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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 06:09:42 -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/t1259327448ev9b440r4ag32yn.htm/, Retrieved Sun, 28 Apr 2024 21:24:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60710, Retrieved Sun, 28 Apr 2024 21:24:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

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]
-    D          [(Partial) Autocorrelation Function] [WS 8: Methode 1 A...] [2009-11-27 13:09:42] [b9056af0304697100f456398102f1287] [Current]
-   P             [(Partial) Autocorrelation Function] [WS 8: Methode 1 A...] [2009-11-27 13:14:01] [8cf9233b7464ea02e32be3b30fdac052]
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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=60710&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=60710&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60710&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
10.0279950.19190.424315
20.2488861.70630.047279
30.0112310.0770.469477
40.1040110.71310.239667
5-0.141768-0.97190.168034
6-0.015503-0.10630.457906
70.0870160.59650.276836
8-0.007894-0.05410.478536
90.1696691.16320.125312
10-0.016689-0.11440.454698
110.3878292.65880.005343
12-0.146045-1.00120.16092
130.0747940.51280.30526
140.0026430.01810.492811
150.085580.58670.280105
16-0.131765-0.90330.185478
170.0450160.30860.379488
18-0.11598-0.79510.215271
19-0.147198-1.00910.159038
20-0.01036-0.0710.471839
21-0.129017-0.88450.190466
220.0412020.28250.389412
23-0.113336-0.7770.220528
24-0.010141-0.06950.472435
25-0.015372-0.10540.45826
260.0153310.10510.458371
27-0.137593-0.94330.175178
28-0.147615-1.0120.15836
29-0.137223-0.94080.175821
30-0.073034-0.50070.30946
31-0.028427-0.19490.423162
32-0.049958-0.34250.366752
330.0036070.02470.490189
34-0.022039-0.15110.440275
35-0.011699-0.08020.468208
36-0.021773-0.14930.44099

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.027995 & 0.1919 & 0.424315 \tabularnewline
2 & 0.248886 & 1.7063 & 0.047279 \tabularnewline
3 & 0.011231 & 0.077 & 0.469477 \tabularnewline
4 & 0.104011 & 0.7131 & 0.239667 \tabularnewline
5 & -0.141768 & -0.9719 & 0.168034 \tabularnewline
6 & -0.015503 & -0.1063 & 0.457906 \tabularnewline
7 & 0.087016 & 0.5965 & 0.276836 \tabularnewline
8 & -0.007894 & -0.0541 & 0.478536 \tabularnewline
9 & 0.169669 & 1.1632 & 0.125312 \tabularnewline
10 & -0.016689 & -0.1144 & 0.454698 \tabularnewline
11 & 0.387829 & 2.6588 & 0.005343 \tabularnewline
12 & -0.146045 & -1.0012 & 0.16092 \tabularnewline
13 & 0.074794 & 0.5128 & 0.30526 \tabularnewline
14 & 0.002643 & 0.0181 & 0.492811 \tabularnewline
15 & 0.08558 & 0.5867 & 0.280105 \tabularnewline
16 & -0.131765 & -0.9033 & 0.185478 \tabularnewline
17 & 0.045016 & 0.3086 & 0.379488 \tabularnewline
18 & -0.11598 & -0.7951 & 0.215271 \tabularnewline
19 & -0.147198 & -1.0091 & 0.159038 \tabularnewline
20 & -0.01036 & -0.071 & 0.471839 \tabularnewline
21 & -0.129017 & -0.8845 & 0.190466 \tabularnewline
22 & 0.041202 & 0.2825 & 0.389412 \tabularnewline
23 & -0.113336 & -0.777 & 0.220528 \tabularnewline
24 & -0.010141 & -0.0695 & 0.472435 \tabularnewline
25 & -0.015372 & -0.1054 & 0.45826 \tabularnewline
26 & 0.015331 & 0.1051 & 0.458371 \tabularnewline
27 & -0.137593 & -0.9433 & 0.175178 \tabularnewline
28 & -0.147615 & -1.012 & 0.15836 \tabularnewline
29 & -0.137223 & -0.9408 & 0.175821 \tabularnewline
30 & -0.073034 & -0.5007 & 0.30946 \tabularnewline
31 & -0.028427 & -0.1949 & 0.423162 \tabularnewline
32 & -0.049958 & -0.3425 & 0.366752 \tabularnewline
33 & 0.003607 & 0.0247 & 0.490189 \tabularnewline
34 & -0.022039 & -0.1511 & 0.440275 \tabularnewline
35 & -0.011699 & -0.0802 & 0.468208 \tabularnewline
36 & -0.021773 & -0.1493 & 0.44099 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60710&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]0.027995[/C][C]0.1919[/C][C]0.424315[/C][/ROW]
[ROW][C]2[/C][C]0.248886[/C][C]1.7063[/C][C]0.047279[/C][/ROW]
[ROW][C]3[/C][C]0.011231[/C][C]0.077[/C][C]0.469477[/C][/ROW]
[ROW][C]4[/C][C]0.104011[/C][C]0.7131[/C][C]0.239667[/C][/ROW]
[ROW][C]5[/C][C]-0.141768[/C][C]-0.9719[/C][C]0.168034[/C][/ROW]
[ROW][C]6[/C][C]-0.015503[/C][C]-0.1063[/C][C]0.457906[/C][/ROW]
[ROW][C]7[/C][C]0.087016[/C][C]0.5965[/C][C]0.276836[/C][/ROW]
[ROW][C]8[/C][C]-0.007894[/C][C]-0.0541[/C][C]0.478536[/C][/ROW]
[ROW][C]9[/C][C]0.169669[/C][C]1.1632[/C][C]0.125312[/C][/ROW]
[ROW][C]10[/C][C]-0.016689[/C][C]-0.1144[/C][C]0.454698[/C][/ROW]
[ROW][C]11[/C][C]0.387829[/C][C]2.6588[/C][C]0.005343[/C][/ROW]
[ROW][C]12[/C][C]-0.146045[/C][C]-1.0012[/C][C]0.16092[/C][/ROW]
[ROW][C]13[/C][C]0.074794[/C][C]0.5128[/C][C]0.30526[/C][/ROW]
[ROW][C]14[/C][C]0.002643[/C][C]0.0181[/C][C]0.492811[/C][/ROW]
[ROW][C]15[/C][C]0.08558[/C][C]0.5867[/C][C]0.280105[/C][/ROW]
[ROW][C]16[/C][C]-0.131765[/C][C]-0.9033[/C][C]0.185478[/C][/ROW]
[ROW][C]17[/C][C]0.045016[/C][C]0.3086[/C][C]0.379488[/C][/ROW]
[ROW][C]18[/C][C]-0.11598[/C][C]-0.7951[/C][C]0.215271[/C][/ROW]
[ROW][C]19[/C][C]-0.147198[/C][C]-1.0091[/C][C]0.159038[/C][/ROW]
[ROW][C]20[/C][C]-0.01036[/C][C]-0.071[/C][C]0.471839[/C][/ROW]
[ROW][C]21[/C][C]-0.129017[/C][C]-0.8845[/C][C]0.190466[/C][/ROW]
[ROW][C]22[/C][C]0.041202[/C][C]0.2825[/C][C]0.389412[/C][/ROW]
[ROW][C]23[/C][C]-0.113336[/C][C]-0.777[/C][C]0.220528[/C][/ROW]
[ROW][C]24[/C][C]-0.010141[/C][C]-0.0695[/C][C]0.472435[/C][/ROW]
[ROW][C]25[/C][C]-0.015372[/C][C]-0.1054[/C][C]0.45826[/C][/ROW]
[ROW][C]26[/C][C]0.015331[/C][C]0.1051[/C][C]0.458371[/C][/ROW]
[ROW][C]27[/C][C]-0.137593[/C][C]-0.9433[/C][C]0.175178[/C][/ROW]
[ROW][C]28[/C][C]-0.147615[/C][C]-1.012[/C][C]0.15836[/C][/ROW]
[ROW][C]29[/C][C]-0.137223[/C][C]-0.9408[/C][C]0.175821[/C][/ROW]
[ROW][C]30[/C][C]-0.073034[/C][C]-0.5007[/C][C]0.30946[/C][/ROW]
[ROW][C]31[/C][C]-0.028427[/C][C]-0.1949[/C][C]0.423162[/C][/ROW]
[ROW][C]32[/C][C]-0.049958[/C][C]-0.3425[/C][C]0.366752[/C][/ROW]
[ROW][C]33[/C][C]0.003607[/C][C]0.0247[/C][C]0.490189[/C][/ROW]
[ROW][C]34[/C][C]-0.022039[/C][C]-0.1511[/C][C]0.440275[/C][/ROW]
[ROW][C]35[/C][C]-0.011699[/C][C]-0.0802[/C][C]0.468208[/C][/ROW]
[ROW][C]36[/C][C]-0.021773[/C][C]-0.1493[/C][C]0.44099[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60710&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60710&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
10.0279950.19190.424315
20.2488861.70630.047279
30.0112310.0770.469477
40.1040110.71310.239667
5-0.141768-0.97190.168034
6-0.015503-0.10630.457906
70.0870160.59650.276836
8-0.007894-0.05410.478536
90.1696691.16320.125312
10-0.016689-0.11440.454698
110.3878292.65880.005343
12-0.146045-1.00120.16092
130.0747940.51280.30526
140.0026430.01810.492811
150.085580.58670.280105
16-0.131765-0.90330.185478
170.0450160.30860.379488
18-0.11598-0.79510.215271
19-0.147198-1.00910.159038
20-0.01036-0.0710.471839
21-0.129017-0.88450.190466
220.0412020.28250.389412
23-0.113336-0.7770.220528
24-0.010141-0.06950.472435
25-0.015372-0.10540.45826
260.0153310.10510.458371
27-0.137593-0.94330.175178
28-0.147615-1.0120.15836
29-0.137223-0.94080.175821
30-0.073034-0.50070.30946
31-0.028427-0.19490.423162
32-0.049958-0.34250.366752
330.0036070.02470.490189
34-0.022039-0.15110.440275
35-0.011699-0.08020.468208
36-0.021773-0.14930.44099






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0279950.19190.424315
20.2482971.70220.047659
3-0.001021-0.0070.497222
40.0447920.30710.380071
5-0.157539-1.080.142819
6-0.048314-0.33120.370973
70.1723921.18190.121603
80.0025760.01770.492991
90.1503911.0310.153902
10-0.057763-0.3960.346948
110.3254662.23130.015235
12-0.1691-1.15930.126096
13-0.096007-0.65820.256813
140.1164290.79820.214386
150.0413010.28310.389155
16-0.06077-0.41660.339428
17-0.013471-0.09240.463405
18-0.229836-1.57570.060904
19-0.107012-0.73360.233408
200.0169060.11590.454113
21-0.065391-0.44830.327998
22-0.06227-0.42690.335699
230.0072030.04940.480413
24-0.092615-0.63490.264273
250.0304370.20870.417806
26-0.007974-0.05470.478319
27-0.031725-0.21750.414381
28-0.21282-1.4590.075605
290.0082740.05670.477504
300.147581.01180.158417
31-0.026562-0.18210.428145
320.0209320.14350.443253
33-0.012834-0.0880.465132
34-0.038499-0.26390.39649
350.0994080.68150.249447
36-0.020496-0.14050.444427

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.027995 & 0.1919 & 0.424315 \tabularnewline
2 & 0.248297 & 1.7022 & 0.047659 \tabularnewline
3 & -0.001021 & -0.007 & 0.497222 \tabularnewline
4 & 0.044792 & 0.3071 & 0.380071 \tabularnewline
5 & -0.157539 & -1.08 & 0.142819 \tabularnewline
6 & -0.048314 & -0.3312 & 0.370973 \tabularnewline
7 & 0.172392 & 1.1819 & 0.121603 \tabularnewline
8 & 0.002576 & 0.0177 & 0.492991 \tabularnewline
9 & 0.150391 & 1.031 & 0.153902 \tabularnewline
10 & -0.057763 & -0.396 & 0.346948 \tabularnewline
11 & 0.325466 & 2.2313 & 0.015235 \tabularnewline
12 & -0.1691 & -1.1593 & 0.126096 \tabularnewline
13 & -0.096007 & -0.6582 & 0.256813 \tabularnewline
14 & 0.116429 & 0.7982 & 0.214386 \tabularnewline
15 & 0.041301 & 0.2831 & 0.389155 \tabularnewline
16 & -0.06077 & -0.4166 & 0.339428 \tabularnewline
17 & -0.013471 & -0.0924 & 0.463405 \tabularnewline
18 & -0.229836 & -1.5757 & 0.060904 \tabularnewline
19 & -0.107012 & -0.7336 & 0.233408 \tabularnewline
20 & 0.016906 & 0.1159 & 0.454113 \tabularnewline
21 & -0.065391 & -0.4483 & 0.327998 \tabularnewline
22 & -0.06227 & -0.4269 & 0.335699 \tabularnewline
23 & 0.007203 & 0.0494 & 0.480413 \tabularnewline
24 & -0.092615 & -0.6349 & 0.264273 \tabularnewline
25 & 0.030437 & 0.2087 & 0.417806 \tabularnewline
26 & -0.007974 & -0.0547 & 0.478319 \tabularnewline
27 & -0.031725 & -0.2175 & 0.414381 \tabularnewline
28 & -0.21282 & -1.459 & 0.075605 \tabularnewline
29 & 0.008274 & 0.0567 & 0.477504 \tabularnewline
30 & 0.14758 & 1.0118 & 0.158417 \tabularnewline
31 & -0.026562 & -0.1821 & 0.428145 \tabularnewline
32 & 0.020932 & 0.1435 & 0.443253 \tabularnewline
33 & -0.012834 & -0.088 & 0.465132 \tabularnewline
34 & -0.038499 & -0.2639 & 0.39649 \tabularnewline
35 & 0.099408 & 0.6815 & 0.249447 \tabularnewline
36 & -0.020496 & -0.1405 & 0.444427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60710&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]0.027995[/C][C]0.1919[/C][C]0.424315[/C][/ROW]
[ROW][C]2[/C][C]0.248297[/C][C]1.7022[/C][C]0.047659[/C][/ROW]
[ROW][C]3[/C][C]-0.001021[/C][C]-0.007[/C][C]0.497222[/C][/ROW]
[ROW][C]4[/C][C]0.044792[/C][C]0.3071[/C][C]0.380071[/C][/ROW]
[ROW][C]5[/C][C]-0.157539[/C][C]-1.08[/C][C]0.142819[/C][/ROW]
[ROW][C]6[/C][C]-0.048314[/C][C]-0.3312[/C][C]0.370973[/C][/ROW]
[ROW][C]7[/C][C]0.172392[/C][C]1.1819[/C][C]0.121603[/C][/ROW]
[ROW][C]8[/C][C]0.002576[/C][C]0.0177[/C][C]0.492991[/C][/ROW]
[ROW][C]9[/C][C]0.150391[/C][C]1.031[/C][C]0.153902[/C][/ROW]
[ROW][C]10[/C][C]-0.057763[/C][C]-0.396[/C][C]0.346948[/C][/ROW]
[ROW][C]11[/C][C]0.325466[/C][C]2.2313[/C][C]0.015235[/C][/ROW]
[ROW][C]12[/C][C]-0.1691[/C][C]-1.1593[/C][C]0.126096[/C][/ROW]
[ROW][C]13[/C][C]-0.096007[/C][C]-0.6582[/C][C]0.256813[/C][/ROW]
[ROW][C]14[/C][C]0.116429[/C][C]0.7982[/C][C]0.214386[/C][/ROW]
[ROW][C]15[/C][C]0.041301[/C][C]0.2831[/C][C]0.389155[/C][/ROW]
[ROW][C]16[/C][C]-0.06077[/C][C]-0.4166[/C][C]0.339428[/C][/ROW]
[ROW][C]17[/C][C]-0.013471[/C][C]-0.0924[/C][C]0.463405[/C][/ROW]
[ROW][C]18[/C][C]-0.229836[/C][C]-1.5757[/C][C]0.060904[/C][/ROW]
[ROW][C]19[/C][C]-0.107012[/C][C]-0.7336[/C][C]0.233408[/C][/ROW]
[ROW][C]20[/C][C]0.016906[/C][C]0.1159[/C][C]0.454113[/C][/ROW]
[ROW][C]21[/C][C]-0.065391[/C][C]-0.4483[/C][C]0.327998[/C][/ROW]
[ROW][C]22[/C][C]-0.06227[/C][C]-0.4269[/C][C]0.335699[/C][/ROW]
[ROW][C]23[/C][C]0.007203[/C][C]0.0494[/C][C]0.480413[/C][/ROW]
[ROW][C]24[/C][C]-0.092615[/C][C]-0.6349[/C][C]0.264273[/C][/ROW]
[ROW][C]25[/C][C]0.030437[/C][C]0.2087[/C][C]0.417806[/C][/ROW]
[ROW][C]26[/C][C]-0.007974[/C][C]-0.0547[/C][C]0.478319[/C][/ROW]
[ROW][C]27[/C][C]-0.031725[/C][C]-0.2175[/C][C]0.414381[/C][/ROW]
[ROW][C]28[/C][C]-0.21282[/C][C]-1.459[/C][C]0.075605[/C][/ROW]
[ROW][C]29[/C][C]0.008274[/C][C]0.0567[/C][C]0.477504[/C][/ROW]
[ROW][C]30[/C][C]0.14758[/C][C]1.0118[/C][C]0.158417[/C][/ROW]
[ROW][C]31[/C][C]-0.026562[/C][C]-0.1821[/C][C]0.428145[/C][/ROW]
[ROW][C]32[/C][C]0.020932[/C][C]0.1435[/C][C]0.443253[/C][/ROW]
[ROW][C]33[/C][C]-0.012834[/C][C]-0.088[/C][C]0.465132[/C][/ROW]
[ROW][C]34[/C][C]-0.038499[/C][C]-0.2639[/C][C]0.39649[/C][/ROW]
[ROW][C]35[/C][C]0.099408[/C][C]0.6815[/C][C]0.249447[/C][/ROW]
[ROW][C]36[/C][C]-0.020496[/C][C]-0.1405[/C][C]0.444427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60710&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60710&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
10.0279950.19190.424315
20.2482971.70220.047659
3-0.001021-0.0070.497222
40.0447920.30710.380071
5-0.157539-1.080.142819
6-0.048314-0.33120.370973
70.1723921.18190.121603
80.0025760.01770.492991
90.1503911.0310.153902
10-0.057763-0.3960.346948
110.3254662.23130.015235
12-0.1691-1.15930.126096
13-0.096007-0.65820.256813
140.1164290.79820.214386
150.0413010.28310.389155
16-0.06077-0.41660.339428
17-0.013471-0.09240.463405
18-0.229836-1.57570.060904
19-0.107012-0.73360.233408
200.0169060.11590.454113
21-0.065391-0.44830.327998
22-0.06227-0.42690.335699
230.0072030.04940.480413
24-0.092615-0.63490.264273
250.0304370.20870.417806
26-0.007974-0.05470.478319
27-0.031725-0.21750.414381
28-0.21282-1.4590.075605
290.0082740.05670.477504
300.147581.01180.158417
31-0.026562-0.18210.428145
320.0209320.14350.443253
33-0.012834-0.0880.465132
34-0.038499-0.26390.39649
350.0994080.68150.249447
36-0.020496-0.14050.444427


Figures (Output of Computation)

Input Parameters & R Code

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')