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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, 14 Dec 2009 03:16:18 -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/14/t12607863145ba2le4a8co8x7k.htm/, Retrieved Sun, 05 May 2024 12:18:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67508, Retrieved Sun, 05 May 2024 12:18:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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]
-   PD        [(Partial) Autocorrelation Function] [Ws 8 autocorrelat...] [2009-11-27 12:17:11] [12f02da0296cb21dc23d82ae014a8b71]
-   PD            [(Partial) Autocorrelation Function] [Paper Y3 d=1 D=0] [2009-12-14 10:16:18] [b653746fe14da1ddc21bd75262e8c46b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29
103.69
103.68
104.2
104.08
104.16
103.05
104.66
104.46
104.95
105.85
106.23
104.86
107.44
108.23
108.45
109.39
110.15
109.13
110.28
110.17
109.99
109.26
109.11
107.06
109.53
108.92
109.24
109.12
109
107.23
109.49
109.04
109.02
109.23

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=67508&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=67508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67508&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
1-0.4646-3.56870.00036
20.0829030.63680.263363
30.0217960.16740.433807
40.0675890.51920.302794
5-0.443152-3.40396e-04
60.7428975.70630
7-0.443367-3.40560.000597
80.0476050.36570.357963
9-0.00783-0.06010.476122
100.0033070.02540.48991
11-0.349352-2.68340.004721
120.6610415.07752e-06
13-0.41685-3.20190.0011
140.0363090.27890.390651
150.0243650.18720.426092
16-0.015664-0.12030.452321
17-0.347246-2.66720.004928
180.5826444.47541.8e-05
19-0.352368-2.70660.004438
200.0220520.16940.433037
210.0018110.01390.494475
220.0496120.38110.352259
23-0.304188-2.33650.01144
240.5395374.14435.5e-05
25-0.27112-2.08250.02082
260.0574750.44150.330242
27-0.011754-0.09030.464183
280.0204110.15680.437978
29-0.255292-1.96090.027306
300.4236833.25440.000942
31-0.245612-1.88660.03207
320.0347280.26680.395295
330.0261490.20090.420753
340.0121490.09330.462985
35-0.198625-1.52570.066218
360.3734512.86850.002856

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.4646 & -3.5687 & 0.00036 \tabularnewline
2 & 0.082903 & 0.6368 & 0.263363 \tabularnewline
3 & 0.021796 & 0.1674 & 0.433807 \tabularnewline
4 & 0.067589 & 0.5192 & 0.302794 \tabularnewline
5 & -0.443152 & -3.4039 & 6e-04 \tabularnewline
6 & 0.742897 & 5.7063 & 0 \tabularnewline
7 & -0.443367 & -3.4056 & 0.000597 \tabularnewline
8 & 0.047605 & 0.3657 & 0.357963 \tabularnewline
9 & -0.00783 & -0.0601 & 0.476122 \tabularnewline
10 & 0.003307 & 0.0254 & 0.48991 \tabularnewline
11 & -0.349352 & -2.6834 & 0.004721 \tabularnewline
12 & 0.661041 & 5.0775 & 2e-06 \tabularnewline
13 & -0.41685 & -3.2019 & 0.0011 \tabularnewline
14 & 0.036309 & 0.2789 & 0.390651 \tabularnewline
15 & 0.024365 & 0.1872 & 0.426092 \tabularnewline
16 & -0.015664 & -0.1203 & 0.452321 \tabularnewline
17 & -0.347246 & -2.6672 & 0.004928 \tabularnewline
18 & 0.582644 & 4.4754 & 1.8e-05 \tabularnewline
19 & -0.352368 & -2.7066 & 0.004438 \tabularnewline
20 & 0.022052 & 0.1694 & 0.433037 \tabularnewline
21 & 0.001811 & 0.0139 & 0.494475 \tabularnewline
22 & 0.049612 & 0.3811 & 0.352259 \tabularnewline
23 & -0.304188 & -2.3365 & 0.01144 \tabularnewline
24 & 0.539537 & 4.1443 & 5.5e-05 \tabularnewline
25 & -0.27112 & -2.0825 & 0.02082 \tabularnewline
26 & 0.057475 & 0.4415 & 0.330242 \tabularnewline
27 & -0.011754 & -0.0903 & 0.464183 \tabularnewline
28 & 0.020411 & 0.1568 & 0.437978 \tabularnewline
29 & -0.255292 & -1.9609 & 0.027306 \tabularnewline
30 & 0.423683 & 3.2544 & 0.000942 \tabularnewline
31 & -0.245612 & -1.8866 & 0.03207 \tabularnewline
32 & 0.034728 & 0.2668 & 0.395295 \tabularnewline
33 & 0.026149 & 0.2009 & 0.420753 \tabularnewline
34 & 0.012149 & 0.0933 & 0.462985 \tabularnewline
35 & -0.198625 & -1.5257 & 0.066218 \tabularnewline
36 & 0.373451 & 2.8685 & 0.002856 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67508&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]-0.4646[/C][C]-3.5687[/C][C]0.00036[/C][/ROW]
[ROW][C]2[/C][C]0.082903[/C][C]0.6368[/C][C]0.263363[/C][/ROW]
[ROW][C]3[/C][C]0.021796[/C][C]0.1674[/C][C]0.433807[/C][/ROW]
[ROW][C]4[/C][C]0.067589[/C][C]0.5192[/C][C]0.302794[/C][/ROW]
[ROW][C]5[/C][C]-0.443152[/C][C]-3.4039[/C][C]6e-04[/C][/ROW]
[ROW][C]6[/C][C]0.742897[/C][C]5.7063[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.443367[/C][C]-3.4056[/C][C]0.000597[/C][/ROW]
[ROW][C]8[/C][C]0.047605[/C][C]0.3657[/C][C]0.357963[/C][/ROW]
[ROW][C]9[/C][C]-0.00783[/C][C]-0.0601[/C][C]0.476122[/C][/ROW]
[ROW][C]10[/C][C]0.003307[/C][C]0.0254[/C][C]0.48991[/C][/ROW]
[ROW][C]11[/C][C]-0.349352[/C][C]-2.6834[/C][C]0.004721[/C][/ROW]
[ROW][C]12[/C][C]0.661041[/C][C]5.0775[/C][C]2e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.41685[/C][C]-3.2019[/C][C]0.0011[/C][/ROW]
[ROW][C]14[/C][C]0.036309[/C][C]0.2789[/C][C]0.390651[/C][/ROW]
[ROW][C]15[/C][C]0.024365[/C][C]0.1872[/C][C]0.426092[/C][/ROW]
[ROW][C]16[/C][C]-0.015664[/C][C]-0.1203[/C][C]0.452321[/C][/ROW]
[ROW][C]17[/C][C]-0.347246[/C][C]-2.6672[/C][C]0.004928[/C][/ROW]
[ROW][C]18[/C][C]0.582644[/C][C]4.4754[/C][C]1.8e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.352368[/C][C]-2.7066[/C][C]0.004438[/C][/ROW]
[ROW][C]20[/C][C]0.022052[/C][C]0.1694[/C][C]0.433037[/C][/ROW]
[ROW][C]21[/C][C]0.001811[/C][C]0.0139[/C][C]0.494475[/C][/ROW]
[ROW][C]22[/C][C]0.049612[/C][C]0.3811[/C][C]0.352259[/C][/ROW]
[ROW][C]23[/C][C]-0.304188[/C][C]-2.3365[/C][C]0.01144[/C][/ROW]
[ROW][C]24[/C][C]0.539537[/C][C]4.1443[/C][C]5.5e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.27112[/C][C]-2.0825[/C][C]0.02082[/C][/ROW]
[ROW][C]26[/C][C]0.057475[/C][C]0.4415[/C][C]0.330242[/C][/ROW]
[ROW][C]27[/C][C]-0.011754[/C][C]-0.0903[/C][C]0.464183[/C][/ROW]
[ROW][C]28[/C][C]0.020411[/C][C]0.1568[/C][C]0.437978[/C][/ROW]
[ROW][C]29[/C][C]-0.255292[/C][C]-1.9609[/C][C]0.027306[/C][/ROW]
[ROW][C]30[/C][C]0.423683[/C][C]3.2544[/C][C]0.000942[/C][/ROW]
[ROW][C]31[/C][C]-0.245612[/C][C]-1.8866[/C][C]0.03207[/C][/ROW]
[ROW][C]32[/C][C]0.034728[/C][C]0.2668[/C][C]0.395295[/C][/ROW]
[ROW][C]33[/C][C]0.026149[/C][C]0.2009[/C][C]0.420753[/C][/ROW]
[ROW][C]34[/C][C]0.012149[/C][C]0.0933[/C][C]0.462985[/C][/ROW]
[ROW][C]35[/C][C]-0.198625[/C][C]-1.5257[/C][C]0.066218[/C][/ROW]
[ROW][C]36[/C][C]0.373451[/C][C]2.8685[/C][C]0.002856[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67508&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
1-0.4646-3.56870.00036
20.0829030.63680.263363
30.0217960.16740.433807
40.0675890.51920.302794
5-0.443152-3.40396e-04
60.7428975.70630
7-0.443367-3.40560.000597
80.0476050.36570.357963
9-0.00783-0.06010.476122
100.0033070.02540.48991
11-0.349352-2.68340.004721
120.6610415.07752e-06
13-0.41685-3.20190.0011
140.0363090.27890.390651
150.0243650.18720.426092
16-0.015664-0.12030.452321
17-0.347246-2.66720.004928
180.5826444.47541.8e-05
19-0.352368-2.70660.004438
200.0220520.16940.433037
210.0018110.01390.494475
220.0496120.38110.352259
23-0.304188-2.33650.01144
240.5395374.14435.5e-05
25-0.27112-2.08250.02082
260.0574750.44150.330242
27-0.011754-0.09030.464183
280.0204110.15680.437978
29-0.255292-1.96090.027306
300.4236833.25440.000942
31-0.245612-1.88660.03207
320.0347280.26680.395295
330.0261490.20090.420753
340.0121490.09330.462985
35-0.198625-1.52570.066218
360.3734512.86850.002856






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.4646-3.56870.00036
2-0.169548-1.30230.098934
3-0.015663-0.12030.452324
40.1142280.87740.191915
5-0.470711-3.61560.000311
60.561384.3123.1e-05
7-0.05212-0.40030.345175
8-0.146071-1.1220.133205
9-0.132763-1.01980.156
10-0.222023-1.70540.046691
11-0.010307-0.07920.468582
120.2157021.65680.05143
13-0.021216-0.1630.435551
14-0.134812-1.03550.152329
15-0.074546-0.57260.284545
16-0.052006-0.39950.345495
17-0.185586-1.42550.07964
18-0.075974-0.58360.280867
190.0226690.17410.431183
20-0.033768-0.25940.398124
21-0.144985-1.11370.134972
220.0505620.38840.349569
23-0.035085-0.26950.394246
240.0015450.01190.495284
250.0978720.75180.22759
260.0509330.39120.348521
27-0.058223-0.44720.328177
28-0.148966-1.14420.128575
290.0159280.12230.451521
30-0.152452-1.1710.123152
31-0.080454-0.6180.269483
320.0156120.11990.452477
330.086830.6670.253702
340.0119240.09160.463667
350.0423560.32530.373035
360.0113120.08690.465527

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.4646 & -3.5687 & 0.00036 \tabularnewline
2 & -0.169548 & -1.3023 & 0.098934 \tabularnewline
3 & -0.015663 & -0.1203 & 0.452324 \tabularnewline
4 & 0.114228 & 0.8774 & 0.191915 \tabularnewline
5 & -0.470711 & -3.6156 & 0.000311 \tabularnewline
6 & 0.56138 & 4.312 & 3.1e-05 \tabularnewline
7 & -0.05212 & -0.4003 & 0.345175 \tabularnewline
8 & -0.146071 & -1.122 & 0.133205 \tabularnewline
9 & -0.132763 & -1.0198 & 0.156 \tabularnewline
10 & -0.222023 & -1.7054 & 0.046691 \tabularnewline
11 & -0.010307 & -0.0792 & 0.468582 \tabularnewline
12 & 0.215702 & 1.6568 & 0.05143 \tabularnewline
13 & -0.021216 & -0.163 & 0.435551 \tabularnewline
14 & -0.134812 & -1.0355 & 0.152329 \tabularnewline
15 & -0.074546 & -0.5726 & 0.284545 \tabularnewline
16 & -0.052006 & -0.3995 & 0.345495 \tabularnewline
17 & -0.185586 & -1.4255 & 0.07964 \tabularnewline
18 & -0.075974 & -0.5836 & 0.280867 \tabularnewline
19 & 0.022669 & 0.1741 & 0.431183 \tabularnewline
20 & -0.033768 & -0.2594 & 0.398124 \tabularnewline
21 & -0.144985 & -1.1137 & 0.134972 \tabularnewline
22 & 0.050562 & 0.3884 & 0.349569 \tabularnewline
23 & -0.035085 & -0.2695 & 0.394246 \tabularnewline
24 & 0.001545 & 0.0119 & 0.495284 \tabularnewline
25 & 0.097872 & 0.7518 & 0.22759 \tabularnewline
26 & 0.050933 & 0.3912 & 0.348521 \tabularnewline
27 & -0.058223 & -0.4472 & 0.328177 \tabularnewline
28 & -0.148966 & -1.1442 & 0.128575 \tabularnewline
29 & 0.015928 & 0.1223 & 0.451521 \tabularnewline
30 & -0.152452 & -1.171 & 0.123152 \tabularnewline
31 & -0.080454 & -0.618 & 0.269483 \tabularnewline
32 & 0.015612 & 0.1199 & 0.452477 \tabularnewline
33 & 0.08683 & 0.667 & 0.253702 \tabularnewline
34 & 0.011924 & 0.0916 & 0.463667 \tabularnewline
35 & 0.042356 & 0.3253 & 0.373035 \tabularnewline
36 & 0.011312 & 0.0869 & 0.465527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67508&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]-0.4646[/C][C]-3.5687[/C][C]0.00036[/C][/ROW]
[ROW][C]2[/C][C]-0.169548[/C][C]-1.3023[/C][C]0.098934[/C][/ROW]
[ROW][C]3[/C][C]-0.015663[/C][C]-0.1203[/C][C]0.452324[/C][/ROW]
[ROW][C]4[/C][C]0.114228[/C][C]0.8774[/C][C]0.191915[/C][/ROW]
[ROW][C]5[/C][C]-0.470711[/C][C]-3.6156[/C][C]0.000311[/C][/ROW]
[ROW][C]6[/C][C]0.56138[/C][C]4.312[/C][C]3.1e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.05212[/C][C]-0.4003[/C][C]0.345175[/C][/ROW]
[ROW][C]8[/C][C]-0.146071[/C][C]-1.122[/C][C]0.133205[/C][/ROW]
[ROW][C]9[/C][C]-0.132763[/C][C]-1.0198[/C][C]0.156[/C][/ROW]
[ROW][C]10[/C][C]-0.222023[/C][C]-1.7054[/C][C]0.046691[/C][/ROW]
[ROW][C]11[/C][C]-0.010307[/C][C]-0.0792[/C][C]0.468582[/C][/ROW]
[ROW][C]12[/C][C]0.215702[/C][C]1.6568[/C][C]0.05143[/C][/ROW]
[ROW][C]13[/C][C]-0.021216[/C][C]-0.163[/C][C]0.435551[/C][/ROW]
[ROW][C]14[/C][C]-0.134812[/C][C]-1.0355[/C][C]0.152329[/C][/ROW]
[ROW][C]15[/C][C]-0.074546[/C][C]-0.5726[/C][C]0.284545[/C][/ROW]
[ROW][C]16[/C][C]-0.052006[/C][C]-0.3995[/C][C]0.345495[/C][/ROW]
[ROW][C]17[/C][C]-0.185586[/C][C]-1.4255[/C][C]0.07964[/C][/ROW]
[ROW][C]18[/C][C]-0.075974[/C][C]-0.5836[/C][C]0.280867[/C][/ROW]
[ROW][C]19[/C][C]0.022669[/C][C]0.1741[/C][C]0.431183[/C][/ROW]
[ROW][C]20[/C][C]-0.033768[/C][C]-0.2594[/C][C]0.398124[/C][/ROW]
[ROW][C]21[/C][C]-0.144985[/C][C]-1.1137[/C][C]0.134972[/C][/ROW]
[ROW][C]22[/C][C]0.050562[/C][C]0.3884[/C][C]0.349569[/C][/ROW]
[ROW][C]23[/C][C]-0.035085[/C][C]-0.2695[/C][C]0.394246[/C][/ROW]
[ROW][C]24[/C][C]0.001545[/C][C]0.0119[/C][C]0.495284[/C][/ROW]
[ROW][C]25[/C][C]0.097872[/C][C]0.7518[/C][C]0.22759[/C][/ROW]
[ROW][C]26[/C][C]0.050933[/C][C]0.3912[/C][C]0.348521[/C][/ROW]
[ROW][C]27[/C][C]-0.058223[/C][C]-0.4472[/C][C]0.328177[/C][/ROW]
[ROW][C]28[/C][C]-0.148966[/C][C]-1.1442[/C][C]0.128575[/C][/ROW]
[ROW][C]29[/C][C]0.015928[/C][C]0.1223[/C][C]0.451521[/C][/ROW]
[ROW][C]30[/C][C]-0.152452[/C][C]-1.171[/C][C]0.123152[/C][/ROW]
[ROW][C]31[/C][C]-0.080454[/C][C]-0.618[/C][C]0.269483[/C][/ROW]
[ROW][C]32[/C][C]0.015612[/C][C]0.1199[/C][C]0.452477[/C][/ROW]
[ROW][C]33[/C][C]0.08683[/C][C]0.667[/C][C]0.253702[/C][/ROW]
[ROW][C]34[/C][C]0.011924[/C][C]0.0916[/C][C]0.463667[/C][/ROW]
[ROW][C]35[/C][C]0.042356[/C][C]0.3253[/C][C]0.373035[/C][/ROW]
[ROW][C]36[/C][C]0.011312[/C][C]0.0869[/C][C]0.465527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67508&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67508&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
1-0.4646-3.56870.00036
2-0.169548-1.30230.098934
3-0.015663-0.12030.452324
40.1142280.87740.191915
5-0.470711-3.61560.000311
60.561384.3123.1e-05
7-0.05212-0.40030.345175
8-0.146071-1.1220.133205
9-0.132763-1.01980.156
10-0.222023-1.70540.046691
11-0.010307-0.07920.468582
120.2157021.65680.05143
13-0.021216-0.1630.435551
14-0.134812-1.03550.152329
15-0.074546-0.57260.284545
16-0.052006-0.39950.345495
17-0.185586-1.42550.07964
18-0.075974-0.58360.280867
190.0226690.17410.431183
20-0.033768-0.25940.398124
21-0.144985-1.11370.134972
220.0505620.38840.349569
23-0.035085-0.26950.394246
240.0015450.01190.495284
250.0978720.75180.22759
260.0509330.39120.348521
27-0.058223-0.44720.328177
28-0.148966-1.14420.128575
290.0159280.12230.451521
30-0.152452-1.1710.123152
31-0.080454-0.6180.269483
320.0156120.11990.452477
330.086830.6670.253702
340.0119240.09160.463667
350.0423560.32530.373035
360.0113120.08690.465527


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')