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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 computationMon, 22 Nov 2010 15:02:03 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/22/t129043818951jxyhfciv0bp5u.htm/, Retrieved Fri, 03 May 2024 17:46:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98570, Retrieved Fri, 03 May 2024 17:46:15 +0000
QR Codes:

Original text written by user:Dit is dus de juiste blog met betrekking tot oefening 2 stap 2 MVG Nicolas Norga
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean versus Median] [opdracht 5 oefeni...] [2010-10-19 09:27:19] [544c47be79b2f5f4be445678c64cc68d]
- RMPD    [(Partial) Autocorrelation Function] [opdracht 6 bis oe...] [2010-11-22 15:02:03] [72a344459e5b13eacf7bf474aa92c893] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
132.1
125
127.1
101.5
85.7
79.3
70.9
77.1
83.9
96.2
111.7
127.2
143.6
134.9
135.6
105.3
86.4
74.6
67.6
73.4
78.5
98.2
118.6
136.9
137.9
115.6
119.3
98.5
84.3
73.5
60.7
69.5
77.9
113.9
126.3
135.1
130.5
113.1
110
90.8
85.4
72.5
64.7
67.2
77.9
105.2
107.2
120.7
121.3
107.9
105.6
81.3
71.7
64.8
57.3
61.9
70.1
88.8
106.8
110.7
114.1
108
111.5
86.8
78.4
68
57.3
65.3
73.3
88.6
101.3
122.9
126.6
114.1
124.7
93.3
77.2
66.5
57.9
63.7
65.8
85
101
105.3
121
117.9
106
86.6
79.9
65.2
61.2
67.6
78.9
95.5
113.1
124.4
122
110.3
114
93.3
75.5
65.4
59.2
63.8
74.2
91.7
107
120.7
127.4
119.7
112.7
84.4
75.6
66.5
59.9
64.8
74.3
100.4
105.9
131.1

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98570&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98570&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98570&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'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5294165.50190
20.2416112.51090.006762
30.2247042.33520.010691
40.110261.14590.127193
50.0464820.48310.315016
60.0603030.62670.266095
70.0604020.62770.265756
8-0.041744-0.43380.332644
9-0.032674-0.33960.367423
100.1132171.17660.120974
11-0.014295-0.14860.441091
12-0.310766-3.22960.000821
13-0.162817-1.6920.04676
14-0.112621-1.17040.122209
15-0.260876-2.71110.003902
16-0.135714-1.41040.080651
17-0.075518-0.78480.217144
18-0.048717-0.50630.306847
190.0223130.23190.408535
200.1687691.75390.041142
210.2301292.39160.009253
220.0544350.56570.286384
230.0043240.04490.482119
240.0359430.37350.354743
25-0.045157-0.46930.319906
26-0.003239-0.03370.486606
270.1571491.63310.052675
280.0779330.80990.209887
290.1075851.11810.133011
300.1414221.46970.072275
310.1057321.09880.13715
320.039020.40550.342953
33-0.097664-1.0150.156197
34-0.035223-0.3660.357522
35-0.069616-0.72350.235477
36-0.158967-1.6520.050716

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.529416 & 5.5019 & 0 \tabularnewline
2 & 0.241611 & 2.5109 & 0.006762 \tabularnewline
3 & 0.224704 & 2.3352 & 0.010691 \tabularnewline
4 & 0.11026 & 1.1459 & 0.127193 \tabularnewline
5 & 0.046482 & 0.4831 & 0.315016 \tabularnewline
6 & 0.060303 & 0.6267 & 0.266095 \tabularnewline
7 & 0.060402 & 0.6277 & 0.265756 \tabularnewline
8 & -0.041744 & -0.4338 & 0.332644 \tabularnewline
9 & -0.032674 & -0.3396 & 0.367423 \tabularnewline
10 & 0.113217 & 1.1766 & 0.120974 \tabularnewline
11 & -0.014295 & -0.1486 & 0.441091 \tabularnewline
12 & -0.310766 & -3.2296 & 0.000821 \tabularnewline
13 & -0.162817 & -1.692 & 0.04676 \tabularnewline
14 & -0.112621 & -1.1704 & 0.122209 \tabularnewline
15 & -0.260876 & -2.7111 & 0.003902 \tabularnewline
16 & -0.135714 & -1.4104 & 0.080651 \tabularnewline
17 & -0.075518 & -0.7848 & 0.217144 \tabularnewline
18 & -0.048717 & -0.5063 & 0.306847 \tabularnewline
19 & 0.022313 & 0.2319 & 0.408535 \tabularnewline
20 & 0.168769 & 1.7539 & 0.041142 \tabularnewline
21 & 0.230129 & 2.3916 & 0.009253 \tabularnewline
22 & 0.054435 & 0.5657 & 0.286384 \tabularnewline
23 & 0.004324 & 0.0449 & 0.482119 \tabularnewline
24 & 0.035943 & 0.3735 & 0.354743 \tabularnewline
25 & -0.045157 & -0.4693 & 0.319906 \tabularnewline
26 & -0.003239 & -0.0337 & 0.486606 \tabularnewline
27 & 0.157149 & 1.6331 & 0.052675 \tabularnewline
28 & 0.077933 & 0.8099 & 0.209887 \tabularnewline
29 & 0.107585 & 1.1181 & 0.133011 \tabularnewline
30 & 0.141422 & 1.4697 & 0.072275 \tabularnewline
31 & 0.105732 & 1.0988 & 0.13715 \tabularnewline
32 & 0.03902 & 0.4055 & 0.342953 \tabularnewline
33 & -0.097664 & -1.015 & 0.156197 \tabularnewline
34 & -0.035223 & -0.366 & 0.357522 \tabularnewline
35 & -0.069616 & -0.7235 & 0.235477 \tabularnewline
36 & -0.158967 & -1.652 & 0.050716 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98570&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]0.529416[/C][C]5.5019[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.241611[/C][C]2.5109[/C][C]0.006762[/C][/ROW]
[ROW][C]3[/C][C]0.224704[/C][C]2.3352[/C][C]0.010691[/C][/ROW]
[ROW][C]4[/C][C]0.11026[/C][C]1.1459[/C][C]0.127193[/C][/ROW]
[ROW][C]5[/C][C]0.046482[/C][C]0.4831[/C][C]0.315016[/C][/ROW]
[ROW][C]6[/C][C]0.060303[/C][C]0.6267[/C][C]0.266095[/C][/ROW]
[ROW][C]7[/C][C]0.060402[/C][C]0.6277[/C][C]0.265756[/C][/ROW]
[ROW][C]8[/C][C]-0.041744[/C][C]-0.4338[/C][C]0.332644[/C][/ROW]
[ROW][C]9[/C][C]-0.032674[/C][C]-0.3396[/C][C]0.367423[/C][/ROW]
[ROW][C]10[/C][C]0.113217[/C][C]1.1766[/C][C]0.120974[/C][/ROW]
[ROW][C]11[/C][C]-0.014295[/C][C]-0.1486[/C][C]0.441091[/C][/ROW]
[ROW][C]12[/C][C]-0.310766[/C][C]-3.2296[/C][C]0.000821[/C][/ROW]
[ROW][C]13[/C][C]-0.162817[/C][C]-1.692[/C][C]0.04676[/C][/ROW]
[ROW][C]14[/C][C]-0.112621[/C][C]-1.1704[/C][C]0.122209[/C][/ROW]
[ROW][C]15[/C][C]-0.260876[/C][C]-2.7111[/C][C]0.003902[/C][/ROW]
[ROW][C]16[/C][C]-0.135714[/C][C]-1.4104[/C][C]0.080651[/C][/ROW]
[ROW][C]17[/C][C]-0.075518[/C][C]-0.7848[/C][C]0.217144[/C][/ROW]
[ROW][C]18[/C][C]-0.048717[/C][C]-0.5063[/C][C]0.306847[/C][/ROW]
[ROW][C]19[/C][C]0.022313[/C][C]0.2319[/C][C]0.408535[/C][/ROW]
[ROW][C]20[/C][C]0.168769[/C][C]1.7539[/C][C]0.041142[/C][/ROW]
[ROW][C]21[/C][C]0.230129[/C][C]2.3916[/C][C]0.009253[/C][/ROW]
[ROW][C]22[/C][C]0.054435[/C][C]0.5657[/C][C]0.286384[/C][/ROW]
[ROW][C]23[/C][C]0.004324[/C][C]0.0449[/C][C]0.482119[/C][/ROW]
[ROW][C]24[/C][C]0.035943[/C][C]0.3735[/C][C]0.354743[/C][/ROW]
[ROW][C]25[/C][C]-0.045157[/C][C]-0.4693[/C][C]0.319906[/C][/ROW]
[ROW][C]26[/C][C]-0.003239[/C][C]-0.0337[/C][C]0.486606[/C][/ROW]
[ROW][C]27[/C][C]0.157149[/C][C]1.6331[/C][C]0.052675[/C][/ROW]
[ROW][C]28[/C][C]0.077933[/C][C]0.8099[/C][C]0.209887[/C][/ROW]
[ROW][C]29[/C][C]0.107585[/C][C]1.1181[/C][C]0.133011[/C][/ROW]
[ROW][C]30[/C][C]0.141422[/C][C]1.4697[/C][C]0.072275[/C][/ROW]
[ROW][C]31[/C][C]0.105732[/C][C]1.0988[/C][C]0.13715[/C][/ROW]
[ROW][C]32[/C][C]0.03902[/C][C]0.4055[/C][C]0.342953[/C][/ROW]
[ROW][C]33[/C][C]-0.097664[/C][C]-1.015[/C][C]0.156197[/C][/ROW]
[ROW][C]34[/C][C]-0.035223[/C][C]-0.366[/C][C]0.357522[/C][/ROW]
[ROW][C]35[/C][C]-0.069616[/C][C]-0.7235[/C][C]0.235477[/C][/ROW]
[ROW][C]36[/C][C]-0.158967[/C][C]-1.652[/C][C]0.050716[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98570&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98570&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
10.5294165.50190
20.2416112.51090.006762
30.2247042.33520.010691
40.110261.14590.127193
50.0464820.48310.315016
60.0603030.62670.266095
70.0604020.62770.265756
8-0.041744-0.43380.332644
9-0.032674-0.33960.367423
100.1132171.17660.120974
11-0.014295-0.14860.441091
12-0.310766-3.22960.000821
13-0.162817-1.6920.04676
14-0.112621-1.17040.122209
15-0.260876-2.71110.003902
16-0.135714-1.41040.080651
17-0.075518-0.78480.217144
18-0.048717-0.50630.306847
190.0223130.23190.408535
200.1687691.75390.041142
210.2301292.39160.009253
220.0544350.56570.286384
230.0043240.04490.482119
240.0359430.37350.354743
25-0.045157-0.46930.319906
26-0.003239-0.03370.486606
270.1571491.63310.052675
280.0779330.80990.209887
290.1075851.11810.133011
300.1414221.46970.072275
310.1057321.09880.13715
320.039020.40550.342953
33-0.097664-1.0150.156197
34-0.035223-0.3660.357522
35-0.069616-0.72350.235477
36-0.158967-1.6520.050716






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5294165.50190
2-0.05373-0.55840.288872
30.1649341.7140.044695
4-0.099111-1.030.152658
50.0249360.25910.398011
60.021760.22610.41076
70.0270730.28140.389489
8-0.122118-1.26910.10357
90.0490680.50990.305569
100.1577471.63940.052025
11-0.187204-1.94550.027158
12-0.357982-3.72030.000159
130.2201122.28750.012058
14-0.070021-0.72770.234192
15-0.196033-2.03720.022036
160.117921.22550.111534
17-0.023499-0.24420.403767
180.1251771.30090.098034
190.0568560.59090.277921
200.0891340.92630.178176
210.1438961.49540.068862
22-0.050792-0.52780.299344
23-0.149056-1.5490.062149
24-0.118569-1.23220.110275
250.1165081.21080.11431
260.0263320.27360.392439
27-0.012948-0.13460.446604
28-0.032679-0.33960.367404
290.1798311.86890.032176
30-0.060665-0.63040.264866
31-0.02489-0.25870.398193
320.0337680.35090.363163
33-0.019764-0.20540.418827
340.0822870.85510.197181
35-0.136185-1.41530.079932
36-0.147686-1.53480.063879

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.529416 & 5.5019 & 0 \tabularnewline
2 & -0.05373 & -0.5584 & 0.288872 \tabularnewline
3 & 0.164934 & 1.714 & 0.044695 \tabularnewline
4 & -0.099111 & -1.03 & 0.152658 \tabularnewline
5 & 0.024936 & 0.2591 & 0.398011 \tabularnewline
6 & 0.02176 & 0.2261 & 0.41076 \tabularnewline
7 & 0.027073 & 0.2814 & 0.389489 \tabularnewline
8 & -0.122118 & -1.2691 & 0.10357 \tabularnewline
9 & 0.049068 & 0.5099 & 0.305569 \tabularnewline
10 & 0.157747 & 1.6394 & 0.052025 \tabularnewline
11 & -0.187204 & -1.9455 & 0.027158 \tabularnewline
12 & -0.357982 & -3.7203 & 0.000159 \tabularnewline
13 & 0.220112 & 2.2875 & 0.012058 \tabularnewline
14 & -0.070021 & -0.7277 & 0.234192 \tabularnewline
15 & -0.196033 & -2.0372 & 0.022036 \tabularnewline
16 & 0.11792 & 1.2255 & 0.111534 \tabularnewline
17 & -0.023499 & -0.2442 & 0.403767 \tabularnewline
18 & 0.125177 & 1.3009 & 0.098034 \tabularnewline
19 & 0.056856 & 0.5909 & 0.277921 \tabularnewline
20 & 0.089134 & 0.9263 & 0.178176 \tabularnewline
21 & 0.143896 & 1.4954 & 0.068862 \tabularnewline
22 & -0.050792 & -0.5278 & 0.299344 \tabularnewline
23 & -0.149056 & -1.549 & 0.062149 \tabularnewline
24 & -0.118569 & -1.2322 & 0.110275 \tabularnewline
25 & 0.116508 & 1.2108 & 0.11431 \tabularnewline
26 & 0.026332 & 0.2736 & 0.392439 \tabularnewline
27 & -0.012948 & -0.1346 & 0.446604 \tabularnewline
28 & -0.032679 & -0.3396 & 0.367404 \tabularnewline
29 & 0.179831 & 1.8689 & 0.032176 \tabularnewline
30 & -0.060665 & -0.6304 & 0.264866 \tabularnewline
31 & -0.02489 & -0.2587 & 0.398193 \tabularnewline
32 & 0.033768 & 0.3509 & 0.363163 \tabularnewline
33 & -0.019764 & -0.2054 & 0.418827 \tabularnewline
34 & 0.082287 & 0.8551 & 0.197181 \tabularnewline
35 & -0.136185 & -1.4153 & 0.079932 \tabularnewline
36 & -0.147686 & -1.5348 & 0.063879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98570&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]0.529416[/C][C]5.5019[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.05373[/C][C]-0.5584[/C][C]0.288872[/C][/ROW]
[ROW][C]3[/C][C]0.164934[/C][C]1.714[/C][C]0.044695[/C][/ROW]
[ROW][C]4[/C][C]-0.099111[/C][C]-1.03[/C][C]0.152658[/C][/ROW]
[ROW][C]5[/C][C]0.024936[/C][C]0.2591[/C][C]0.398011[/C][/ROW]
[ROW][C]6[/C][C]0.02176[/C][C]0.2261[/C][C]0.41076[/C][/ROW]
[ROW][C]7[/C][C]0.027073[/C][C]0.2814[/C][C]0.389489[/C][/ROW]
[ROW][C]8[/C][C]-0.122118[/C][C]-1.2691[/C][C]0.10357[/C][/ROW]
[ROW][C]9[/C][C]0.049068[/C][C]0.5099[/C][C]0.305569[/C][/ROW]
[ROW][C]10[/C][C]0.157747[/C][C]1.6394[/C][C]0.052025[/C][/ROW]
[ROW][C]11[/C][C]-0.187204[/C][C]-1.9455[/C][C]0.027158[/C][/ROW]
[ROW][C]12[/C][C]-0.357982[/C][C]-3.7203[/C][C]0.000159[/C][/ROW]
[ROW][C]13[/C][C]0.220112[/C][C]2.2875[/C][C]0.012058[/C][/ROW]
[ROW][C]14[/C][C]-0.070021[/C][C]-0.7277[/C][C]0.234192[/C][/ROW]
[ROW][C]15[/C][C]-0.196033[/C][C]-2.0372[/C][C]0.022036[/C][/ROW]
[ROW][C]16[/C][C]0.11792[/C][C]1.2255[/C][C]0.111534[/C][/ROW]
[ROW][C]17[/C][C]-0.023499[/C][C]-0.2442[/C][C]0.403767[/C][/ROW]
[ROW][C]18[/C][C]0.125177[/C][C]1.3009[/C][C]0.098034[/C][/ROW]
[ROW][C]19[/C][C]0.056856[/C][C]0.5909[/C][C]0.277921[/C][/ROW]
[ROW][C]20[/C][C]0.089134[/C][C]0.9263[/C][C]0.178176[/C][/ROW]
[ROW][C]21[/C][C]0.143896[/C][C]1.4954[/C][C]0.068862[/C][/ROW]
[ROW][C]22[/C][C]-0.050792[/C][C]-0.5278[/C][C]0.299344[/C][/ROW]
[ROW][C]23[/C][C]-0.149056[/C][C]-1.549[/C][C]0.062149[/C][/ROW]
[ROW][C]24[/C][C]-0.118569[/C][C]-1.2322[/C][C]0.110275[/C][/ROW]
[ROW][C]25[/C][C]0.116508[/C][C]1.2108[/C][C]0.11431[/C][/ROW]
[ROW][C]26[/C][C]0.026332[/C][C]0.2736[/C][C]0.392439[/C][/ROW]
[ROW][C]27[/C][C]-0.012948[/C][C]-0.1346[/C][C]0.446604[/C][/ROW]
[ROW][C]28[/C][C]-0.032679[/C][C]-0.3396[/C][C]0.367404[/C][/ROW]
[ROW][C]29[/C][C]0.179831[/C][C]1.8689[/C][C]0.032176[/C][/ROW]
[ROW][C]30[/C][C]-0.060665[/C][C]-0.6304[/C][C]0.264866[/C][/ROW]
[ROW][C]31[/C][C]-0.02489[/C][C]-0.2587[/C][C]0.398193[/C][/ROW]
[ROW][C]32[/C][C]0.033768[/C][C]0.3509[/C][C]0.363163[/C][/ROW]
[ROW][C]33[/C][C]-0.019764[/C][C]-0.2054[/C][C]0.418827[/C][/ROW]
[ROW][C]34[/C][C]0.082287[/C][C]0.8551[/C][C]0.197181[/C][/ROW]
[ROW][C]35[/C][C]-0.136185[/C][C]-1.4153[/C][C]0.079932[/C][/ROW]
[ROW][C]36[/C][C]-0.147686[/C][C]-1.5348[/C][C]0.063879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98570&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98570&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
10.5294165.50190
2-0.05373-0.55840.288872
30.1649341.7140.044695
4-0.099111-1.030.152658
50.0249360.25910.398011
60.021760.22610.41076
70.0270730.28140.389489
8-0.122118-1.26910.10357
90.0490680.50990.305569
100.1577471.63940.052025
11-0.187204-1.94550.027158
12-0.357982-3.72030.000159
130.2201122.28750.012058
14-0.070021-0.72770.234192
15-0.196033-2.03720.022036
160.117921.22550.111534
17-0.023499-0.24420.403767
180.1251771.30090.098034
190.0568560.59090.277921
200.0891340.92630.178176
210.1438961.49540.068862
22-0.050792-0.52780.299344
23-0.149056-1.5490.062149
24-0.118569-1.23220.110275
250.1165081.21080.11431
260.0263320.27360.392439
27-0.012948-0.13460.446604
28-0.032679-0.33960.367404
290.1798311.86890.032176
30-0.060665-0.63040.264866
31-0.02489-0.25870.398193
320.0337680.35090.363163
33-0.019764-0.20540.418827
340.0822870.85510.197181
35-0.136185-1.41530.079932
36-0.147686-1.53480.063879


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')