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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 computationTue, 16 Dec 2008 07:02:56 -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/2008/Dec/16/t1229436237qvhv1markfbl6oi.htm/, Retrieved Wed, 15 May 2024 05:40:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33950, Retrieved Wed, 15 May 2024 05:40:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Mean plot vervaar...] [2007-11-09 12:25:12] [74be16979710d4c4e7c6647856088456]
- R  D  [Mean Plot] [Mean plot Vlaams ...] [2008-12-13 21:24:44] [005293453b571dbccb80b45226e44173]
- RMPD    [Variance Reduction Matrix] [Variance Reductio...] [2008-12-14 16:50:50] [005293453b571dbccb80b45226e44173]
-    D      [Variance Reduction Matrix] [Variance Reductio...] [2008-12-14 17:00:55] [005293453b571dbccb80b45226e44173]
- RM          [(Partial) Autocorrelation Function] [partial autocorr ...] [2008-12-14 17:18:01] [005293453b571dbccb80b45226e44173]
-   P           [(Partial) Autocorrelation Function] [part autocorrelat...] [2008-12-14 18:33:57] [005293453b571dbccb80b45226e44173]
-   P               [(Partial) Autocorrelation Function] [pacf vlaams gewes...] [2008-12-16 14:02:56] [b0654df83a8a0e1de3ceb7bf60f0d58f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
217859
208679
213188
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33950&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33950&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9206036.37810
20.8647455.99110
30.7883985.46221e-06
40.7305365.06133e-06
50.6610984.58021.7e-05
60.5822534.0349.8e-05
70.505593.50280.000503
80.4203162.9120.002717
90.3519542.43840.009251
100.25981.79990.039078
110.1897811.31480.097406
120.097470.67530.251365
130.0480630.3330.370296
14-0.010323-0.07150.47164
15-0.071457-0.49510.311406
16-0.11192-0.77540.220952
17-0.152782-1.05850.147561
18-0.18087-1.25310.108119
19-0.231374-1.6030.057747
20-0.282351-1.95620.028138
21-0.340475-2.35890.011224
22-0.379333-2.62810.005748
23-0.402052-2.78550.003814
24-0.432477-2.99630.002158
25-0.436914-3.0270.001982
26-0.441071-3.05580.00183
27-0.424838-2.94340.002495
28-0.429136-2.97310.0023
29-0.416523-2.88580.002917
30-0.39747-2.75380.004148
31-0.358697-2.48510.008244
32-0.319045-2.21040.015938
33-0.272033-1.88470.032767
34-0.238352-1.65140.052598
35-0.198721-1.37680.087484
36-0.137209-0.95060.173282

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.920603 & 6.3781 & 0 \tabularnewline
2 & 0.864745 & 5.9911 & 0 \tabularnewline
3 & 0.788398 & 5.4622 & 1e-06 \tabularnewline
4 & 0.730536 & 5.0613 & 3e-06 \tabularnewline
5 & 0.661098 & 4.5802 & 1.7e-05 \tabularnewline
6 & 0.582253 & 4.034 & 9.8e-05 \tabularnewline
7 & 0.50559 & 3.5028 & 0.000503 \tabularnewline
8 & 0.420316 & 2.912 & 0.002717 \tabularnewline
9 & 0.351954 & 2.4384 & 0.009251 \tabularnewline
10 & 0.2598 & 1.7999 & 0.039078 \tabularnewline
11 & 0.189781 & 1.3148 & 0.097406 \tabularnewline
12 & 0.09747 & 0.6753 & 0.251365 \tabularnewline
13 & 0.048063 & 0.333 & 0.370296 \tabularnewline
14 & -0.010323 & -0.0715 & 0.47164 \tabularnewline
15 & -0.071457 & -0.4951 & 0.311406 \tabularnewline
16 & -0.11192 & -0.7754 & 0.220952 \tabularnewline
17 & -0.152782 & -1.0585 & 0.147561 \tabularnewline
18 & -0.18087 & -1.2531 & 0.108119 \tabularnewline
19 & -0.231374 & -1.603 & 0.057747 \tabularnewline
20 & -0.282351 & -1.9562 & 0.028138 \tabularnewline
21 & -0.340475 & -2.3589 & 0.011224 \tabularnewline
22 & -0.379333 & -2.6281 & 0.005748 \tabularnewline
23 & -0.402052 & -2.7855 & 0.003814 \tabularnewline
24 & -0.432477 & -2.9963 & 0.002158 \tabularnewline
25 & -0.436914 & -3.027 & 0.001982 \tabularnewline
26 & -0.441071 & -3.0558 & 0.00183 \tabularnewline
27 & -0.424838 & -2.9434 & 0.002495 \tabularnewline
28 & -0.429136 & -2.9731 & 0.0023 \tabularnewline
29 & -0.416523 & -2.8858 & 0.002917 \tabularnewline
30 & -0.39747 & -2.7538 & 0.004148 \tabularnewline
31 & -0.358697 & -2.4851 & 0.008244 \tabularnewline
32 & -0.319045 & -2.2104 & 0.015938 \tabularnewline
33 & -0.272033 & -1.8847 & 0.032767 \tabularnewline
34 & -0.238352 & -1.6514 & 0.052598 \tabularnewline
35 & -0.198721 & -1.3768 & 0.087484 \tabularnewline
36 & -0.137209 & -0.9506 & 0.173282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33950&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]0.920603[/C][C]6.3781[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.864745[/C][C]5.9911[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.788398[/C][C]5.4622[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.730536[/C][C]5.0613[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.661098[/C][C]4.5802[/C][C]1.7e-05[/C][/ROW]
[ROW][C]6[/C][C]0.582253[/C][C]4.034[/C][C]9.8e-05[/C][/ROW]
[ROW][C]7[/C][C]0.50559[/C][C]3.5028[/C][C]0.000503[/C][/ROW]
[ROW][C]8[/C][C]0.420316[/C][C]2.912[/C][C]0.002717[/C][/ROW]
[ROW][C]9[/C][C]0.351954[/C][C]2.4384[/C][C]0.009251[/C][/ROW]
[ROW][C]10[/C][C]0.2598[/C][C]1.7999[/C][C]0.039078[/C][/ROW]
[ROW][C]11[/C][C]0.189781[/C][C]1.3148[/C][C]0.097406[/C][/ROW]
[ROW][C]12[/C][C]0.09747[/C][C]0.6753[/C][C]0.251365[/C][/ROW]
[ROW][C]13[/C][C]0.048063[/C][C]0.333[/C][C]0.370296[/C][/ROW]
[ROW][C]14[/C][C]-0.010323[/C][C]-0.0715[/C][C]0.47164[/C][/ROW]
[ROW][C]15[/C][C]-0.071457[/C][C]-0.4951[/C][C]0.311406[/C][/ROW]
[ROW][C]16[/C][C]-0.11192[/C][C]-0.7754[/C][C]0.220952[/C][/ROW]
[ROW][C]17[/C][C]-0.152782[/C][C]-1.0585[/C][C]0.147561[/C][/ROW]
[ROW][C]18[/C][C]-0.18087[/C][C]-1.2531[/C][C]0.108119[/C][/ROW]
[ROW][C]19[/C][C]-0.231374[/C][C]-1.603[/C][C]0.057747[/C][/ROW]
[ROW][C]20[/C][C]-0.282351[/C][C]-1.9562[/C][C]0.028138[/C][/ROW]
[ROW][C]21[/C][C]-0.340475[/C][C]-2.3589[/C][C]0.011224[/C][/ROW]
[ROW][C]22[/C][C]-0.379333[/C][C]-2.6281[/C][C]0.005748[/C][/ROW]
[ROW][C]23[/C][C]-0.402052[/C][C]-2.7855[/C][C]0.003814[/C][/ROW]
[ROW][C]24[/C][C]-0.432477[/C][C]-2.9963[/C][C]0.002158[/C][/ROW]
[ROW][C]25[/C][C]-0.436914[/C][C]-3.027[/C][C]0.001982[/C][/ROW]
[ROW][C]26[/C][C]-0.441071[/C][C]-3.0558[/C][C]0.00183[/C][/ROW]
[ROW][C]27[/C][C]-0.424838[/C][C]-2.9434[/C][C]0.002495[/C][/ROW]
[ROW][C]28[/C][C]-0.429136[/C][C]-2.9731[/C][C]0.0023[/C][/ROW]
[ROW][C]29[/C][C]-0.416523[/C][C]-2.8858[/C][C]0.002917[/C][/ROW]
[ROW][C]30[/C][C]-0.39747[/C][C]-2.7538[/C][C]0.004148[/C][/ROW]
[ROW][C]31[/C][C]-0.358697[/C][C]-2.4851[/C][C]0.008244[/C][/ROW]
[ROW][C]32[/C][C]-0.319045[/C][C]-2.2104[/C][C]0.015938[/C][/ROW]
[ROW][C]33[/C][C]-0.272033[/C][C]-1.8847[/C][C]0.032767[/C][/ROW]
[ROW][C]34[/C][C]-0.238352[/C][C]-1.6514[/C][C]0.052598[/C][/ROW]
[ROW][C]35[/C][C]-0.198721[/C][C]-1.3768[/C][C]0.087484[/C][/ROW]
[ROW][C]36[/C][C]-0.137209[/C][C]-0.9506[/C][C]0.173282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33950&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
10.9206036.37810
20.8647455.99110
30.7883985.46221e-06
40.7305365.06133e-06
50.6610984.58021.7e-05
60.5822534.0349.8e-05
70.505593.50280.000503
80.4203162.9120.002717
90.3519542.43840.009251
100.25981.79990.039078
110.1897811.31480.097406
120.097470.67530.251365
130.0480630.3330.370296
14-0.010323-0.07150.47164
15-0.071457-0.49510.311406
16-0.11192-0.77540.220952
17-0.152782-1.05850.147561
18-0.18087-1.25310.108119
19-0.231374-1.6030.057747
20-0.282351-1.95620.028138
21-0.340475-2.35890.011224
22-0.379333-2.62810.005748
23-0.402052-2.78550.003814
24-0.432477-2.99630.002158
25-0.436914-3.0270.001982
26-0.441071-3.05580.00183
27-0.424838-2.94340.002495
28-0.429136-2.97310.0023
29-0.416523-2.88580.002917
30-0.39747-2.75380.004148
31-0.358697-2.48510.008244
32-0.319045-2.21040.015938
33-0.272033-1.88470.032767
34-0.238352-1.65140.052598
35-0.198721-1.37680.087484
36-0.137209-0.95060.173282






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9206036.37810
20.1130190.7830.21873
3-0.144558-1.00150.160797
40.0485510.33640.369028
5-0.071635-0.49630.310973
6-0.142615-0.98810.164037
7-0.03346-0.23180.408833
8-0.10057-0.69680.244654
90.0267450.18530.426889
10-0.170813-1.18340.121235
110.0253820.17580.430576
12-0.142308-0.98590.164554
130.1530981.06070.147068
14-0.022747-0.15760.437719
15-0.137709-0.95410.172412
160.1202490.83310.204455
17-0.01519-0.10520.458312
18-0.057662-0.39950.345651
19-0.139265-0.96490.169727
20-0.172692-1.19640.1187
21-0.06727-0.46610.32164
22-0.0516-0.35750.361143
230.1089030.75450.227117
24-0.128866-0.89280.188208
250.1615181.1190.134348
260.0699980.4850.314955
27-0.029124-0.20180.420471
28-0.060312-0.41790.338958
290.0144430.10010.460356
300.0528590.36620.357906
310.0478010.33120.370978
32-0.055645-0.38550.350779
330.0885160.61330.271302
34-0.188624-1.30680.09875
350.1060160.73450.233108
360.0461390.31970.375307

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.920603 & 6.3781 & 0 \tabularnewline
2 & 0.113019 & 0.783 & 0.21873 \tabularnewline
3 & -0.144558 & -1.0015 & 0.160797 \tabularnewline
4 & 0.048551 & 0.3364 & 0.369028 \tabularnewline
5 & -0.071635 & -0.4963 & 0.310973 \tabularnewline
6 & -0.142615 & -0.9881 & 0.164037 \tabularnewline
7 & -0.03346 & -0.2318 & 0.408833 \tabularnewline
8 & -0.10057 & -0.6968 & 0.244654 \tabularnewline
9 & 0.026745 & 0.1853 & 0.426889 \tabularnewline
10 & -0.170813 & -1.1834 & 0.121235 \tabularnewline
11 & 0.025382 & 0.1758 & 0.430576 \tabularnewline
12 & -0.142308 & -0.9859 & 0.164554 \tabularnewline
13 & 0.153098 & 1.0607 & 0.147068 \tabularnewline
14 & -0.022747 & -0.1576 & 0.437719 \tabularnewline
15 & -0.137709 & -0.9541 & 0.172412 \tabularnewline
16 & 0.120249 & 0.8331 & 0.204455 \tabularnewline
17 & -0.01519 & -0.1052 & 0.458312 \tabularnewline
18 & -0.057662 & -0.3995 & 0.345651 \tabularnewline
19 & -0.139265 & -0.9649 & 0.169727 \tabularnewline
20 & -0.172692 & -1.1964 & 0.1187 \tabularnewline
21 & -0.06727 & -0.4661 & 0.32164 \tabularnewline
22 & -0.0516 & -0.3575 & 0.361143 \tabularnewline
23 & 0.108903 & 0.7545 & 0.227117 \tabularnewline
24 & -0.128866 & -0.8928 & 0.188208 \tabularnewline
25 & 0.161518 & 1.119 & 0.134348 \tabularnewline
26 & 0.069998 & 0.485 & 0.314955 \tabularnewline
27 & -0.029124 & -0.2018 & 0.420471 \tabularnewline
28 & -0.060312 & -0.4179 & 0.338958 \tabularnewline
29 & 0.014443 & 0.1001 & 0.460356 \tabularnewline
30 & 0.052859 & 0.3662 & 0.357906 \tabularnewline
31 & 0.047801 & 0.3312 & 0.370978 \tabularnewline
32 & -0.055645 & -0.3855 & 0.350779 \tabularnewline
33 & 0.088516 & 0.6133 & 0.271302 \tabularnewline
34 & -0.188624 & -1.3068 & 0.09875 \tabularnewline
35 & 0.106016 & 0.7345 & 0.233108 \tabularnewline
36 & 0.046139 & 0.3197 & 0.375307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33950&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]0.920603[/C][C]6.3781[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.113019[/C][C]0.783[/C][C]0.21873[/C][/ROW]
[ROW][C]3[/C][C]-0.144558[/C][C]-1.0015[/C][C]0.160797[/C][/ROW]
[ROW][C]4[/C][C]0.048551[/C][C]0.3364[/C][C]0.369028[/C][/ROW]
[ROW][C]5[/C][C]-0.071635[/C][C]-0.4963[/C][C]0.310973[/C][/ROW]
[ROW][C]6[/C][C]-0.142615[/C][C]-0.9881[/C][C]0.164037[/C][/ROW]
[ROW][C]7[/C][C]-0.03346[/C][C]-0.2318[/C][C]0.408833[/C][/ROW]
[ROW][C]8[/C][C]-0.10057[/C][C]-0.6968[/C][C]0.244654[/C][/ROW]
[ROW][C]9[/C][C]0.026745[/C][C]0.1853[/C][C]0.426889[/C][/ROW]
[ROW][C]10[/C][C]-0.170813[/C][C]-1.1834[/C][C]0.121235[/C][/ROW]
[ROW][C]11[/C][C]0.025382[/C][C]0.1758[/C][C]0.430576[/C][/ROW]
[ROW][C]12[/C][C]-0.142308[/C][C]-0.9859[/C][C]0.164554[/C][/ROW]
[ROW][C]13[/C][C]0.153098[/C][C]1.0607[/C][C]0.147068[/C][/ROW]
[ROW][C]14[/C][C]-0.022747[/C][C]-0.1576[/C][C]0.437719[/C][/ROW]
[ROW][C]15[/C][C]-0.137709[/C][C]-0.9541[/C][C]0.172412[/C][/ROW]
[ROW][C]16[/C][C]0.120249[/C][C]0.8331[/C][C]0.204455[/C][/ROW]
[ROW][C]17[/C][C]-0.01519[/C][C]-0.1052[/C][C]0.458312[/C][/ROW]
[ROW][C]18[/C][C]-0.057662[/C][C]-0.3995[/C][C]0.345651[/C][/ROW]
[ROW][C]19[/C][C]-0.139265[/C][C]-0.9649[/C][C]0.169727[/C][/ROW]
[ROW][C]20[/C][C]-0.172692[/C][C]-1.1964[/C][C]0.1187[/C][/ROW]
[ROW][C]21[/C][C]-0.06727[/C][C]-0.4661[/C][C]0.32164[/C][/ROW]
[ROW][C]22[/C][C]-0.0516[/C][C]-0.3575[/C][C]0.361143[/C][/ROW]
[ROW][C]23[/C][C]0.108903[/C][C]0.7545[/C][C]0.227117[/C][/ROW]
[ROW][C]24[/C][C]-0.128866[/C][C]-0.8928[/C][C]0.188208[/C][/ROW]
[ROW][C]25[/C][C]0.161518[/C][C]1.119[/C][C]0.134348[/C][/ROW]
[ROW][C]26[/C][C]0.069998[/C][C]0.485[/C][C]0.314955[/C][/ROW]
[ROW][C]27[/C][C]-0.029124[/C][C]-0.2018[/C][C]0.420471[/C][/ROW]
[ROW][C]28[/C][C]-0.060312[/C][C]-0.4179[/C][C]0.338958[/C][/ROW]
[ROW][C]29[/C][C]0.014443[/C][C]0.1001[/C][C]0.460356[/C][/ROW]
[ROW][C]30[/C][C]0.052859[/C][C]0.3662[/C][C]0.357906[/C][/ROW]
[ROW][C]31[/C][C]0.047801[/C][C]0.3312[/C][C]0.370978[/C][/ROW]
[ROW][C]32[/C][C]-0.055645[/C][C]-0.3855[/C][C]0.350779[/C][/ROW]
[ROW][C]33[/C][C]0.088516[/C][C]0.6133[/C][C]0.271302[/C][/ROW]
[ROW][C]34[/C][C]-0.188624[/C][C]-1.3068[/C][C]0.09875[/C][/ROW]
[ROW][C]35[/C][C]0.106016[/C][C]0.7345[/C][C]0.233108[/C][/ROW]
[ROW][C]36[/C][C]0.046139[/C][C]0.3197[/C][C]0.375307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33950&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
10.9206036.37810
20.1130190.7830.21873
3-0.144558-1.00150.160797
40.0485510.33640.369028
5-0.071635-0.49630.310973
6-0.142615-0.98810.164037
7-0.03346-0.23180.408833
8-0.10057-0.69680.244654
90.0267450.18530.426889
10-0.170813-1.18340.121235
110.0253820.17580.430576
12-0.142308-0.98590.164554
130.1530981.06070.147068
14-0.022747-0.15760.437719
15-0.137709-0.95410.172412
160.1202490.83310.204455
17-0.01519-0.10520.458312
18-0.057662-0.39950.345651
19-0.139265-0.96490.169727
20-0.172692-1.19640.1187
21-0.06727-0.46610.32164
22-0.0516-0.35750.361143
230.1089030.75450.227117
24-0.128866-0.89280.188208
250.1615181.1190.134348
260.0699980.4850.314955
27-0.029124-0.20180.420471
28-0.060312-0.41790.338958
290.0144430.10010.460356
300.0528590.36620.357906
310.0478010.33120.370978
32-0.055645-0.38550.350779
330.0885160.61330.271302
34-0.188624-1.30680.09875
350.1060160.73450.233108
360.0461390.31970.375307


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')