Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 29 Nov 2011 07:05:22 -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/Nov/29/t1322568334j034hlza85zfxqy.htm/, Retrieved Thu, 28 Mar 2024 20:13:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148223, Retrieved Thu, 28 Mar 2024 20:13:23 +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)
-     [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]
-    D        [(Partial) Autocorrelation Function] [Ws8.1 ACF1] [2009-11-25 19:12:20] [e0fc65a5811681d807296d590d5b45de]
-               [(Partial) Autocorrelation Function] [Workshop 8 ACF] [2010-11-29 17:48:44] [814f53995537cd15c528d8efbf1cf544]
- RM                [(Partial) Autocorrelation Function] [] [2011-11-29 12:05:22] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
58608
46865
51378
46235
47206
45382
41227
33795
31295
42625
33625
21538
56421
53152
53536
52408
41454
38271
35306
26414
31917
38030
27534
18387
50556
43901
48572
43899
37532
40357
35489
29027
34485
42598
30306
26451
47460
50104
61465
53726
39477
43895
31481
29896
33842
39120
33702
25094
51442
45594
52518
48564
41745
49585
32747
33379
35645
37034
35681
20972




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148223&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148223&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148223&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'George Udny Yule' @ yule.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3864632.99350.002
20.1513671.17250.122819
30.0609570.47220.319258
4-0.175153-1.35670.089976
5-0.263012-2.03730.02302
6-0.419162-3.24680.000956
7-0.329088-2.54910.006687
8-0.21567-1.67060.050008
9-0.057349-0.44420.32924
100.0069960.05420.478481
110.2056711.59310.058194
120.7069535.4760
130.2972032.30210.012407
140.1218570.94390.174502
150.0430340.33330.370019
16-0.178412-1.3820.086052
17-0.228253-1.7680.041069
18-0.356357-2.76030.003824
19-0.297509-2.30450.012336
20-0.177617-1.37580.086997
21-0.115162-0.8920.187967
22-0.067331-0.52150.301954
230.1152140.89240.187861
240.4836223.74610.000203
250.2118731.64120.052998
260.0963290.74620.229243
270.0010070.00780.496901
28-0.130383-1.00990.158289
29-0.146713-1.13640.130146
30-0.275562-2.13450.018449
31-0.195594-1.51510.067503
32-0.085884-0.66530.254219
33-0.022774-0.17640.430284
340.0067540.05230.479226
350.1006620.77970.219309
360.3664432.83850.003089

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.386463 & 2.9935 & 0.002 \tabularnewline
2 & 0.151367 & 1.1725 & 0.122819 \tabularnewline
3 & 0.060957 & 0.4722 & 0.319258 \tabularnewline
4 & -0.175153 & -1.3567 & 0.089976 \tabularnewline
5 & -0.263012 & -2.0373 & 0.02302 \tabularnewline
6 & -0.419162 & -3.2468 & 0.000956 \tabularnewline
7 & -0.329088 & -2.5491 & 0.006687 \tabularnewline
8 & -0.21567 & -1.6706 & 0.050008 \tabularnewline
9 & -0.057349 & -0.4442 & 0.32924 \tabularnewline
10 & 0.006996 & 0.0542 & 0.478481 \tabularnewline
11 & 0.205671 & 1.5931 & 0.058194 \tabularnewline
12 & 0.706953 & 5.476 & 0 \tabularnewline
13 & 0.297203 & 2.3021 & 0.012407 \tabularnewline
14 & 0.121857 & 0.9439 & 0.174502 \tabularnewline
15 & 0.043034 & 0.3333 & 0.370019 \tabularnewline
16 & -0.178412 & -1.382 & 0.086052 \tabularnewline
17 & -0.228253 & -1.768 & 0.041069 \tabularnewline
18 & -0.356357 & -2.7603 & 0.003824 \tabularnewline
19 & -0.297509 & -2.3045 & 0.012336 \tabularnewline
20 & -0.177617 & -1.3758 & 0.086997 \tabularnewline
21 & -0.115162 & -0.892 & 0.187967 \tabularnewline
22 & -0.067331 & -0.5215 & 0.301954 \tabularnewline
23 & 0.115214 & 0.8924 & 0.187861 \tabularnewline
24 & 0.483622 & 3.7461 & 0.000203 \tabularnewline
25 & 0.211873 & 1.6412 & 0.052998 \tabularnewline
26 & 0.096329 & 0.7462 & 0.229243 \tabularnewline
27 & 0.001007 & 0.0078 & 0.496901 \tabularnewline
28 & -0.130383 & -1.0099 & 0.158289 \tabularnewline
29 & -0.146713 & -1.1364 & 0.130146 \tabularnewline
30 & -0.275562 & -2.1345 & 0.018449 \tabularnewline
31 & -0.195594 & -1.5151 & 0.067503 \tabularnewline
32 & -0.085884 & -0.6653 & 0.254219 \tabularnewline
33 & -0.022774 & -0.1764 & 0.430284 \tabularnewline
34 & 0.006754 & 0.0523 & 0.479226 \tabularnewline
35 & 0.100662 & 0.7797 & 0.219309 \tabularnewline
36 & 0.366443 & 2.8385 & 0.003089 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148223&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]0.386463[/C][C]2.9935[/C][C]0.002[/C][/ROW]
[ROW][C]2[/C][C]0.151367[/C][C]1.1725[/C][C]0.122819[/C][/ROW]
[ROW][C]3[/C][C]0.060957[/C][C]0.4722[/C][C]0.319258[/C][/ROW]
[ROW][C]4[/C][C]-0.175153[/C][C]-1.3567[/C][C]0.089976[/C][/ROW]
[ROW][C]5[/C][C]-0.263012[/C][C]-2.0373[/C][C]0.02302[/C][/ROW]
[ROW][C]6[/C][C]-0.419162[/C][C]-3.2468[/C][C]0.000956[/C][/ROW]
[ROW][C]7[/C][C]-0.329088[/C][C]-2.5491[/C][C]0.006687[/C][/ROW]
[ROW][C]8[/C][C]-0.21567[/C][C]-1.6706[/C][C]0.050008[/C][/ROW]
[ROW][C]9[/C][C]-0.057349[/C][C]-0.4442[/C][C]0.32924[/C][/ROW]
[ROW][C]10[/C][C]0.006996[/C][C]0.0542[/C][C]0.478481[/C][/ROW]
[ROW][C]11[/C][C]0.205671[/C][C]1.5931[/C][C]0.058194[/C][/ROW]
[ROW][C]12[/C][C]0.706953[/C][C]5.476[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.297203[/C][C]2.3021[/C][C]0.012407[/C][/ROW]
[ROW][C]14[/C][C]0.121857[/C][C]0.9439[/C][C]0.174502[/C][/ROW]
[ROW][C]15[/C][C]0.043034[/C][C]0.3333[/C][C]0.370019[/C][/ROW]
[ROW][C]16[/C][C]-0.178412[/C][C]-1.382[/C][C]0.086052[/C][/ROW]
[ROW][C]17[/C][C]-0.228253[/C][C]-1.768[/C][C]0.041069[/C][/ROW]
[ROW][C]18[/C][C]-0.356357[/C][C]-2.7603[/C][C]0.003824[/C][/ROW]
[ROW][C]19[/C][C]-0.297509[/C][C]-2.3045[/C][C]0.012336[/C][/ROW]
[ROW][C]20[/C][C]-0.177617[/C][C]-1.3758[/C][C]0.086997[/C][/ROW]
[ROW][C]21[/C][C]-0.115162[/C][C]-0.892[/C][C]0.187967[/C][/ROW]
[ROW][C]22[/C][C]-0.067331[/C][C]-0.5215[/C][C]0.301954[/C][/ROW]
[ROW][C]23[/C][C]0.115214[/C][C]0.8924[/C][C]0.187861[/C][/ROW]
[ROW][C]24[/C][C]0.483622[/C][C]3.7461[/C][C]0.000203[/C][/ROW]
[ROW][C]25[/C][C]0.211873[/C][C]1.6412[/C][C]0.052998[/C][/ROW]
[ROW][C]26[/C][C]0.096329[/C][C]0.7462[/C][C]0.229243[/C][/ROW]
[ROW][C]27[/C][C]0.001007[/C][C]0.0078[/C][C]0.496901[/C][/ROW]
[ROW][C]28[/C][C]-0.130383[/C][C]-1.0099[/C][C]0.158289[/C][/ROW]
[ROW][C]29[/C][C]-0.146713[/C][C]-1.1364[/C][C]0.130146[/C][/ROW]
[ROW][C]30[/C][C]-0.275562[/C][C]-2.1345[/C][C]0.018449[/C][/ROW]
[ROW][C]31[/C][C]-0.195594[/C][C]-1.5151[/C][C]0.067503[/C][/ROW]
[ROW][C]32[/C][C]-0.085884[/C][C]-0.6653[/C][C]0.254219[/C][/ROW]
[ROW][C]33[/C][C]-0.022774[/C][C]-0.1764[/C][C]0.430284[/C][/ROW]
[ROW][C]34[/C][C]0.006754[/C][C]0.0523[/C][C]0.479226[/C][/ROW]
[ROW][C]35[/C][C]0.100662[/C][C]0.7797[/C][C]0.219309[/C][/ROW]
[ROW][C]36[/C][C]0.366443[/C][C]2.8385[/C][C]0.003089[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148223&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148223&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
10.3864632.99350.002
20.1513671.17250.122819
30.0609570.47220.319258
4-0.175153-1.35670.089976
5-0.263012-2.03730.02302
6-0.419162-3.24680.000956
7-0.329088-2.54910.006687
8-0.21567-1.67060.050008
9-0.057349-0.44420.32924
100.0069960.05420.478481
110.2056711.59310.058194
120.7069535.4760
130.2972032.30210.012407
140.1218570.94390.174502
150.0430340.33330.370019
16-0.178412-1.3820.086052
17-0.228253-1.7680.041069
18-0.356357-2.76030.003824
19-0.297509-2.30450.012336
20-0.177617-1.37580.086997
21-0.115162-0.8920.187967
22-0.067331-0.52150.301954
230.1152140.89240.187861
240.4836223.74610.000203
250.2118731.64120.052998
260.0963290.74620.229243
270.0010070.00780.496901
28-0.130383-1.00990.158289
29-0.146713-1.13640.130146
30-0.275562-2.13450.018449
31-0.195594-1.51510.067503
32-0.085884-0.66530.254219
33-0.022774-0.17640.430284
340.0067540.05230.479226
350.1006620.77970.219309
360.3664432.83850.003089







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3864632.99350.002
20.0023660.01830.49272
30.001980.01530.493909
4-0.23472-1.81810.037018
5-0.147813-1.1450.128387
6-0.31246-2.42030.009276
7-0.075135-0.5820.281375
8-0.092957-0.720.237147
90.0453830.35150.363208
10-0.120403-0.93260.177373
110.137241.06310.146009
120.6281844.86594e-06
13-0.320532-2.48280.007924
14-0.117408-0.90940.183379
15-0.119305-0.92410.17956
16-0.040783-0.31590.376586
17-0.043686-0.33840.368125
180.0828010.64140.261861
190.016170.12530.45037
20-0.018777-0.14540.442423
21-0.155402-1.20370.116709
22-0.047919-0.37120.355906
230.0004480.00350.49862
24-0.08481-0.65690.256866
25-0.068528-0.53080.298753
26-0.020034-0.15520.4386
27-0.148622-1.15120.127104
280.0787940.61030.271972
290.0142660.11050.456188
30-0.063269-0.49010.312933
310.0143750.11130.455857
32-0.03505-0.27150.393469
330.1385011.07280.143823
340.0334030.25870.39836
35-0.097521-0.75540.226483
36-0.02175-0.16850.433389

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.386463 & 2.9935 & 0.002 \tabularnewline
2 & 0.002366 & 0.0183 & 0.49272 \tabularnewline
3 & 0.00198 & 0.0153 & 0.493909 \tabularnewline
4 & -0.23472 & -1.8181 & 0.037018 \tabularnewline
5 & -0.147813 & -1.145 & 0.128387 \tabularnewline
6 & -0.31246 & -2.4203 & 0.009276 \tabularnewline
7 & -0.075135 & -0.582 & 0.281375 \tabularnewline
8 & -0.092957 & -0.72 & 0.237147 \tabularnewline
9 & 0.045383 & 0.3515 & 0.363208 \tabularnewline
10 & -0.120403 & -0.9326 & 0.177373 \tabularnewline
11 & 0.13724 & 1.0631 & 0.146009 \tabularnewline
12 & 0.628184 & 4.8659 & 4e-06 \tabularnewline
13 & -0.320532 & -2.4828 & 0.007924 \tabularnewline
14 & -0.117408 & -0.9094 & 0.183379 \tabularnewline
15 & -0.119305 & -0.9241 & 0.17956 \tabularnewline
16 & -0.040783 & -0.3159 & 0.376586 \tabularnewline
17 & -0.043686 & -0.3384 & 0.368125 \tabularnewline
18 & 0.082801 & 0.6414 & 0.261861 \tabularnewline
19 & 0.01617 & 0.1253 & 0.45037 \tabularnewline
20 & -0.018777 & -0.1454 & 0.442423 \tabularnewline
21 & -0.155402 & -1.2037 & 0.116709 \tabularnewline
22 & -0.047919 & -0.3712 & 0.355906 \tabularnewline
23 & 0.000448 & 0.0035 & 0.49862 \tabularnewline
24 & -0.08481 & -0.6569 & 0.256866 \tabularnewline
25 & -0.068528 & -0.5308 & 0.298753 \tabularnewline
26 & -0.020034 & -0.1552 & 0.4386 \tabularnewline
27 & -0.148622 & -1.1512 & 0.127104 \tabularnewline
28 & 0.078794 & 0.6103 & 0.271972 \tabularnewline
29 & 0.014266 & 0.1105 & 0.456188 \tabularnewline
30 & -0.063269 & -0.4901 & 0.312933 \tabularnewline
31 & 0.014375 & 0.1113 & 0.455857 \tabularnewline
32 & -0.03505 & -0.2715 & 0.393469 \tabularnewline
33 & 0.138501 & 1.0728 & 0.143823 \tabularnewline
34 & 0.033403 & 0.2587 & 0.39836 \tabularnewline
35 & -0.097521 & -0.7554 & 0.226483 \tabularnewline
36 & -0.02175 & -0.1685 & 0.433389 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148223&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]0.386463[/C][C]2.9935[/C][C]0.002[/C][/ROW]
[ROW][C]2[/C][C]0.002366[/C][C]0.0183[/C][C]0.49272[/C][/ROW]
[ROW][C]3[/C][C]0.00198[/C][C]0.0153[/C][C]0.493909[/C][/ROW]
[ROW][C]4[/C][C]-0.23472[/C][C]-1.8181[/C][C]0.037018[/C][/ROW]
[ROW][C]5[/C][C]-0.147813[/C][C]-1.145[/C][C]0.128387[/C][/ROW]
[ROW][C]6[/C][C]-0.31246[/C][C]-2.4203[/C][C]0.009276[/C][/ROW]
[ROW][C]7[/C][C]-0.075135[/C][C]-0.582[/C][C]0.281375[/C][/ROW]
[ROW][C]8[/C][C]-0.092957[/C][C]-0.72[/C][C]0.237147[/C][/ROW]
[ROW][C]9[/C][C]0.045383[/C][C]0.3515[/C][C]0.363208[/C][/ROW]
[ROW][C]10[/C][C]-0.120403[/C][C]-0.9326[/C][C]0.177373[/C][/ROW]
[ROW][C]11[/C][C]0.13724[/C][C]1.0631[/C][C]0.146009[/C][/ROW]
[ROW][C]12[/C][C]0.628184[/C][C]4.8659[/C][C]4e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.320532[/C][C]-2.4828[/C][C]0.007924[/C][/ROW]
[ROW][C]14[/C][C]-0.117408[/C][C]-0.9094[/C][C]0.183379[/C][/ROW]
[ROW][C]15[/C][C]-0.119305[/C][C]-0.9241[/C][C]0.17956[/C][/ROW]
[ROW][C]16[/C][C]-0.040783[/C][C]-0.3159[/C][C]0.376586[/C][/ROW]
[ROW][C]17[/C][C]-0.043686[/C][C]-0.3384[/C][C]0.368125[/C][/ROW]
[ROW][C]18[/C][C]0.082801[/C][C]0.6414[/C][C]0.261861[/C][/ROW]
[ROW][C]19[/C][C]0.01617[/C][C]0.1253[/C][C]0.45037[/C][/ROW]
[ROW][C]20[/C][C]-0.018777[/C][C]-0.1454[/C][C]0.442423[/C][/ROW]
[ROW][C]21[/C][C]-0.155402[/C][C]-1.2037[/C][C]0.116709[/C][/ROW]
[ROW][C]22[/C][C]-0.047919[/C][C]-0.3712[/C][C]0.355906[/C][/ROW]
[ROW][C]23[/C][C]0.000448[/C][C]0.0035[/C][C]0.49862[/C][/ROW]
[ROW][C]24[/C][C]-0.08481[/C][C]-0.6569[/C][C]0.256866[/C][/ROW]
[ROW][C]25[/C][C]-0.068528[/C][C]-0.5308[/C][C]0.298753[/C][/ROW]
[ROW][C]26[/C][C]-0.020034[/C][C]-0.1552[/C][C]0.4386[/C][/ROW]
[ROW][C]27[/C][C]-0.148622[/C][C]-1.1512[/C][C]0.127104[/C][/ROW]
[ROW][C]28[/C][C]0.078794[/C][C]0.6103[/C][C]0.271972[/C][/ROW]
[ROW][C]29[/C][C]0.014266[/C][C]0.1105[/C][C]0.456188[/C][/ROW]
[ROW][C]30[/C][C]-0.063269[/C][C]-0.4901[/C][C]0.312933[/C][/ROW]
[ROW][C]31[/C][C]0.014375[/C][C]0.1113[/C][C]0.455857[/C][/ROW]
[ROW][C]32[/C][C]-0.03505[/C][C]-0.2715[/C][C]0.393469[/C][/ROW]
[ROW][C]33[/C][C]0.138501[/C][C]1.0728[/C][C]0.143823[/C][/ROW]
[ROW][C]34[/C][C]0.033403[/C][C]0.2587[/C][C]0.39836[/C][/ROW]
[ROW][C]35[/C][C]-0.097521[/C][C]-0.7554[/C][C]0.226483[/C][/ROW]
[ROW][C]36[/C][C]-0.02175[/C][C]-0.1685[/C][C]0.433389[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148223&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148223&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
10.3864632.99350.002
20.0023660.01830.49272
30.001980.01530.493909
4-0.23472-1.81810.037018
5-0.147813-1.1450.128387
6-0.31246-2.42030.009276
7-0.075135-0.5820.281375
8-0.092957-0.720.237147
90.0453830.35150.363208
10-0.120403-0.93260.177373
110.137241.06310.146009
120.6281844.86594e-06
13-0.320532-2.48280.007924
14-0.117408-0.90940.183379
15-0.119305-0.92410.17956
16-0.040783-0.31590.376586
17-0.043686-0.33840.368125
180.0828010.64140.261861
190.016170.12530.45037
20-0.018777-0.14540.442423
21-0.155402-1.20370.116709
22-0.047919-0.37120.355906
230.0004480.00350.49862
24-0.08481-0.65690.256866
25-0.068528-0.53080.298753
26-0.020034-0.15520.4386
27-0.148622-1.15120.127104
280.0787940.61030.271972
290.0142660.11050.456188
30-0.063269-0.49010.312933
310.0143750.11130.455857
32-0.03505-0.27150.393469
330.1385011.07280.143823
340.0334030.25870.39836
35-0.097521-0.75540.226483
36-0.02175-0.16850.433389



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 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')