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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 computationMon, 07 Dec 2009 12:26:08 -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/2009/Dec/07/t1260214017sdrmosqggsfi4lx.htm/, Retrieved Sat, 04 May 2024 21:45:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64615, Retrieved Sat, 04 May 2024 21:45:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

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 12:26:39] [b98453cac15ba1066b407e146608df68]
F    D        [(Partial) Autocorrelation Function] [WS 8: ACF 3, D=1 ...] [2009-11-27 13:09:29] [b97b96148b0223bc16666763988dc147]
-   P             [(Partial) Autocorrelation Function] [lambda = -0,7] [2009-12-07 19:26:08] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107

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=64615&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=64615&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64615&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
1-0.008526-0.05850.476817
20.0245090.1680.433642
30.1235850.84730.200574
40.140680.96450.169877
50.0166520.11420.454798
60.1983731.360.090163
70.075370.51670.303891
80.0523230.35870.360709
90.0503230.3450.365817
10-0.1749-1.19910.118258
110.3631642.48970.008189
12-0.127746-0.87580.192801
13-0.088282-0.60520.273968
140.0185940.12750.449553
150.1342740.92050.180996
16-0.090846-0.62280.26821
170.1209010.82890.205688
18-0.0855-0.58620.280287
19-0.072323-0.49580.311165
200.0240010.16450.435005
21-0.164509-1.12780.132562
22-0.04145-0.28420.388766
23-0.133478-0.91510.182411
24-0.097383-0.66760.253818
25-0.091395-0.62660.266985
260.0332660.22810.410294
27-0.097618-0.66920.253309
28-0.106478-0.730.234515
29-0.109761-0.75250.227756
30-0.078507-0.53820.296484
31-0.026955-0.18480.427094
32-0.046053-0.31570.376805
330.013710.0940.462759
34-0.012804-0.08780.465212
35-0.003101-0.02130.491564
36-0.054791-0.37560.354443

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.008526 & -0.0585 & 0.476817 \tabularnewline
2 & 0.024509 & 0.168 & 0.433642 \tabularnewline
3 & 0.123585 & 0.8473 & 0.200574 \tabularnewline
4 & 0.14068 & 0.9645 & 0.169877 \tabularnewline
5 & 0.016652 & 0.1142 & 0.454798 \tabularnewline
6 & 0.198373 & 1.36 & 0.090163 \tabularnewline
7 & 0.07537 & 0.5167 & 0.303891 \tabularnewline
8 & 0.052323 & 0.3587 & 0.360709 \tabularnewline
9 & 0.050323 & 0.345 & 0.365817 \tabularnewline
10 & -0.1749 & -1.1991 & 0.118258 \tabularnewline
11 & 0.363164 & 2.4897 & 0.008189 \tabularnewline
12 & -0.127746 & -0.8758 & 0.192801 \tabularnewline
13 & -0.088282 & -0.6052 & 0.273968 \tabularnewline
14 & 0.018594 & 0.1275 & 0.449553 \tabularnewline
15 & 0.134274 & 0.9205 & 0.180996 \tabularnewline
16 & -0.090846 & -0.6228 & 0.26821 \tabularnewline
17 & 0.120901 & 0.8289 & 0.205688 \tabularnewline
18 & -0.0855 & -0.5862 & 0.280287 \tabularnewline
19 & -0.072323 & -0.4958 & 0.311165 \tabularnewline
20 & 0.024001 & 0.1645 & 0.435005 \tabularnewline
21 & -0.164509 & -1.1278 & 0.132562 \tabularnewline
22 & -0.04145 & -0.2842 & 0.388766 \tabularnewline
23 & -0.133478 & -0.9151 & 0.182411 \tabularnewline
24 & -0.097383 & -0.6676 & 0.253818 \tabularnewline
25 & -0.091395 & -0.6266 & 0.266985 \tabularnewline
26 & 0.033266 & 0.2281 & 0.410294 \tabularnewline
27 & -0.097618 & -0.6692 & 0.253309 \tabularnewline
28 & -0.106478 & -0.73 & 0.234515 \tabularnewline
29 & -0.109761 & -0.7525 & 0.227756 \tabularnewline
30 & -0.078507 & -0.5382 & 0.296484 \tabularnewline
31 & -0.026955 & -0.1848 & 0.427094 \tabularnewline
32 & -0.046053 & -0.3157 & 0.376805 \tabularnewline
33 & 0.01371 & 0.094 & 0.462759 \tabularnewline
34 & -0.012804 & -0.0878 & 0.465212 \tabularnewline
35 & -0.003101 & -0.0213 & 0.491564 \tabularnewline
36 & -0.054791 & -0.3756 & 0.354443 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64615&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]-0.008526[/C][C]-0.0585[/C][C]0.476817[/C][/ROW]
[ROW][C]2[/C][C]0.024509[/C][C]0.168[/C][C]0.433642[/C][/ROW]
[ROW][C]3[/C][C]0.123585[/C][C]0.8473[/C][C]0.200574[/C][/ROW]
[ROW][C]4[/C][C]0.14068[/C][C]0.9645[/C][C]0.169877[/C][/ROW]
[ROW][C]5[/C][C]0.016652[/C][C]0.1142[/C][C]0.454798[/C][/ROW]
[ROW][C]6[/C][C]0.198373[/C][C]1.36[/C][C]0.090163[/C][/ROW]
[ROW][C]7[/C][C]0.07537[/C][C]0.5167[/C][C]0.303891[/C][/ROW]
[ROW][C]8[/C][C]0.052323[/C][C]0.3587[/C][C]0.360709[/C][/ROW]
[ROW][C]9[/C][C]0.050323[/C][C]0.345[/C][C]0.365817[/C][/ROW]
[ROW][C]10[/C][C]-0.1749[/C][C]-1.1991[/C][C]0.118258[/C][/ROW]
[ROW][C]11[/C][C]0.363164[/C][C]2.4897[/C][C]0.008189[/C][/ROW]
[ROW][C]12[/C][C]-0.127746[/C][C]-0.8758[/C][C]0.192801[/C][/ROW]
[ROW][C]13[/C][C]-0.088282[/C][C]-0.6052[/C][C]0.273968[/C][/ROW]
[ROW][C]14[/C][C]0.018594[/C][C]0.1275[/C][C]0.449553[/C][/ROW]
[ROW][C]15[/C][C]0.134274[/C][C]0.9205[/C][C]0.180996[/C][/ROW]
[ROW][C]16[/C][C]-0.090846[/C][C]-0.6228[/C][C]0.26821[/C][/ROW]
[ROW][C]17[/C][C]0.120901[/C][C]0.8289[/C][C]0.205688[/C][/ROW]
[ROW][C]18[/C][C]-0.0855[/C][C]-0.5862[/C][C]0.280287[/C][/ROW]
[ROW][C]19[/C][C]-0.072323[/C][C]-0.4958[/C][C]0.311165[/C][/ROW]
[ROW][C]20[/C][C]0.024001[/C][C]0.1645[/C][C]0.435005[/C][/ROW]
[ROW][C]21[/C][C]-0.164509[/C][C]-1.1278[/C][C]0.132562[/C][/ROW]
[ROW][C]22[/C][C]-0.04145[/C][C]-0.2842[/C][C]0.388766[/C][/ROW]
[ROW][C]23[/C][C]-0.133478[/C][C]-0.9151[/C][C]0.182411[/C][/ROW]
[ROW][C]24[/C][C]-0.097383[/C][C]-0.6676[/C][C]0.253818[/C][/ROW]
[ROW][C]25[/C][C]-0.091395[/C][C]-0.6266[/C][C]0.266985[/C][/ROW]
[ROW][C]26[/C][C]0.033266[/C][C]0.2281[/C][C]0.410294[/C][/ROW]
[ROW][C]27[/C][C]-0.097618[/C][C]-0.6692[/C][C]0.253309[/C][/ROW]
[ROW][C]28[/C][C]-0.106478[/C][C]-0.73[/C][C]0.234515[/C][/ROW]
[ROW][C]29[/C][C]-0.109761[/C][C]-0.7525[/C][C]0.227756[/C][/ROW]
[ROW][C]30[/C][C]-0.078507[/C][C]-0.5382[/C][C]0.296484[/C][/ROW]
[ROW][C]31[/C][C]-0.026955[/C][C]-0.1848[/C][C]0.427094[/C][/ROW]
[ROW][C]32[/C][C]-0.046053[/C][C]-0.3157[/C][C]0.376805[/C][/ROW]
[ROW][C]33[/C][C]0.01371[/C][C]0.094[/C][C]0.462759[/C][/ROW]
[ROW][C]34[/C][C]-0.012804[/C][C]-0.0878[/C][C]0.465212[/C][/ROW]
[ROW][C]35[/C][C]-0.003101[/C][C]-0.0213[/C][C]0.491564[/C][/ROW]
[ROW][C]36[/C][C]-0.054791[/C][C]-0.3756[/C][C]0.354443[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64615&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64615&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
1-0.008526-0.05850.476817
20.0245090.1680.433642
30.1235850.84730.200574
40.140680.96450.169877
50.0166520.11420.454798
60.1983731.360.090163
70.075370.51670.303891
80.0523230.35870.360709
90.0503230.3450.365817
10-0.1749-1.19910.118258
110.3631642.48970.008189
12-0.127746-0.87580.192801
13-0.088282-0.60520.273968
140.0185940.12750.449553
150.1342740.92050.180996
16-0.090846-0.62280.26821
170.1209010.82890.205688
18-0.0855-0.58620.280287
19-0.072323-0.49580.311165
200.0240010.16450.435005
21-0.164509-1.12780.132562
22-0.04145-0.28420.388766
23-0.133478-0.91510.182411
24-0.097383-0.66760.253818
25-0.091395-0.62660.266985
260.0332660.22810.410294
27-0.097618-0.66920.253309
28-0.106478-0.730.234515
29-0.109761-0.75250.227756
30-0.078507-0.53820.296484
31-0.026955-0.18480.427094
32-0.046053-0.31570.376805
330.013710.0940.462759
34-0.012804-0.08780.465212
35-0.003101-0.02130.491564
36-0.054791-0.37560.354443






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.008526-0.05850.476817
20.0244380.16750.433833
30.124080.85060.199639
40.1448420.9930.1629
50.0168580.11560.454242
60.1840291.26160.106652
70.0553660.37960.352987
80.0320420.21970.41354
90.0065980.04520.482057
10-0.257977-1.76860.041725
110.3595992.46530.008699
12-0.246527-1.69010.048816
13-0.057368-0.39330.347941
14-0.006303-0.04320.482859
150.0537410.36840.357104
160.0800650.54890.292837
17-0.00046-0.00320.498748
18-0.086806-0.59510.277312
19-0.0427-0.29270.385505
20-0.028268-0.19380.423586
21-0.07087-0.48590.314661
22-0.254511-1.74480.043775
23-0.080837-0.55420.291038
24-0.022987-0.15760.437727
250.0084220.05770.477101
260.0103220.07080.471943
270.0997940.68420.248619
28-0.140575-0.96370.170057
290.0826790.56680.286768
30-0.042836-0.29370.385153
31-0.079226-0.54310.294798
320.0186410.12780.449426
330.0500330.3430.36656
340.0816860.560.289065
350.0270620.18550.426808
36-0.008514-0.05840.47685

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.008526 & -0.0585 & 0.476817 \tabularnewline
2 & 0.024438 & 0.1675 & 0.433833 \tabularnewline
3 & 0.12408 & 0.8506 & 0.199639 \tabularnewline
4 & 0.144842 & 0.993 & 0.1629 \tabularnewline
5 & 0.016858 & 0.1156 & 0.454242 \tabularnewline
6 & 0.184029 & 1.2616 & 0.106652 \tabularnewline
7 & 0.055366 & 0.3796 & 0.352987 \tabularnewline
8 & 0.032042 & 0.2197 & 0.41354 \tabularnewline
9 & 0.006598 & 0.0452 & 0.482057 \tabularnewline
10 & -0.257977 & -1.7686 & 0.041725 \tabularnewline
11 & 0.359599 & 2.4653 & 0.008699 \tabularnewline
12 & -0.246527 & -1.6901 & 0.048816 \tabularnewline
13 & -0.057368 & -0.3933 & 0.347941 \tabularnewline
14 & -0.006303 & -0.0432 & 0.482859 \tabularnewline
15 & 0.053741 & 0.3684 & 0.357104 \tabularnewline
16 & 0.080065 & 0.5489 & 0.292837 \tabularnewline
17 & -0.00046 & -0.0032 & 0.498748 \tabularnewline
18 & -0.086806 & -0.5951 & 0.277312 \tabularnewline
19 & -0.0427 & -0.2927 & 0.385505 \tabularnewline
20 & -0.028268 & -0.1938 & 0.423586 \tabularnewline
21 & -0.07087 & -0.4859 & 0.314661 \tabularnewline
22 & -0.254511 & -1.7448 & 0.043775 \tabularnewline
23 & -0.080837 & -0.5542 & 0.291038 \tabularnewline
24 & -0.022987 & -0.1576 & 0.437727 \tabularnewline
25 & 0.008422 & 0.0577 & 0.477101 \tabularnewline
26 & 0.010322 & 0.0708 & 0.471943 \tabularnewline
27 & 0.099794 & 0.6842 & 0.248619 \tabularnewline
28 & -0.140575 & -0.9637 & 0.170057 \tabularnewline
29 & 0.082679 & 0.5668 & 0.286768 \tabularnewline
30 & -0.042836 & -0.2937 & 0.385153 \tabularnewline
31 & -0.079226 & -0.5431 & 0.294798 \tabularnewline
32 & 0.018641 & 0.1278 & 0.449426 \tabularnewline
33 & 0.050033 & 0.343 & 0.36656 \tabularnewline
34 & 0.081686 & 0.56 & 0.289065 \tabularnewline
35 & 0.027062 & 0.1855 & 0.426808 \tabularnewline
36 & -0.008514 & -0.0584 & 0.47685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64615&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]-0.008526[/C][C]-0.0585[/C][C]0.476817[/C][/ROW]
[ROW][C]2[/C][C]0.024438[/C][C]0.1675[/C][C]0.433833[/C][/ROW]
[ROW][C]3[/C][C]0.12408[/C][C]0.8506[/C][C]0.199639[/C][/ROW]
[ROW][C]4[/C][C]0.144842[/C][C]0.993[/C][C]0.1629[/C][/ROW]
[ROW][C]5[/C][C]0.016858[/C][C]0.1156[/C][C]0.454242[/C][/ROW]
[ROW][C]6[/C][C]0.184029[/C][C]1.2616[/C][C]0.106652[/C][/ROW]
[ROW][C]7[/C][C]0.055366[/C][C]0.3796[/C][C]0.352987[/C][/ROW]
[ROW][C]8[/C][C]0.032042[/C][C]0.2197[/C][C]0.41354[/C][/ROW]
[ROW][C]9[/C][C]0.006598[/C][C]0.0452[/C][C]0.482057[/C][/ROW]
[ROW][C]10[/C][C]-0.257977[/C][C]-1.7686[/C][C]0.041725[/C][/ROW]
[ROW][C]11[/C][C]0.359599[/C][C]2.4653[/C][C]0.008699[/C][/ROW]
[ROW][C]12[/C][C]-0.246527[/C][C]-1.6901[/C][C]0.048816[/C][/ROW]
[ROW][C]13[/C][C]-0.057368[/C][C]-0.3933[/C][C]0.347941[/C][/ROW]
[ROW][C]14[/C][C]-0.006303[/C][C]-0.0432[/C][C]0.482859[/C][/ROW]
[ROW][C]15[/C][C]0.053741[/C][C]0.3684[/C][C]0.357104[/C][/ROW]
[ROW][C]16[/C][C]0.080065[/C][C]0.5489[/C][C]0.292837[/C][/ROW]
[ROW][C]17[/C][C]-0.00046[/C][C]-0.0032[/C][C]0.498748[/C][/ROW]
[ROW][C]18[/C][C]-0.086806[/C][C]-0.5951[/C][C]0.277312[/C][/ROW]
[ROW][C]19[/C][C]-0.0427[/C][C]-0.2927[/C][C]0.385505[/C][/ROW]
[ROW][C]20[/C][C]-0.028268[/C][C]-0.1938[/C][C]0.423586[/C][/ROW]
[ROW][C]21[/C][C]-0.07087[/C][C]-0.4859[/C][C]0.314661[/C][/ROW]
[ROW][C]22[/C][C]-0.254511[/C][C]-1.7448[/C][C]0.043775[/C][/ROW]
[ROW][C]23[/C][C]-0.080837[/C][C]-0.5542[/C][C]0.291038[/C][/ROW]
[ROW][C]24[/C][C]-0.022987[/C][C]-0.1576[/C][C]0.437727[/C][/ROW]
[ROW][C]25[/C][C]0.008422[/C][C]0.0577[/C][C]0.477101[/C][/ROW]
[ROW][C]26[/C][C]0.010322[/C][C]0.0708[/C][C]0.471943[/C][/ROW]
[ROW][C]27[/C][C]0.099794[/C][C]0.6842[/C][C]0.248619[/C][/ROW]
[ROW][C]28[/C][C]-0.140575[/C][C]-0.9637[/C][C]0.170057[/C][/ROW]
[ROW][C]29[/C][C]0.082679[/C][C]0.5668[/C][C]0.286768[/C][/ROW]
[ROW][C]30[/C][C]-0.042836[/C][C]-0.2937[/C][C]0.385153[/C][/ROW]
[ROW][C]31[/C][C]-0.079226[/C][C]-0.5431[/C][C]0.294798[/C][/ROW]
[ROW][C]32[/C][C]0.018641[/C][C]0.1278[/C][C]0.449426[/C][/ROW]
[ROW][C]33[/C][C]0.050033[/C][C]0.343[/C][C]0.36656[/C][/ROW]
[ROW][C]34[/C][C]0.081686[/C][C]0.56[/C][C]0.289065[/C][/ROW]
[ROW][C]35[/C][C]0.027062[/C][C]0.1855[/C][C]0.426808[/C][/ROW]
[ROW][C]36[/C][C]-0.008514[/C][C]-0.0584[/C][C]0.47685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64615&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64615&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
1-0.008526-0.05850.476817
20.0244380.16750.433833
30.124080.85060.199639
40.1448420.9930.1629
50.0168580.11560.454242
60.1840291.26160.106652
70.0553660.37960.352987
80.0320420.21970.41354
90.0065980.04520.482057
10-0.257977-1.76860.041725
110.3595992.46530.008699
12-0.246527-1.69010.048816
13-0.057368-0.39330.347941
14-0.006303-0.04320.482859
150.0537410.36840.357104
160.0800650.54890.292837
17-0.00046-0.00320.498748
18-0.086806-0.59510.277312
19-0.0427-0.29270.385505
20-0.028268-0.19380.423586
21-0.07087-0.48590.314661
22-0.254511-1.74480.043775
23-0.080837-0.55420.291038
24-0.022987-0.15760.437727
250.0084220.05770.477101
260.0103220.07080.471943
270.0997940.68420.248619
28-0.140575-0.96370.170057
290.0826790.56680.286768
30-0.042836-0.29370.385153
31-0.079226-0.54310.294798
320.0186410.12780.449426
330.0500330.3430.36656
340.0816860.560.289065
350.0270620.18550.426808
36-0.008514-0.05840.47685


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.7 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.7 ; par3 = 1 ; 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')