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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 02 Dec 2008 13:23:08 -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/02/t1228249435i4k6wmqtd0efzlt.htm/, Retrieved Sat, 25 May 2024 12:39:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28374, Retrieved Sat, 25 May 2024 12:39:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [(Partial) Autocorrelation Function] [law of averages q...] [2008-12-02 20:23:08] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-09 23:08:33 [Peter Van Doninck] [reply] 
de student zegt dat hij zowel seizoenaliteit als lange termijntrend gezuiverd heeft... Er was in de oorspronkelijke data echter geen lange termijntrend waar te nemen..

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
61,5
88,5
93,3
89,2
101,3
97
102,2
100,3
78,2
105,9
119,9
108
77
93,1
109,5
100,4
99
113,9
102,1
101,6
84
110,7
111,6
110,7
73,1
87,5
109,6
99,3
92,1
109,3
94,5
91,4
82,9
103,3
96
104,8
65,8
78,7
100,3
85
94,5
97,9
91,9
87,2
84,4
99,2
105,4
110,9
69,8
86,8
106,7
88,8
96,9
108,1
93,7
94,8
79,8
95,6
107,9
104,9
61,9
85,7
92,4
86,4
99,3
95,5
97
102,1
77,8
105,5
113,2
108,8
66,9
89,3
93,6
92
99,5
98,6
94,6
96,7
75,3
102,5
115,1
104,7
71,4

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=28374&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=28374&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28374&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
1-0.595441-5.05252e-06
2-0.002026-0.01720.493164
30.3579423.03720.001662
4-0.225373-1.91240.029905
5-0.082765-0.70230.242384
60.3186052.70350.004278
7-0.269097-2.28340.012681
8-0.004941-0.04190.483337
90.2282721.93690.028338
10-0.287119-2.43630.008657
110.1452291.23230.110922
12-0.016-0.13580.446194
13-0.075265-0.63860.26254
140.0088780.07530.470081
150.1096570.93050.177619
16-0.174069-1.4770.072015
170.0875860.74320.229893
180.0851740.72270.236096
19-0.133894-1.13610.129836
200.0440630.37390.354794
210.1301781.10460.136506
22-0.250573-2.12620.018459
230.3017322.56030.006278
24-0.165098-1.40090.08277
25-0.066812-0.56690.286266
260.1409681.19620.117781
27-0.038737-0.32870.37167
28-0.121386-1.030.153231
290.2010241.70570.046183
30-0.186781-1.58490.058687
310.0225130.1910.424522
320.1372211.16440.124061
33-0.194209-1.64790.051863
340.0792150.67220.251816
350.0516880.43860.331136
36-0.091308-0.77480.220504

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.595441 & -5.0525 & 2e-06 \tabularnewline
2 & -0.002026 & -0.0172 & 0.493164 \tabularnewline
3 & 0.357942 & 3.0372 & 0.001662 \tabularnewline
4 & -0.225373 & -1.9124 & 0.029905 \tabularnewline
5 & -0.082765 & -0.7023 & 0.242384 \tabularnewline
6 & 0.318605 & 2.7035 & 0.004278 \tabularnewline
7 & -0.269097 & -2.2834 & 0.012681 \tabularnewline
8 & -0.004941 & -0.0419 & 0.483337 \tabularnewline
9 & 0.228272 & 1.9369 & 0.028338 \tabularnewline
10 & -0.287119 & -2.4363 & 0.008657 \tabularnewline
11 & 0.145229 & 1.2323 & 0.110922 \tabularnewline
12 & -0.016 & -0.1358 & 0.446194 \tabularnewline
13 & -0.075265 & -0.6386 & 0.26254 \tabularnewline
14 & 0.008878 & 0.0753 & 0.470081 \tabularnewline
15 & 0.109657 & 0.9305 & 0.177619 \tabularnewline
16 & -0.174069 & -1.477 & 0.072015 \tabularnewline
17 & 0.087586 & 0.7432 & 0.229893 \tabularnewline
18 & 0.085174 & 0.7227 & 0.236096 \tabularnewline
19 & -0.133894 & -1.1361 & 0.129836 \tabularnewline
20 & 0.044063 & 0.3739 & 0.354794 \tabularnewline
21 & 0.130178 & 1.1046 & 0.136506 \tabularnewline
22 & -0.250573 & -2.1262 & 0.018459 \tabularnewline
23 & 0.301732 & 2.5603 & 0.006278 \tabularnewline
24 & -0.165098 & -1.4009 & 0.08277 \tabularnewline
25 & -0.066812 & -0.5669 & 0.286266 \tabularnewline
26 & 0.140968 & 1.1962 & 0.117781 \tabularnewline
27 & -0.038737 & -0.3287 & 0.37167 \tabularnewline
28 & -0.121386 & -1.03 & 0.153231 \tabularnewline
29 & 0.201024 & 1.7057 & 0.046183 \tabularnewline
30 & -0.186781 & -1.5849 & 0.058687 \tabularnewline
31 & 0.022513 & 0.191 & 0.424522 \tabularnewline
32 & 0.137221 & 1.1644 & 0.124061 \tabularnewline
33 & -0.194209 & -1.6479 & 0.051863 \tabularnewline
34 & 0.079215 & 0.6722 & 0.251816 \tabularnewline
35 & 0.051688 & 0.4386 & 0.331136 \tabularnewline
36 & -0.091308 & -0.7748 & 0.220504 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28374&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]-0.595441[/C][C]-5.0525[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.002026[/C][C]-0.0172[/C][C]0.493164[/C][/ROW]
[ROW][C]3[/C][C]0.357942[/C][C]3.0372[/C][C]0.001662[/C][/ROW]
[ROW][C]4[/C][C]-0.225373[/C][C]-1.9124[/C][C]0.029905[/C][/ROW]
[ROW][C]5[/C][C]-0.082765[/C][C]-0.7023[/C][C]0.242384[/C][/ROW]
[ROW][C]6[/C][C]0.318605[/C][C]2.7035[/C][C]0.004278[/C][/ROW]
[ROW][C]7[/C][C]-0.269097[/C][C]-2.2834[/C][C]0.012681[/C][/ROW]
[ROW][C]8[/C][C]-0.004941[/C][C]-0.0419[/C][C]0.483337[/C][/ROW]
[ROW][C]9[/C][C]0.228272[/C][C]1.9369[/C][C]0.028338[/C][/ROW]
[ROW][C]10[/C][C]-0.287119[/C][C]-2.4363[/C][C]0.008657[/C][/ROW]
[ROW][C]11[/C][C]0.145229[/C][C]1.2323[/C][C]0.110922[/C][/ROW]
[ROW][C]12[/C][C]-0.016[/C][C]-0.1358[/C][C]0.446194[/C][/ROW]
[ROW][C]13[/C][C]-0.075265[/C][C]-0.6386[/C][C]0.26254[/C][/ROW]
[ROW][C]14[/C][C]0.008878[/C][C]0.0753[/C][C]0.470081[/C][/ROW]
[ROW][C]15[/C][C]0.109657[/C][C]0.9305[/C][C]0.177619[/C][/ROW]
[ROW][C]16[/C][C]-0.174069[/C][C]-1.477[/C][C]0.072015[/C][/ROW]
[ROW][C]17[/C][C]0.087586[/C][C]0.7432[/C][C]0.229893[/C][/ROW]
[ROW][C]18[/C][C]0.085174[/C][C]0.7227[/C][C]0.236096[/C][/ROW]
[ROW][C]19[/C][C]-0.133894[/C][C]-1.1361[/C][C]0.129836[/C][/ROW]
[ROW][C]20[/C][C]0.044063[/C][C]0.3739[/C][C]0.354794[/C][/ROW]
[ROW][C]21[/C][C]0.130178[/C][C]1.1046[/C][C]0.136506[/C][/ROW]
[ROW][C]22[/C][C]-0.250573[/C][C]-2.1262[/C][C]0.018459[/C][/ROW]
[ROW][C]23[/C][C]0.301732[/C][C]2.5603[/C][C]0.006278[/C][/ROW]
[ROW][C]24[/C][C]-0.165098[/C][C]-1.4009[/C][C]0.08277[/C][/ROW]
[ROW][C]25[/C][C]-0.066812[/C][C]-0.5669[/C][C]0.286266[/C][/ROW]
[ROW][C]26[/C][C]0.140968[/C][C]1.1962[/C][C]0.117781[/C][/ROW]
[ROW][C]27[/C][C]-0.038737[/C][C]-0.3287[/C][C]0.37167[/C][/ROW]
[ROW][C]28[/C][C]-0.121386[/C][C]-1.03[/C][C]0.153231[/C][/ROW]
[ROW][C]29[/C][C]0.201024[/C][C]1.7057[/C][C]0.046183[/C][/ROW]
[ROW][C]30[/C][C]-0.186781[/C][C]-1.5849[/C][C]0.058687[/C][/ROW]
[ROW][C]31[/C][C]0.022513[/C][C]0.191[/C][C]0.424522[/C][/ROW]
[ROW][C]32[/C][C]0.137221[/C][C]1.1644[/C][C]0.124061[/C][/ROW]
[ROW][C]33[/C][C]-0.194209[/C][C]-1.6479[/C][C]0.051863[/C][/ROW]
[ROW][C]34[/C][C]0.079215[/C][C]0.6722[/C][C]0.251816[/C][/ROW]
[ROW][C]35[/C][C]0.051688[/C][C]0.4386[/C][C]0.331136[/C][/ROW]
[ROW][C]36[/C][C]-0.091308[/C][C]-0.7748[/C][C]0.220504[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28374&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28374&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
1-0.595441-5.05252e-06
2-0.002026-0.01720.493164
30.3579423.03720.001662
4-0.225373-1.91240.029905
5-0.082765-0.70230.242384
60.3186052.70350.004278
7-0.269097-2.28340.012681
8-0.004941-0.04190.483337
90.2282721.93690.028338
10-0.287119-2.43630.008657
110.1452291.23230.110922
12-0.016-0.13580.446194
13-0.075265-0.63860.26254
140.0088780.07530.470081
150.1096570.93050.177619
16-0.174069-1.4770.072015
170.0875860.74320.229893
180.0851740.72270.236096
19-0.133894-1.13610.129836
200.0440630.37390.354794
210.1301781.10460.136506
22-0.250573-2.12620.018459
230.3017322.56030.006278
24-0.165098-1.40090.08277
25-0.066812-0.56690.286266
260.1409681.19620.117781
27-0.038737-0.32870.37167
28-0.121386-1.030.153231
290.2010241.70570.046183
30-0.186781-1.58490.058687
310.0225130.1910.424522
320.1372211.16440.124061
33-0.194209-1.64790.051863
340.0792150.67220.251816
350.0516880.43860.331136
36-0.091308-0.77480.220504






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.595441-5.05252e-06
2-0.552446-4.68776e-06
30.0604730.51310.304715
40.2876972.44120.008549
50.0269870.2290.409761
60.1490171.26440.105073
70.0270140.22920.409672
8-0.162518-1.3790.08608
9-0.066186-0.56160.288064
10-0.181329-1.53860.064139
11-0.006448-0.05470.47826
12-0.117913-1.00050.160204
13-0.050241-0.42630.335577
14-0.090448-0.76750.222654
150.0749160.63570.263499
160.0718320.60950.272052
17-0.023706-0.20120.420573
180.1082240.91830.180761
190.1288571.09340.138934
20-0.031917-0.27080.393652
210.0586440.49760.310136
22-0.242841-2.06060.021479
230.1944271.64980.051673
240.0055160.04680.481401
25-0.085644-0.72670.234878
26-0.224629-1.9060.030319
27-0.099477-0.84410.200707
280.0433180.36760.357138
290.1545571.31150.096934
30-0.014289-0.12120.451918
310.01760.14930.440852
32-0.041494-0.35210.362902
330.015030.12750.449436
34-0.139896-1.18710.119553
350.0205610.17450.430993
36-0.0161-0.13660.44586

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.595441 & -5.0525 & 2e-06 \tabularnewline
2 & -0.552446 & -4.6877 & 6e-06 \tabularnewline
3 & 0.060473 & 0.5131 & 0.304715 \tabularnewline
4 & 0.287697 & 2.4412 & 0.008549 \tabularnewline
5 & 0.026987 & 0.229 & 0.409761 \tabularnewline
6 & 0.149017 & 1.2644 & 0.105073 \tabularnewline
7 & 0.027014 & 0.2292 & 0.409672 \tabularnewline
8 & -0.162518 & -1.379 & 0.08608 \tabularnewline
9 & -0.066186 & -0.5616 & 0.288064 \tabularnewline
10 & -0.181329 & -1.5386 & 0.064139 \tabularnewline
11 & -0.006448 & -0.0547 & 0.47826 \tabularnewline
12 & -0.117913 & -1.0005 & 0.160204 \tabularnewline
13 & -0.050241 & -0.4263 & 0.335577 \tabularnewline
14 & -0.090448 & -0.7675 & 0.222654 \tabularnewline
15 & 0.074916 & 0.6357 & 0.263499 \tabularnewline
16 & 0.071832 & 0.6095 & 0.272052 \tabularnewline
17 & -0.023706 & -0.2012 & 0.420573 \tabularnewline
18 & 0.108224 & 0.9183 & 0.180761 \tabularnewline
19 & 0.128857 & 1.0934 & 0.138934 \tabularnewline
20 & -0.031917 & -0.2708 & 0.393652 \tabularnewline
21 & 0.058644 & 0.4976 & 0.310136 \tabularnewline
22 & -0.242841 & -2.0606 & 0.021479 \tabularnewline
23 & 0.194427 & 1.6498 & 0.051673 \tabularnewline
24 & 0.005516 & 0.0468 & 0.481401 \tabularnewline
25 & -0.085644 & -0.7267 & 0.234878 \tabularnewline
26 & -0.224629 & -1.906 & 0.030319 \tabularnewline
27 & -0.099477 & -0.8441 & 0.200707 \tabularnewline
28 & 0.043318 & 0.3676 & 0.357138 \tabularnewline
29 & 0.154557 & 1.3115 & 0.096934 \tabularnewline
30 & -0.014289 & -0.1212 & 0.451918 \tabularnewline
31 & 0.0176 & 0.1493 & 0.440852 \tabularnewline
32 & -0.041494 & -0.3521 & 0.362902 \tabularnewline
33 & 0.01503 & 0.1275 & 0.449436 \tabularnewline
34 & -0.139896 & -1.1871 & 0.119553 \tabularnewline
35 & 0.020561 & 0.1745 & 0.430993 \tabularnewline
36 & -0.0161 & -0.1366 & 0.44586 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28374&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]-0.595441[/C][C]-5.0525[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.552446[/C][C]-4.6877[/C][C]6e-06[/C][/ROW]
[ROW][C]3[/C][C]0.060473[/C][C]0.5131[/C][C]0.304715[/C][/ROW]
[ROW][C]4[/C][C]0.287697[/C][C]2.4412[/C][C]0.008549[/C][/ROW]
[ROW][C]5[/C][C]0.026987[/C][C]0.229[/C][C]0.409761[/C][/ROW]
[ROW][C]6[/C][C]0.149017[/C][C]1.2644[/C][C]0.105073[/C][/ROW]
[ROW][C]7[/C][C]0.027014[/C][C]0.2292[/C][C]0.409672[/C][/ROW]
[ROW][C]8[/C][C]-0.162518[/C][C]-1.379[/C][C]0.08608[/C][/ROW]
[ROW][C]9[/C][C]-0.066186[/C][C]-0.5616[/C][C]0.288064[/C][/ROW]
[ROW][C]10[/C][C]-0.181329[/C][C]-1.5386[/C][C]0.064139[/C][/ROW]
[ROW][C]11[/C][C]-0.006448[/C][C]-0.0547[/C][C]0.47826[/C][/ROW]
[ROW][C]12[/C][C]-0.117913[/C][C]-1.0005[/C][C]0.160204[/C][/ROW]
[ROW][C]13[/C][C]-0.050241[/C][C]-0.4263[/C][C]0.335577[/C][/ROW]
[ROW][C]14[/C][C]-0.090448[/C][C]-0.7675[/C][C]0.222654[/C][/ROW]
[ROW][C]15[/C][C]0.074916[/C][C]0.6357[/C][C]0.263499[/C][/ROW]
[ROW][C]16[/C][C]0.071832[/C][C]0.6095[/C][C]0.272052[/C][/ROW]
[ROW][C]17[/C][C]-0.023706[/C][C]-0.2012[/C][C]0.420573[/C][/ROW]
[ROW][C]18[/C][C]0.108224[/C][C]0.9183[/C][C]0.180761[/C][/ROW]
[ROW][C]19[/C][C]0.128857[/C][C]1.0934[/C][C]0.138934[/C][/ROW]
[ROW][C]20[/C][C]-0.031917[/C][C]-0.2708[/C][C]0.393652[/C][/ROW]
[ROW][C]21[/C][C]0.058644[/C][C]0.4976[/C][C]0.310136[/C][/ROW]
[ROW][C]22[/C][C]-0.242841[/C][C]-2.0606[/C][C]0.021479[/C][/ROW]
[ROW][C]23[/C][C]0.194427[/C][C]1.6498[/C][C]0.051673[/C][/ROW]
[ROW][C]24[/C][C]0.005516[/C][C]0.0468[/C][C]0.481401[/C][/ROW]
[ROW][C]25[/C][C]-0.085644[/C][C]-0.7267[/C][C]0.234878[/C][/ROW]
[ROW][C]26[/C][C]-0.224629[/C][C]-1.906[/C][C]0.030319[/C][/ROW]
[ROW][C]27[/C][C]-0.099477[/C][C]-0.8441[/C][C]0.200707[/C][/ROW]
[ROW][C]28[/C][C]0.043318[/C][C]0.3676[/C][C]0.357138[/C][/ROW]
[ROW][C]29[/C][C]0.154557[/C][C]1.3115[/C][C]0.096934[/C][/ROW]
[ROW][C]30[/C][C]-0.014289[/C][C]-0.1212[/C][C]0.451918[/C][/ROW]
[ROW][C]31[/C][C]0.0176[/C][C]0.1493[/C][C]0.440852[/C][/ROW]
[ROW][C]32[/C][C]-0.041494[/C][C]-0.3521[/C][C]0.362902[/C][/ROW]
[ROW][C]33[/C][C]0.01503[/C][C]0.1275[/C][C]0.449436[/C][/ROW]
[ROW][C]34[/C][C]-0.139896[/C][C]-1.1871[/C][C]0.119553[/C][/ROW]
[ROW][C]35[/C][C]0.020561[/C][C]0.1745[/C][C]0.430993[/C][/ROW]
[ROW][C]36[/C][C]-0.0161[/C][C]-0.1366[/C][C]0.44586[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28374&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28374&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
1-0.595441-5.05252e-06
2-0.552446-4.68776e-06
30.0604730.51310.304715
40.2876972.44120.008549
50.0269870.2290.409761
60.1490171.26440.105073
70.0270140.22920.409672
8-0.162518-1.3790.08608
9-0.066186-0.56160.288064
10-0.181329-1.53860.064139
11-0.006448-0.05470.47826
12-0.117913-1.00050.160204
13-0.050241-0.42630.335577
14-0.090448-0.76750.222654
150.0749160.63570.263499
160.0718320.60950.272052
17-0.023706-0.20120.420573
180.1082240.91830.180761
190.1288571.09340.138934
20-0.031917-0.27080.393652
210.0586440.49760.310136
22-0.242841-2.06060.021479
230.1944271.64980.051673
240.0055160.04680.481401
25-0.085644-0.72670.234878
26-0.224629-1.9060.030319
27-0.099477-0.84410.200707
280.0433180.36760.357138
290.1545571.31150.096934
30-0.014289-0.12120.451918
310.01760.14930.440852
32-0.041494-0.35210.362902
330.015030.12750.449436
34-0.139896-1.18710.119553
350.0205610.17450.430993
36-0.0161-0.13660.44586


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')