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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, 24 Nov 2009 08:39:07 -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/24/t1259077217kgz8rg22stb7bz0.htm/, Retrieved Sun, 16 Jun 2024 20:44:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59126, Retrieved Sun, 16 Jun 2024 20:44:49 +0000
QR Codes:

Original text written by user:Uitleg in Word document
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
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]
- R  D          [(Partial) Autocorrelation Function] [Bestedingen consu...] [2009-11-24 15:39:07] [8eb8270f5a1cfdf0409dcfcbf10be18b] [Current]
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Dataseries X:
96.96
93.11
95.62
98.30
96.38
100.82
99.06
94.03
102.07
99.31
98.64
101.82
99.14
97.63
100.06
101.32
101.49
105.43
105.09
99.48
108.53
104.34
106.10
107.35
103.00
104.50
105.17
104.84
106.18
108.86
107.77
102.74
112.63
106.26
108.86
111.38
106.85
107.86
107.94
111.38
111.29
113.72
111.88
109.87
113.72
111.71
114.81
112.05
111.54
110.87
110.87
115.48
111.63
116.24
113.56
106.01
110.45
107.77
108.61
108.19




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=59126&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=59126&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59126&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.50781-3.48140.000544
2-0.073815-0.5060.307594
30.4354742.98550.002242
4-0.291045-1.99530.025912
50.0514880.3530.36284
60.0960230.65830.256778
7-0.148994-1.02140.156135
80.124450.85320.198942
9-0.023118-0.15850.437375
10-0.154251-1.05750.147846
110.2509371.72030.045975
12-0.156019-1.06960.145128
13-0.125929-0.86330.196172
140.2525631.73150.044962
15-0.116955-0.80180.213351
16-0.123642-0.84760.200466
170.0786070.53890.296248
180.0543190.37240.355636
19-0.131521-0.90170.185916
200.057020.39090.348815
210.0765190.52460.301167
22-0.153835-1.05460.148491
230.1946871.33470.094201
24-0.135716-0.93040.178454
250.0465040.31880.37564
260.0831820.57030.285606
27-0.09944-0.68170.249378
280.0612680.420.338187
290.0658850.45170.326788
30-0.100066-0.6860.248037
310.0024740.0170.493271
320.1004360.68860.247244
33-0.10225-0.7010.243384
340.0102030.06990.472266
350.039480.27070.393919
36-0.086594-0.59370.277794

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.50781 & -3.4814 & 0.000544 \tabularnewline
2 & -0.073815 & -0.506 & 0.307594 \tabularnewline
3 & 0.435474 & 2.9855 & 0.002242 \tabularnewline
4 & -0.291045 & -1.9953 & 0.025912 \tabularnewline
5 & 0.051488 & 0.353 & 0.36284 \tabularnewline
6 & 0.096023 & 0.6583 & 0.256778 \tabularnewline
7 & -0.148994 & -1.0214 & 0.156135 \tabularnewline
8 & 0.12445 & 0.8532 & 0.198942 \tabularnewline
9 & -0.023118 & -0.1585 & 0.437375 \tabularnewline
10 & -0.154251 & -1.0575 & 0.147846 \tabularnewline
11 & 0.250937 & 1.7203 & 0.045975 \tabularnewline
12 & -0.156019 & -1.0696 & 0.145128 \tabularnewline
13 & -0.125929 & -0.8633 & 0.196172 \tabularnewline
14 & 0.252563 & 1.7315 & 0.044962 \tabularnewline
15 & -0.116955 & -0.8018 & 0.213351 \tabularnewline
16 & -0.123642 & -0.8476 & 0.200466 \tabularnewline
17 & 0.078607 & 0.5389 & 0.296248 \tabularnewline
18 & 0.054319 & 0.3724 & 0.355636 \tabularnewline
19 & -0.131521 & -0.9017 & 0.185916 \tabularnewline
20 & 0.05702 & 0.3909 & 0.348815 \tabularnewline
21 & 0.076519 & 0.5246 & 0.301167 \tabularnewline
22 & -0.153835 & -1.0546 & 0.148491 \tabularnewline
23 & 0.194687 & 1.3347 & 0.094201 \tabularnewline
24 & -0.135716 & -0.9304 & 0.178454 \tabularnewline
25 & 0.046504 & 0.3188 & 0.37564 \tabularnewline
26 & 0.083182 & 0.5703 & 0.285606 \tabularnewline
27 & -0.09944 & -0.6817 & 0.249378 \tabularnewline
28 & 0.061268 & 0.42 & 0.338187 \tabularnewline
29 & 0.065885 & 0.4517 & 0.326788 \tabularnewline
30 & -0.100066 & -0.686 & 0.248037 \tabularnewline
31 & 0.002474 & 0.017 & 0.493271 \tabularnewline
32 & 0.100436 & 0.6886 & 0.247244 \tabularnewline
33 & -0.10225 & -0.701 & 0.243384 \tabularnewline
34 & 0.010203 & 0.0699 & 0.472266 \tabularnewline
35 & 0.03948 & 0.2707 & 0.393919 \tabularnewline
36 & -0.086594 & -0.5937 & 0.277794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59126&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]-0.50781[/C][C]-3.4814[/C][C]0.000544[/C][/ROW]
[ROW][C]2[/C][C]-0.073815[/C][C]-0.506[/C][C]0.307594[/C][/ROW]
[ROW][C]3[/C][C]0.435474[/C][C]2.9855[/C][C]0.002242[/C][/ROW]
[ROW][C]4[/C][C]-0.291045[/C][C]-1.9953[/C][C]0.025912[/C][/ROW]
[ROW][C]5[/C][C]0.051488[/C][C]0.353[/C][C]0.36284[/C][/ROW]
[ROW][C]6[/C][C]0.096023[/C][C]0.6583[/C][C]0.256778[/C][/ROW]
[ROW][C]7[/C][C]-0.148994[/C][C]-1.0214[/C][C]0.156135[/C][/ROW]
[ROW][C]8[/C][C]0.12445[/C][C]0.8532[/C][C]0.198942[/C][/ROW]
[ROW][C]9[/C][C]-0.023118[/C][C]-0.1585[/C][C]0.437375[/C][/ROW]
[ROW][C]10[/C][C]-0.154251[/C][C]-1.0575[/C][C]0.147846[/C][/ROW]
[ROW][C]11[/C][C]0.250937[/C][C]1.7203[/C][C]0.045975[/C][/ROW]
[ROW][C]12[/C][C]-0.156019[/C][C]-1.0696[/C][C]0.145128[/C][/ROW]
[ROW][C]13[/C][C]-0.125929[/C][C]-0.8633[/C][C]0.196172[/C][/ROW]
[ROW][C]14[/C][C]0.252563[/C][C]1.7315[/C][C]0.044962[/C][/ROW]
[ROW][C]15[/C][C]-0.116955[/C][C]-0.8018[/C][C]0.213351[/C][/ROW]
[ROW][C]16[/C][C]-0.123642[/C][C]-0.8476[/C][C]0.200466[/C][/ROW]
[ROW][C]17[/C][C]0.078607[/C][C]0.5389[/C][C]0.296248[/C][/ROW]
[ROW][C]18[/C][C]0.054319[/C][C]0.3724[/C][C]0.355636[/C][/ROW]
[ROW][C]19[/C][C]-0.131521[/C][C]-0.9017[/C][C]0.185916[/C][/ROW]
[ROW][C]20[/C][C]0.05702[/C][C]0.3909[/C][C]0.348815[/C][/ROW]
[ROW][C]21[/C][C]0.076519[/C][C]0.5246[/C][C]0.301167[/C][/ROW]
[ROW][C]22[/C][C]-0.153835[/C][C]-1.0546[/C][C]0.148491[/C][/ROW]
[ROW][C]23[/C][C]0.194687[/C][C]1.3347[/C][C]0.094201[/C][/ROW]
[ROW][C]24[/C][C]-0.135716[/C][C]-0.9304[/C][C]0.178454[/C][/ROW]
[ROW][C]25[/C][C]0.046504[/C][C]0.3188[/C][C]0.37564[/C][/ROW]
[ROW][C]26[/C][C]0.083182[/C][C]0.5703[/C][C]0.285606[/C][/ROW]
[ROW][C]27[/C][C]-0.09944[/C][C]-0.6817[/C][C]0.249378[/C][/ROW]
[ROW][C]28[/C][C]0.061268[/C][C]0.42[/C][C]0.338187[/C][/ROW]
[ROW][C]29[/C][C]0.065885[/C][C]0.4517[/C][C]0.326788[/C][/ROW]
[ROW][C]30[/C][C]-0.100066[/C][C]-0.686[/C][C]0.248037[/C][/ROW]
[ROW][C]31[/C][C]0.002474[/C][C]0.017[/C][C]0.493271[/C][/ROW]
[ROW][C]32[/C][C]0.100436[/C][C]0.6886[/C][C]0.247244[/C][/ROW]
[ROW][C]33[/C][C]-0.10225[/C][C]-0.701[/C][C]0.243384[/C][/ROW]
[ROW][C]34[/C][C]0.010203[/C][C]0.0699[/C][C]0.472266[/C][/ROW]
[ROW][C]35[/C][C]0.03948[/C][C]0.2707[/C][C]0.393919[/C][/ROW]
[ROW][C]36[/C][C]-0.086594[/C][C]-0.5937[/C][C]0.277794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59126&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59126&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
1-0.50781-3.48140.000544
2-0.073815-0.5060.307594
30.4354742.98550.002242
4-0.291045-1.99530.025912
50.0514880.3530.36284
60.0960230.65830.256778
7-0.148994-1.02140.156135
80.124450.85320.198942
9-0.023118-0.15850.437375
10-0.154251-1.05750.147846
110.2509371.72030.045975
12-0.156019-1.06960.145128
13-0.125929-0.86330.196172
140.2525631.73150.044962
15-0.116955-0.80180.213351
16-0.123642-0.84760.200466
170.0786070.53890.296248
180.0543190.37240.355636
19-0.131521-0.90170.185916
200.057020.39090.348815
210.0765190.52460.301167
22-0.153835-1.05460.148491
230.1946871.33470.094201
24-0.135716-0.93040.178454
250.0465040.31880.37564
260.0831820.57030.285606
27-0.09944-0.68170.249378
280.0612680.420.338187
290.0658850.45170.326788
30-0.100066-0.6860.248037
310.0024740.0170.493271
320.1004360.68860.247244
33-0.10225-0.7010.243384
340.0102030.06990.472266
350.039480.27070.393919
36-0.086594-0.59370.277794







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.50781-3.48140.000544
2-0.446939-3.06410.001805
30.2597761.78090.040693
40.1650091.13120.131846
50.1161340.79620.214967
6-0.065777-0.45090.327052
7-0.147748-1.01290.158144
80.0041790.02860.488634
90.0833840.57170.28514
10-0.115292-0.79040.216632
110.0748910.51340.305029
120.0108170.07420.470601
13-0.156415-1.07230.144525
14-0.066038-0.45270.326411
150.1165450.7990.214157
16-0.000566-0.00390.49846
17-0.257973-1.76860.041728
18-0.047876-0.32820.372101
190.0189680.130.448545
200.0870730.59690.276706
210.1541281.05660.148036
22-0.128769-0.88280.19092
230.0714560.48990.313249
24-0.017112-0.11730.453556
250.0588860.40370.344131
26-0.007939-0.05440.478414
270.1221880.83770.203225
280.0409690.28090.390023
29-0.040571-0.27810.391062
30-0.011661-0.07990.46831
31-0.048676-0.33370.370043
32-0.038769-0.26580.395784
330.0191760.13150.447985
34-0.054725-0.37520.354608
35-0.022935-0.15720.437867
36-0.073567-0.50440.308186

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.50781 & -3.4814 & 0.000544 \tabularnewline
2 & -0.446939 & -3.0641 & 0.001805 \tabularnewline
3 & 0.259776 & 1.7809 & 0.040693 \tabularnewline
4 & 0.165009 & 1.1312 & 0.131846 \tabularnewline
5 & 0.116134 & 0.7962 & 0.214967 \tabularnewline
6 & -0.065777 & -0.4509 & 0.327052 \tabularnewline
7 & -0.147748 & -1.0129 & 0.158144 \tabularnewline
8 & 0.004179 & 0.0286 & 0.488634 \tabularnewline
9 & 0.083384 & 0.5717 & 0.28514 \tabularnewline
10 & -0.115292 & -0.7904 & 0.216632 \tabularnewline
11 & 0.074891 & 0.5134 & 0.305029 \tabularnewline
12 & 0.010817 & 0.0742 & 0.470601 \tabularnewline
13 & -0.156415 & -1.0723 & 0.144525 \tabularnewline
14 & -0.066038 & -0.4527 & 0.326411 \tabularnewline
15 & 0.116545 & 0.799 & 0.214157 \tabularnewline
16 & -0.000566 & -0.0039 & 0.49846 \tabularnewline
17 & -0.257973 & -1.7686 & 0.041728 \tabularnewline
18 & -0.047876 & -0.3282 & 0.372101 \tabularnewline
19 & 0.018968 & 0.13 & 0.448545 \tabularnewline
20 & 0.087073 & 0.5969 & 0.276706 \tabularnewline
21 & 0.154128 & 1.0566 & 0.148036 \tabularnewline
22 & -0.128769 & -0.8828 & 0.19092 \tabularnewline
23 & 0.071456 & 0.4899 & 0.313249 \tabularnewline
24 & -0.017112 & -0.1173 & 0.453556 \tabularnewline
25 & 0.058886 & 0.4037 & 0.344131 \tabularnewline
26 & -0.007939 & -0.0544 & 0.478414 \tabularnewline
27 & 0.122188 & 0.8377 & 0.203225 \tabularnewline
28 & 0.040969 & 0.2809 & 0.390023 \tabularnewline
29 & -0.040571 & -0.2781 & 0.391062 \tabularnewline
30 & -0.011661 & -0.0799 & 0.46831 \tabularnewline
31 & -0.048676 & -0.3337 & 0.370043 \tabularnewline
32 & -0.038769 & -0.2658 & 0.395784 \tabularnewline
33 & 0.019176 & 0.1315 & 0.447985 \tabularnewline
34 & -0.054725 & -0.3752 & 0.354608 \tabularnewline
35 & -0.022935 & -0.1572 & 0.437867 \tabularnewline
36 & -0.073567 & -0.5044 & 0.308186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59126&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]-0.50781[/C][C]-3.4814[/C][C]0.000544[/C][/ROW]
[ROW][C]2[/C][C]-0.446939[/C][C]-3.0641[/C][C]0.001805[/C][/ROW]
[ROW][C]3[/C][C]0.259776[/C][C]1.7809[/C][C]0.040693[/C][/ROW]
[ROW][C]4[/C][C]0.165009[/C][C]1.1312[/C][C]0.131846[/C][/ROW]
[ROW][C]5[/C][C]0.116134[/C][C]0.7962[/C][C]0.214967[/C][/ROW]
[ROW][C]6[/C][C]-0.065777[/C][C]-0.4509[/C][C]0.327052[/C][/ROW]
[ROW][C]7[/C][C]-0.147748[/C][C]-1.0129[/C][C]0.158144[/C][/ROW]
[ROW][C]8[/C][C]0.004179[/C][C]0.0286[/C][C]0.488634[/C][/ROW]
[ROW][C]9[/C][C]0.083384[/C][C]0.5717[/C][C]0.28514[/C][/ROW]
[ROW][C]10[/C][C]-0.115292[/C][C]-0.7904[/C][C]0.216632[/C][/ROW]
[ROW][C]11[/C][C]0.074891[/C][C]0.5134[/C][C]0.305029[/C][/ROW]
[ROW][C]12[/C][C]0.010817[/C][C]0.0742[/C][C]0.470601[/C][/ROW]
[ROW][C]13[/C][C]-0.156415[/C][C]-1.0723[/C][C]0.144525[/C][/ROW]
[ROW][C]14[/C][C]-0.066038[/C][C]-0.4527[/C][C]0.326411[/C][/ROW]
[ROW][C]15[/C][C]0.116545[/C][C]0.799[/C][C]0.214157[/C][/ROW]
[ROW][C]16[/C][C]-0.000566[/C][C]-0.0039[/C][C]0.49846[/C][/ROW]
[ROW][C]17[/C][C]-0.257973[/C][C]-1.7686[/C][C]0.041728[/C][/ROW]
[ROW][C]18[/C][C]-0.047876[/C][C]-0.3282[/C][C]0.372101[/C][/ROW]
[ROW][C]19[/C][C]0.018968[/C][C]0.13[/C][C]0.448545[/C][/ROW]
[ROW][C]20[/C][C]0.087073[/C][C]0.5969[/C][C]0.276706[/C][/ROW]
[ROW][C]21[/C][C]0.154128[/C][C]1.0566[/C][C]0.148036[/C][/ROW]
[ROW][C]22[/C][C]-0.128769[/C][C]-0.8828[/C][C]0.19092[/C][/ROW]
[ROW][C]23[/C][C]0.071456[/C][C]0.4899[/C][C]0.313249[/C][/ROW]
[ROW][C]24[/C][C]-0.017112[/C][C]-0.1173[/C][C]0.453556[/C][/ROW]
[ROW][C]25[/C][C]0.058886[/C][C]0.4037[/C][C]0.344131[/C][/ROW]
[ROW][C]26[/C][C]-0.007939[/C][C]-0.0544[/C][C]0.478414[/C][/ROW]
[ROW][C]27[/C][C]0.122188[/C][C]0.8377[/C][C]0.203225[/C][/ROW]
[ROW][C]28[/C][C]0.040969[/C][C]0.2809[/C][C]0.390023[/C][/ROW]
[ROW][C]29[/C][C]-0.040571[/C][C]-0.2781[/C][C]0.391062[/C][/ROW]
[ROW][C]30[/C][C]-0.011661[/C][C]-0.0799[/C][C]0.46831[/C][/ROW]
[ROW][C]31[/C][C]-0.048676[/C][C]-0.3337[/C][C]0.370043[/C][/ROW]
[ROW][C]32[/C][C]-0.038769[/C][C]-0.2658[/C][C]0.395784[/C][/ROW]
[ROW][C]33[/C][C]0.019176[/C][C]0.1315[/C][C]0.447985[/C][/ROW]
[ROW][C]34[/C][C]-0.054725[/C][C]-0.3752[/C][C]0.354608[/C][/ROW]
[ROW][C]35[/C][C]-0.022935[/C][C]-0.1572[/C][C]0.437867[/C][/ROW]
[ROW][C]36[/C][C]-0.073567[/C][C]-0.5044[/C][C]0.308186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59126&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59126&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
1-0.50781-3.48140.000544
2-0.446939-3.06410.001805
30.2597761.78090.040693
40.1650091.13120.131846
50.1161340.79620.214967
6-0.065777-0.45090.327052
7-0.147748-1.01290.158144
80.0041790.02860.488634
90.0833840.57170.28514
10-0.115292-0.79040.216632
110.0748910.51340.305029
120.0108170.07420.470601
13-0.156415-1.07230.144525
14-0.066038-0.45270.326411
150.1165450.7990.214157
16-0.000566-0.00390.49846
17-0.257973-1.76860.041728
18-0.047876-0.32820.372101
190.0189680.130.448545
200.0870730.59690.276706
210.1541281.05660.148036
22-0.128769-0.88280.19092
230.0714560.48990.313249
24-0.017112-0.11730.453556
250.0588860.40370.344131
26-0.007939-0.05440.478414
270.1221880.83770.203225
280.0409690.28090.390023
29-0.040571-0.27810.391062
30-0.011661-0.07990.46831
31-0.048676-0.33370.370043
32-0.038769-0.26580.395784
330.0191760.13150.447985
34-0.054725-0.37520.354608
35-0.022935-0.15720.437867
36-0.073567-0.50440.308186



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