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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, 27 Nov 2009 05:44:42 -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/t1259325933i5tfkspq3l90ps2.htm/, Retrieved Mon, 29 Apr 2024 17:58:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60667, Retrieved Mon, 29 Apr 2024 17:58:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [WS7] [2009-11-27 12:44:42] [40cfc51151e9382b81a5fb0c269b074d] [Current]
-   P             [(Partial) Autocorrelation Function] [verbetering ] [2009-12-04 12:59:34] [7d268329e554b8694908ba13e6e6f258]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
295881
293299

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=60667&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=60667&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60667&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
10.8798856.87210
20.7364055.75150
30.6336094.94863e-06
40.5825724.551.3e-05
50.5623054.39172.3e-05
60.5086983.97319.5e-05
70.4132433.22750.001005
80.3047052.37980.010231
90.2380081.85890.033933
100.2208331.72480.044817
110.2343211.83010.036061
120.221331.72860.044466
130.0843160.65850.256338
14-0.047453-0.37060.356103
15-0.138889-1.08480.141149
16-0.172079-1.3440.091966
17-0.170623-1.33260.093808
18-0.199405-1.55740.062274
19-0.249829-1.95120.027814
20-0.31694-2.47540.008051
21-0.344807-2.6930.004565
22-0.325147-2.53950.006833
23-0.283614-2.21510.015249
24-0.26933-2.10350.019775
25-0.343946-2.68630.004648
26-0.400839-3.13070.001338
27-0.415567-3.24570.000952
28-0.372612-2.91020.002518
29-0.329791-2.57570.00622
30-0.303628-2.37140.010447
31-0.288693-2.25480.013874
32-0.291271-2.27490.01322
33-0.2597-2.02830.02345
34-0.184371-1.440.077492
35-0.122274-0.9550.171676
36-0.092354-0.72130.236739

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.879885 & 6.8721 & 0 \tabularnewline
2 & 0.736405 & 5.7515 & 0 \tabularnewline
3 & 0.633609 & 4.9486 & 3e-06 \tabularnewline
4 & 0.582572 & 4.55 & 1.3e-05 \tabularnewline
5 & 0.562305 & 4.3917 & 2.3e-05 \tabularnewline
6 & 0.508698 & 3.9731 & 9.5e-05 \tabularnewline
7 & 0.413243 & 3.2275 & 0.001005 \tabularnewline
8 & 0.304705 & 2.3798 & 0.010231 \tabularnewline
9 & 0.238008 & 1.8589 & 0.033933 \tabularnewline
10 & 0.220833 & 1.7248 & 0.044817 \tabularnewline
11 & 0.234321 & 1.8301 & 0.036061 \tabularnewline
12 & 0.22133 & 1.7286 & 0.044466 \tabularnewline
13 & 0.084316 & 0.6585 & 0.256338 \tabularnewline
14 & -0.047453 & -0.3706 & 0.356103 \tabularnewline
15 & -0.138889 & -1.0848 & 0.141149 \tabularnewline
16 & -0.172079 & -1.344 & 0.091966 \tabularnewline
17 & -0.170623 & -1.3326 & 0.093808 \tabularnewline
18 & -0.199405 & -1.5574 & 0.062274 \tabularnewline
19 & -0.249829 & -1.9512 & 0.027814 \tabularnewline
20 & -0.31694 & -2.4754 & 0.008051 \tabularnewline
21 & -0.344807 & -2.693 & 0.004565 \tabularnewline
22 & -0.325147 & -2.5395 & 0.006833 \tabularnewline
23 & -0.283614 & -2.2151 & 0.015249 \tabularnewline
24 & -0.26933 & -2.1035 & 0.019775 \tabularnewline
25 & -0.343946 & -2.6863 & 0.004648 \tabularnewline
26 & -0.400839 & -3.1307 & 0.001338 \tabularnewline
27 & -0.415567 & -3.2457 & 0.000952 \tabularnewline
28 & -0.372612 & -2.9102 & 0.002518 \tabularnewline
29 & -0.329791 & -2.5757 & 0.00622 \tabularnewline
30 & -0.303628 & -2.3714 & 0.010447 \tabularnewline
31 & -0.288693 & -2.2548 & 0.013874 \tabularnewline
32 & -0.291271 & -2.2749 & 0.01322 \tabularnewline
33 & -0.2597 & -2.0283 & 0.02345 \tabularnewline
34 & -0.184371 & -1.44 & 0.077492 \tabularnewline
35 & -0.122274 & -0.955 & 0.171676 \tabularnewline
36 & -0.092354 & -0.7213 & 0.236739 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60667&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]0.879885[/C][C]6.8721[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.736405[/C][C]5.7515[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.633609[/C][C]4.9486[/C][C]3e-06[/C][/ROW]
[ROW][C]4[/C][C]0.582572[/C][C]4.55[/C][C]1.3e-05[/C][/ROW]
[ROW][C]5[/C][C]0.562305[/C][C]4.3917[/C][C]2.3e-05[/C][/ROW]
[ROW][C]6[/C][C]0.508698[/C][C]3.9731[/C][C]9.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.413243[/C][C]3.2275[/C][C]0.001005[/C][/ROW]
[ROW][C]8[/C][C]0.304705[/C][C]2.3798[/C][C]0.010231[/C][/ROW]
[ROW][C]9[/C][C]0.238008[/C][C]1.8589[/C][C]0.033933[/C][/ROW]
[ROW][C]10[/C][C]0.220833[/C][C]1.7248[/C][C]0.044817[/C][/ROW]
[ROW][C]11[/C][C]0.234321[/C][C]1.8301[/C][C]0.036061[/C][/ROW]
[ROW][C]12[/C][C]0.22133[/C][C]1.7286[/C][C]0.044466[/C][/ROW]
[ROW][C]13[/C][C]0.084316[/C][C]0.6585[/C][C]0.256338[/C][/ROW]
[ROW][C]14[/C][C]-0.047453[/C][C]-0.3706[/C][C]0.356103[/C][/ROW]
[ROW][C]15[/C][C]-0.138889[/C][C]-1.0848[/C][C]0.141149[/C][/ROW]
[ROW][C]16[/C][C]-0.172079[/C][C]-1.344[/C][C]0.091966[/C][/ROW]
[ROW][C]17[/C][C]-0.170623[/C][C]-1.3326[/C][C]0.093808[/C][/ROW]
[ROW][C]18[/C][C]-0.199405[/C][C]-1.5574[/C][C]0.062274[/C][/ROW]
[ROW][C]19[/C][C]-0.249829[/C][C]-1.9512[/C][C]0.027814[/C][/ROW]
[ROW][C]20[/C][C]-0.31694[/C][C]-2.4754[/C][C]0.008051[/C][/ROW]
[ROW][C]21[/C][C]-0.344807[/C][C]-2.693[/C][C]0.004565[/C][/ROW]
[ROW][C]22[/C][C]-0.325147[/C][C]-2.5395[/C][C]0.006833[/C][/ROW]
[ROW][C]23[/C][C]-0.283614[/C][C]-2.2151[/C][C]0.015249[/C][/ROW]
[ROW][C]24[/C][C]-0.26933[/C][C]-2.1035[/C][C]0.019775[/C][/ROW]
[ROW][C]25[/C][C]-0.343946[/C][C]-2.6863[/C][C]0.004648[/C][/ROW]
[ROW][C]26[/C][C]-0.400839[/C][C]-3.1307[/C][C]0.001338[/C][/ROW]
[ROW][C]27[/C][C]-0.415567[/C][C]-3.2457[/C][C]0.000952[/C][/ROW]
[ROW][C]28[/C][C]-0.372612[/C][C]-2.9102[/C][C]0.002518[/C][/ROW]
[ROW][C]29[/C][C]-0.329791[/C][C]-2.5757[/C][C]0.00622[/C][/ROW]
[ROW][C]30[/C][C]-0.303628[/C][C]-2.3714[/C][C]0.010447[/C][/ROW]
[ROW][C]31[/C][C]-0.288693[/C][C]-2.2548[/C][C]0.013874[/C][/ROW]
[ROW][C]32[/C][C]-0.291271[/C][C]-2.2749[/C][C]0.01322[/C][/ROW]
[ROW][C]33[/C][C]-0.2597[/C][C]-2.0283[/C][C]0.02345[/C][/ROW]
[ROW][C]34[/C][C]-0.184371[/C][C]-1.44[/C][C]0.077492[/C][/ROW]
[ROW][C]35[/C][C]-0.122274[/C][C]-0.955[/C][C]0.171676[/C][/ROW]
[ROW][C]36[/C][C]-0.092354[/C][C]-0.7213[/C][C]0.236739[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60667&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60667&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
10.8798856.87210
20.7364055.75150
30.6336094.94863e-06
40.5825724.551.3e-05
50.5623054.39172.3e-05
60.5086983.97319.5e-05
70.4132433.22750.001005
80.3047052.37980.010231
90.2380081.85890.033933
100.2208331.72480.044817
110.2343211.83010.036061
120.221331.72860.044466
130.0843160.65850.256338
14-0.047453-0.37060.356103
15-0.138889-1.08480.141149
16-0.172079-1.3440.091966
17-0.170623-1.33260.093808
18-0.199405-1.55740.062274
19-0.249829-1.95120.027814
20-0.31694-2.47540.008051
21-0.344807-2.6930.004565
22-0.325147-2.53950.006833
23-0.283614-2.21510.015249
24-0.26933-2.10350.019775
25-0.343946-2.68630.004648
26-0.400839-3.13070.001338
27-0.415567-3.24570.000952
28-0.372612-2.91020.002518
29-0.329791-2.57570.00622
30-0.303628-2.37140.010447
31-0.288693-2.25480.013874
32-0.291271-2.27490.01322
33-0.2597-2.02830.02345
34-0.184371-1.440.077492
35-0.122274-0.9550.171676
36-0.092354-0.72130.236739






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8798856.87210
2-0.16737-1.30720.098025
30.111520.8710.193586
40.1357111.05990.146676
50.0903660.70580.241506
6-0.138198-1.07940.142338
7-0.134922-1.05380.148072
8-0.089469-0.69880.243675
90.0711570.55580.290205
100.0720240.56250.28791
110.1024870.80040.213279
12-0.053171-0.41530.339698
13-0.490726-3.83270.000151
140.0301090.23520.407436
15-0.078537-0.61340.270948
160.0314170.24540.403494
170.0466330.36420.358477
18-0.010401-0.08120.467761
190.0536080.41870.338455
20-0.124483-0.97220.167384
21-0.013033-0.10180.459627
22-0.007704-0.06020.476108
23-0.009697-0.07570.469937
24-0.022223-0.17360.431391
25-0.137941-1.07740.142782
260.0557950.43580.332269
270.0033630.02630.489566
280.0439170.3430.366387
29-0.148171-1.15730.125841
300.127250.99390.16211
310.0171440.13390.44696
32-0.026704-0.20860.417741
330.009850.07690.469465
340.0850230.6640.25458
35-0.139836-1.09220.139531
36-0.021184-0.16550.434567

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.879885 & 6.8721 & 0 \tabularnewline
2 & -0.16737 & -1.3072 & 0.098025 \tabularnewline
3 & 0.11152 & 0.871 & 0.193586 \tabularnewline
4 & 0.135711 & 1.0599 & 0.146676 \tabularnewline
5 & 0.090366 & 0.7058 & 0.241506 \tabularnewline
6 & -0.138198 & -1.0794 & 0.142338 \tabularnewline
7 & -0.134922 & -1.0538 & 0.148072 \tabularnewline
8 & -0.089469 & -0.6988 & 0.243675 \tabularnewline
9 & 0.071157 & 0.5558 & 0.290205 \tabularnewline
10 & 0.072024 & 0.5625 & 0.28791 \tabularnewline
11 & 0.102487 & 0.8004 & 0.213279 \tabularnewline
12 & -0.053171 & -0.4153 & 0.339698 \tabularnewline
13 & -0.490726 & -3.8327 & 0.000151 \tabularnewline
14 & 0.030109 & 0.2352 & 0.407436 \tabularnewline
15 & -0.078537 & -0.6134 & 0.270948 \tabularnewline
16 & 0.031417 & 0.2454 & 0.403494 \tabularnewline
17 & 0.046633 & 0.3642 & 0.358477 \tabularnewline
18 & -0.010401 & -0.0812 & 0.467761 \tabularnewline
19 & 0.053608 & 0.4187 & 0.338455 \tabularnewline
20 & -0.124483 & -0.9722 & 0.167384 \tabularnewline
21 & -0.013033 & -0.1018 & 0.459627 \tabularnewline
22 & -0.007704 & -0.0602 & 0.476108 \tabularnewline
23 & -0.009697 & -0.0757 & 0.469937 \tabularnewline
24 & -0.022223 & -0.1736 & 0.431391 \tabularnewline
25 & -0.137941 & -1.0774 & 0.142782 \tabularnewline
26 & 0.055795 & 0.4358 & 0.332269 \tabularnewline
27 & 0.003363 & 0.0263 & 0.489566 \tabularnewline
28 & 0.043917 & 0.343 & 0.366387 \tabularnewline
29 & -0.148171 & -1.1573 & 0.125841 \tabularnewline
30 & 0.12725 & 0.9939 & 0.16211 \tabularnewline
31 & 0.017144 & 0.1339 & 0.44696 \tabularnewline
32 & -0.026704 & -0.2086 & 0.417741 \tabularnewline
33 & 0.00985 & 0.0769 & 0.469465 \tabularnewline
34 & 0.085023 & 0.664 & 0.25458 \tabularnewline
35 & -0.139836 & -1.0922 & 0.139531 \tabularnewline
36 & -0.021184 & -0.1655 & 0.434567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60667&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]0.879885[/C][C]6.8721[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.16737[/C][C]-1.3072[/C][C]0.098025[/C][/ROW]
[ROW][C]3[/C][C]0.11152[/C][C]0.871[/C][C]0.193586[/C][/ROW]
[ROW][C]4[/C][C]0.135711[/C][C]1.0599[/C][C]0.146676[/C][/ROW]
[ROW][C]5[/C][C]0.090366[/C][C]0.7058[/C][C]0.241506[/C][/ROW]
[ROW][C]6[/C][C]-0.138198[/C][C]-1.0794[/C][C]0.142338[/C][/ROW]
[ROW][C]7[/C][C]-0.134922[/C][C]-1.0538[/C][C]0.148072[/C][/ROW]
[ROW][C]8[/C][C]-0.089469[/C][C]-0.6988[/C][C]0.243675[/C][/ROW]
[ROW][C]9[/C][C]0.071157[/C][C]0.5558[/C][C]0.290205[/C][/ROW]
[ROW][C]10[/C][C]0.072024[/C][C]0.5625[/C][C]0.28791[/C][/ROW]
[ROW][C]11[/C][C]0.102487[/C][C]0.8004[/C][C]0.213279[/C][/ROW]
[ROW][C]12[/C][C]-0.053171[/C][C]-0.4153[/C][C]0.339698[/C][/ROW]
[ROW][C]13[/C][C]-0.490726[/C][C]-3.8327[/C][C]0.000151[/C][/ROW]
[ROW][C]14[/C][C]0.030109[/C][C]0.2352[/C][C]0.407436[/C][/ROW]
[ROW][C]15[/C][C]-0.078537[/C][C]-0.6134[/C][C]0.270948[/C][/ROW]
[ROW][C]16[/C][C]0.031417[/C][C]0.2454[/C][C]0.403494[/C][/ROW]
[ROW][C]17[/C][C]0.046633[/C][C]0.3642[/C][C]0.358477[/C][/ROW]
[ROW][C]18[/C][C]-0.010401[/C][C]-0.0812[/C][C]0.467761[/C][/ROW]
[ROW][C]19[/C][C]0.053608[/C][C]0.4187[/C][C]0.338455[/C][/ROW]
[ROW][C]20[/C][C]-0.124483[/C][C]-0.9722[/C][C]0.167384[/C][/ROW]
[ROW][C]21[/C][C]-0.013033[/C][C]-0.1018[/C][C]0.459627[/C][/ROW]
[ROW][C]22[/C][C]-0.007704[/C][C]-0.0602[/C][C]0.476108[/C][/ROW]
[ROW][C]23[/C][C]-0.009697[/C][C]-0.0757[/C][C]0.469937[/C][/ROW]
[ROW][C]24[/C][C]-0.022223[/C][C]-0.1736[/C][C]0.431391[/C][/ROW]
[ROW][C]25[/C][C]-0.137941[/C][C]-1.0774[/C][C]0.142782[/C][/ROW]
[ROW][C]26[/C][C]0.055795[/C][C]0.4358[/C][C]0.332269[/C][/ROW]
[ROW][C]27[/C][C]0.003363[/C][C]0.0263[/C][C]0.489566[/C][/ROW]
[ROW][C]28[/C][C]0.043917[/C][C]0.343[/C][C]0.366387[/C][/ROW]
[ROW][C]29[/C][C]-0.148171[/C][C]-1.1573[/C][C]0.125841[/C][/ROW]
[ROW][C]30[/C][C]0.12725[/C][C]0.9939[/C][C]0.16211[/C][/ROW]
[ROW][C]31[/C][C]0.017144[/C][C]0.1339[/C][C]0.44696[/C][/ROW]
[ROW][C]32[/C][C]-0.026704[/C][C]-0.2086[/C][C]0.417741[/C][/ROW]
[ROW][C]33[/C][C]0.00985[/C][C]0.0769[/C][C]0.469465[/C][/ROW]
[ROW][C]34[/C][C]0.085023[/C][C]0.664[/C][C]0.25458[/C][/ROW]
[ROW][C]35[/C][C]-0.139836[/C][C]-1.0922[/C][C]0.139531[/C][/ROW]
[ROW][C]36[/C][C]-0.021184[/C][C]-0.1655[/C][C]0.434567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60667&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60667&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
10.8798856.87210
2-0.16737-1.30720.098025
30.111520.8710.193586
40.1357111.05990.146676
50.0903660.70580.241506
6-0.138198-1.07940.142338
7-0.134922-1.05380.148072
8-0.089469-0.69880.243675
90.0711570.55580.290205
100.0720240.56250.28791
110.1024870.80040.213279
12-0.053171-0.41530.339698
13-0.490726-3.83270.000151
140.0301090.23520.407436
15-0.078537-0.61340.270948
160.0314170.24540.403494
170.0466330.36420.358477
18-0.010401-0.08120.467761
190.0536080.41870.338455
20-0.124483-0.97220.167384
21-0.013033-0.10180.459627
22-0.007704-0.06020.476108
23-0.009697-0.07570.469937
24-0.022223-0.17360.431391
25-0.137941-1.07740.142782
260.0557950.43580.332269
270.0033630.02630.489566
280.0439170.3430.366387
29-0.148171-1.15730.125841
300.127250.99390.16211
310.0171440.13390.44696
32-0.026704-0.20860.417741
330.009850.07690.469465
340.0850230.6640.25458
35-0.139836-1.09220.139531
36-0.021184-0.16550.434567


Figures (Output of Computation)

Input Parameters & R Code

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 ;
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')