularnewline
32 & -0.295753 & -2.2329 & 0.01475 \tabularnewline
33 & -0.253491 & -1.9138 & 0.030335 \tabularnewline
34 & -0.205629 & -1.5525 & 0.063043 \tabularnewline
35 & -0.163229 & -1.2324 & 0.111439 \tabularnewline
36 & -0.124761 & -0.9419 & 0.175102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63932&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]0.927921[/C][C]7.0057[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.861546[/C][C]6.5045[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.778003[/C][C]5.8738[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.694634[/C][C]5.2444[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.598426[/C][C]4.518[/C][C]1.6e-05[/C][/ROW]
[ROW][C]6[/C][C]0.503146[/C][C]3.7987[/C][C]0.000178[/C][/ROW]
[ROW][C]7[/C][C]0.406719[/C][C]3.0707[/C][C]0.001635[/C][/ROW]
[ROW][C]8[/C][C]0.315933[/C][C]2.3852[/C][C]0.010208[/C][/ROW]
[ROW][C]9[/C][C]0.242351[/C][C]1.8297[/C][C]0.036262[/C][/ROW]
[ROW][C]10[/C][C]0.172478[/C][C]1.3022[/C][C]0.099046[/C][/ROW]
[ROW][C]11[/C][C]0.111444[/C][C]0.8414[/C][C]0.201825[/C][/ROW]
[ROW][C]12[/C][C]0.038287[/C][C]0.2891[/C][C]0.386791[/C][/ROW]
[ROW][C]13[/C][C]-0.009484[/C][C]-0.0716[/C][C]0.471586[/C][/ROW]
[ROW][C]14[/C][C]-0.060387[/C][C]-0.4559[/C][C]0.325093[/C][/ROW]
[ROW][C]15[/C][C]-0.115515[/C][C]-0.8721[/C][C]0.193401[/C][/ROW]
[ROW][C]16[/C][C]-0.191593[/C][C]-1.4465[/C][C]0.076758[/C][/ROW]
[ROW][C]17[/C][C]-0.255833[/C][C]-1.9315[/C][C]0.029199[/C][/ROW]
[ROW][C]18[/C][C]-0.321062[/C][C]-2.424[/C][C]0.009274[/C][/ROW]
[ROW][C]19[/C][C]-0.378382[/C][C]-2.8567[/C][C]0.002982[/C][/ROW]
[ROW][C]20[/C][C]-0.421374[/C][C]-3.1813[/C][C]0.001187[/C][/ROW]
[ROW][C]21[/C][C]-0.468712[/C][C]-3.5387[/C][C]0.000404[/C][/ROW]
[ROW][C]22[/C][C]-0.501506[/C][C]-3.7863[/C][C]0.000185[/C][/ROW]
[ROW][C]23[/C][C]-0.522388[/C][C]-3.9439[/C][C]0.000111[/C][/ROW]
[ROW][C]24[/C][C]-0.525728[/C][C]-3.9692[/C][C]0.000102[/C][/ROW]
[ROW][C]25[/C][C]-0.520021[/C][C]-3.9261[/C][C]0.000118[/C][/ROW]
[ROW][C]26[/C][C]-0.517729[/C][C]-3.9088[/C][C]0.000124[/C][/ROW]
[ROW][C]27[/C][C]-0.50614[/C][C]-3.8213[/C][C]0.000165[/C][/ROW]
[ROW][C]28[/C][C]-0.468603[/C][C]-3.5379[/C][C]0.000405[/C][/ROW]
[ROW][C]29[/C][C]-0.425122[/C][C]-3.2096[/C][C]0.001092[/C][/ROW]
[ROW][C]30[/C][C]-0.376381[/C][C]-2.8416[/C][C]0.003108[/C][/ROW]
[ROW][C]31[/C][C]-0.337357[/C][C]-2.547[/C][C]0.006795[/C][/ROW]
[ROW][C]32[/C][C]-0.295753[/C][C]-2.2329[/C][C]0.01475[/C][/ROW]
[ROW][C]33[/C][C]-0.253491[/C][C]-1.9138[/C][C]0.030335[/C][/ROW]
[ROW][C]34[/C][C]-0.205629[/C][C]-1.5525[/C][C]0.063043[/C][/ROW]
[ROW][C]35[/C][C]-0.163229[/C][C]-1.2324[/C][C]0.111439[/C][/ROW]
[ROW][C]36[/C][C]-0.124761[/C][C]-0.9419[/C][C]0.175102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63932&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63932&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
10.9279217.00570
20.8615466.50450
30.7780035.87380
40.6946345.24441e-06
50.5984264.5181.6e-05
60.5031463.79870.000178
70.4067193.07070.001635
80.3159332.38520.010208
90.2423511.82970.036262
100.1724781.30220.099046
110.1114440.84140.201825
120.0382870.28910.386791
13-0.009484-0.07160.471586
14-0.060387-0.45590.325093
15-0.115515-0.87210.193401
16-0.191593-1.44650.076758
17-0.255833-1.93150.029199
18-0.321062-2.4240.009274
19-0.378382-2.85670.002982
20-0.421374-3.18130.001187
21-0.468712-3.53870.000404
22-0.501506-3.78630.000185
23-0.522388-3.94390.000111
24-0.525728-3.96920.000102
25-0.520021-3.92610.000118
26-0.517729-3.90880.000124
27-0.50614-3.82130.000165
28-0.468603-3.53790.000405
29-0.425122-3.20960.001092
30-0.376381-2.84160.003108
31-0.337357-2.5470.006795
32-0.295753-2.23290.01475
33-0.253491-1.91380.030335
34-0.205629-1.55250.063043
35-0.163229-1.23240.111439
36-0.124761-0.94190.175102






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9279217.00570
20.0036560.02760.489039
3-0.157701-1.19060.119369
4-0.055564-0.41950.338213
5-0.13098-0.98890.163452
6-0.06136-0.46330.322473
7-0.054642-0.41250.340746
8-0.026922-0.20330.41983
90.0717820.54190.294984
10-0.026871-0.20290.419978
11-0.016879-0.12740.449521
12-0.158492-1.19660.118211
130.0812870.61370.270925
14-0.053848-0.40650.342933
15-0.137603-1.03890.151623
16-0.219413-1.65650.051555
17-0.01792-0.13530.446428
18-0.047435-0.35810.360785
19-0.037612-0.2840.388733
200.0354920.2680.394849
21-0.097368-0.73510.232642
22-0.00679-0.05130.479649
230.0040570.03060.487836
24-0.033976-0.25650.39924
250.0170040.12840.449152
26-0.124189-0.93760.176201
27-0.005719-0.04320.482857
280.1084540.81880.208153
290.0374610.28280.389168
300.0256340.19350.423614
31-0.098716-0.74530.22958
32-0.002323-0.01750.493035
33-0.021895-0.16530.434644
34-0.002457-0.01850.492634
35-0.043078-0.32520.373098
36-0.00455-0.03440.486359

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.927921 & 7.0057 & 0 \tabularnewline
2 & 0.003656 & 0.0276 & 0.489039 \tabularnewline
3 & -0.157701 & -1.1906 & 0.119369 \tabularnewline
4 & -0.055564 & -0.4195 & 0.338213 \tabularnewline
5 & -0.13098 & -0.9889 & 0.163452 \tabularnewline
6 & -0.06136 & -0.4633 & 0.322473 \tabularnewline
7 & -0.054642 & -0.4125 & 0.340746 \tabularnewline
8 & -0.026922 & -0.2033 & 0.41983 \tabularnewline
9 & 0.071782 & 0.5419 & 0.294984 \tabularnewline
10 & -0.026871 & -0.2029 & 0.419978 \tabularnewline
11 & -0.016879 & -0.1274 & 0.449521 \tabularnewline
12 & -0.158492 & -1.1966 & 0.118211 \tabularnewline
13 & 0.081287 & 0.6137 & 0.270925 \tabularnewline
14 & -0.053848 & -0.4065 & 0.342933 \tabularnewline
15 & -0.137603 & -1.0389 & 0.151623 \tabularnewline
16 & -0.219413 & -1.6565 & 0.051555 \tabularnewline
17 & -0.01792 & -0.1353 & 0.446428 \tabularnewline
18 & -0.047435 & -0.3581 & 0.360785 \tabularnewline
19 & -0.037612 & -0.284 & 0.388733 \tabularnewline
20 & 0.035492 & 0.268 & 0.394849 \tabularnewline
21 & -0.097368 & -0.7351 & 0.232642 \tabularnewline
22 & -0.00679 & -0.0513 & 0.479649 \tabularnewline
23 & 0.004057 & 0.0306 & 0.487836 \tabularnewline
24 & -0.033976 & -0.2565 & 0.39924 \tabularnewline
25 & 0.017004 & 0.1284 & 0.449152 \tabularnewline
26 & -0.124189 & -0.9376 & 0.176201 \tabularnewline
27 & -0.005719 & -0.0432 & 0.482857 \tabularnewline
28 & 0.108454 & 0.8188 & 0.208153 \tabularnewline
29 & 0.037461 & 0.2828 & 0.389168 \tabularnewline
30 & 0.025634 & 0.1935 & 0.423614 \tabularnewline
31 & -0.098716 & -0.7453 & 0.22958 \tabularnewline
32 & -0.002323 & -0.0175 & 0.493035 \tabularnewline
33 & -0.021895 & -0.1653 & 0.434644 \tabularnewline
34 & -0.002457 & -0.0185 & 0.492634 \tabularnewline
35 & -0.043078 & -0.3252 & 0.373098 \tabularnewline
36 & -0.00455 & -0.0344 & 0.486359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63932&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]0.927921[/C][C]7.0057[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.003656[/C][C]0.0276[/C][C]0.489039[/C][/ROW]
[ROW][C]3[/C][C]-0.157701[/C][C]-1.1906[/C][C]0.119369[/C][/ROW]
[ROW][C]4[/C][C]-0.055564[/C][C]-0.4195[/C][C]0.338213[/C][/ROW]
[ROW][C]5[/C][C]-0.13098[/C][C]-0.9889[/C][C]0.163452[/C][/ROW]
[ROW][C]6[/C][C]-0.06136[/C][C]-0.4633[/C][C]0.322473[/C][/ROW]
[ROW][C]7[/C][C]-0.054642[/C][C]-0.4125[/C][C]0.340746[/C][/ROW]
[ROW][C]8[/C][C]-0.026922[/C][C]-0.2033[/C][C]0.41983[/C][/ROW]
[ROW][C]9[/C][C]0.071782[/C][C]0.5419[/C][C]0.294984[/C][/ROW]
[ROW][C]10[/C][C]-0.026871[/C][C]-0.2029[/C][C]0.419978[/C][/ROW]
[ROW][C]11[/C][C]-0.016879[/C][C]-0.1274[/C][C]0.449521[/C][/ROW]
[ROW][C]12[/C][C]-0.158492[/C][C]-1.1966[/C][C]0.118211[/C][/ROW]
[ROW][C]13[/C][C]0.081287[/C][C]0.6137[/C][C]0.270925[/C][/ROW]
[ROW][C]14[/C][C]-0.053848[/C][C]-0.4065[/C][C]0.342933[/C][/ROW]
[ROW][C]15[/C][C]-0.137603[/C][C]-1.0389[/C][C]0.151623[/C][/ROW]
[ROW][C]16[/C][C]-0.219413[/C][C]-1.6565[/C][C]0.051555[/C][/ROW]
[ROW][C]17[/C][C]-0.01792[/C][C]-0.1353[/C][C]0.446428[/C][/ROW]
[ROW][C]18[/C][C]-0.047435[/C][C]-0.3581[/C][C]0.360785[/C][/ROW]
[ROW][C]19[/C][C]-0.037612[/C][C]-0.284[/C][C]0.388733[/C][/ROW]
[ROW][C]20[/C][C]0.035492[/C][C]0.268[/C][C]0.394849[/C][/ROW]
[ROW][C]21[/C][C]-0.097368[/C][C]-0.7351[/C][C]0.232642[/C][/ROW]
[ROW][C]22[/C][C]-0.00679[/C][C]-0.0513[/C][C]0.479649[/C][/ROW]
[ROW][C]23[/C][C]0.004057[/C][C]0.0306[/C][C]0.487836[/C][/ROW]
[ROW][C]24[/C][C]-0.033976[/C][C]-0.2565[/C][C]0.39924[/C][/ROW]
[ROW][C]25[/C][C]0.017004[/C][C]0.1284[/C][C]0.449152[/C][/ROW]
[ROW][C]26[/C][C]-0.124189[/C][C]-0.9376[/C][C]0.176201[/C][/ROW]
[ROW][C]27[/C][C]-0.005719[/C][C]-0.0432[/C][C]0.482857[/C][/ROW]
[ROW][C]28[/C][C]0.108454[/C][C]0.8188[/C][C]0.208153[/C][/ROW]
[ROW][C]29[/C][C]0.037461[/C][C]0.2828[/C][C]0.389168[/C][/ROW]
[ROW][C]30[/C][C]0.025634[/C][C]0.1935[/C][C]0.423614[/C][/ROW]
[ROW][C]31[/C][C]-0.098716[/C][C]-0.7453[/C][C]0.22958[/C][/ROW]
[ROW][C]32[/C][C]-0.002323[/C][C]-0.0175[/C][C]0.493035[/C][/ROW]
[ROW][C]33[/C][C]-0.021895[/C][C]-0.1653[/C][C]0.434644[/C][/ROW]
[ROW][C]34[/C][C]-0.002457[/C][C]-0.0185[/C][C]0.492634[/C][/ROW]
[ROW][C]35[/C][C]-0.043078[/C][C]-0.3252[/C][C]0.373098[/C][/ROW]
[ROW][C]36[/C][C]-0.00455[/C][C]-0.0344[/C][C]0.486359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63932&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63932&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
10.9279217.00570
20.0036560.02760.489039
3-0.157701-1.19060.119369
4-0.055564-0.41950.338213
5-0.13098-0.98890.163452
6-0.06136-0.46330.322473
7-0.054642-0.41250.340746
8-0.026922-0.20330.41983
90.0717820.54190.294984
10-0.026871-0.20290.419978
11-0.016879-0.12740.449521
12-0.158492-1.19660.118211
130.0812870.61370.270925
14-0.053848-0.40650.342933
15-0.137603-1.03890.151623
16-0.219413-1.65650.051555
17-0.01792-0.13530.446428
18-0.047435-0.35810.360785
19-0.037612-0.2840.388733
200.0354920.2680.394849
21-0.097368-0.73510.232642
22-0.00679-0.05130.479649
230.0040570.03060.487836
24-0.033976-0.25650.39924
250.0170040.12840.449152
26-0.124189-0.93760.176201
27-0.005719-0.04320.482857
280.1084540.81880.208153
290.0374610.28280.389168
300.0256340.19350.423614
31-0.098716-0.74530.22958
32-0.002323-0.01750.493035
33-0.021895-0.16530.434644
34-0.002457-0.01850.492634
35-0.043078-0.32520.373098
36-0.00455-0.03440.486359


Figures (Output of Computation)

Input Parameters & R Code

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