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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 computationSun, 29 Nov 2009 08:11:12 -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/29/t1259507542iawf8aems47afsz.htm/, Retrieved Thu, 25 Apr 2024 05:16:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61624, Retrieved Thu, 25 Apr 2024 05:16:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

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] [Shwws8_v1] [2009-11-27 19:01:50] [5f89c040fdf1f8599c99d7f78a662321]
-   PD            [(Partial) Autocorrelation Function] [Review WS 8 autoc...] [2009-11-29 15:11:12] [51d49d3536f6a59f2486a67bf50b2759] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.1
102.86
102.99
103.73
105.02
104.43
104.63
104.93
105.87
105.66
106.76
106
107.22
107.33
107.11
108.86
107.72
107.88
108.38
107.72
108.41
109.9
111.45
112.18
113.34
113.46
114.06
115.54
116.39
115.94
116.97
115.94
115.91
116.43
116.26
116.35
117.9
117.7
117.53
117.86
117.65
116.51
115.93
115.31
115

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=61624&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=61624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61624&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
10.9471836.35390
20.8972546.0190
30.8397575.63331e-06
40.7761925.20692e-06
50.718494.81988e-06
60.6532214.38193.5e-05
70.5832763.91270.000153
80.513523.44480.000624
90.4484733.00840.002145
100.380682.55370.007059
110.3206272.15080.018448
120.2520641.69090.048886
130.1874071.25720.107591
140.1220150.81850.208692
150.0487060.32670.372695
16-0.012128-0.08140.467759
17-0.081843-0.5490.292854
18-0.146833-0.9850.164949
19-0.207791-1.39390.085096
20-0.269797-1.80990.0385
21-0.327259-2.19530.01667
22-0.371126-2.48960.008276
23-0.400678-2.68780.005023
24-0.420659-2.82190.003541
25-0.430833-2.89010.002954
26-0.437582-2.93540.002615
27-0.444494-2.98180.002307
28-0.438669-2.94270.002564
29-0.424888-2.85020.003285
30-0.418592-2.8080.003673
31-0.398154-2.67090.005246
32-0.384314-2.57810.00664
33-0.372112-2.49620.008142
34-0.351525-2.35810.011387
35-0.333533-2.23740.015129
36-0.311768-2.09140.021084

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947183 & 6.3539 & 0 \tabularnewline
2 & 0.897254 & 6.019 & 0 \tabularnewline
3 & 0.839757 & 5.6333 & 1e-06 \tabularnewline
4 & 0.776192 & 5.2069 & 2e-06 \tabularnewline
5 & 0.71849 & 4.8198 & 8e-06 \tabularnewline
6 & 0.653221 & 4.3819 & 3.5e-05 \tabularnewline
7 & 0.583276 & 3.9127 & 0.000153 \tabularnewline
8 & 0.51352 & 3.4448 & 0.000624 \tabularnewline
9 & 0.448473 & 3.0084 & 0.002145 \tabularnewline
10 & 0.38068 & 2.5537 & 0.007059 \tabularnewline
11 & 0.320627 & 2.1508 & 0.018448 \tabularnewline
12 & 0.252064 & 1.6909 & 0.048886 \tabularnewline
13 & 0.187407 & 1.2572 & 0.107591 \tabularnewline
14 & 0.122015 & 0.8185 & 0.208692 \tabularnewline
15 & 0.048706 & 0.3267 & 0.372695 \tabularnewline
16 & -0.012128 & -0.0814 & 0.467759 \tabularnewline
17 & -0.081843 & -0.549 & 0.292854 \tabularnewline
18 & -0.146833 & -0.985 & 0.164949 \tabularnewline
19 & -0.207791 & -1.3939 & 0.085096 \tabularnewline
20 & -0.269797 & -1.8099 & 0.0385 \tabularnewline
21 & -0.327259 & -2.1953 & 0.01667 \tabularnewline
22 & -0.371126 & -2.4896 & 0.008276 \tabularnewline
23 & -0.400678 & -2.6878 & 0.005023 \tabularnewline
24 & -0.420659 & -2.8219 & 0.003541 \tabularnewline
25 & -0.430833 & -2.8901 & 0.002954 \tabularnewline
26 & -0.437582 & -2.9354 & 0.002615 \tabularnewline
27 & -0.444494 & -2.9818 & 0.002307 \tabularnewline
28 & -0.438669 & -2.9427 & 0.002564 \tabularnewline
29 & -0.424888 & -2.8502 & 0.003285 \tabularnewline
30 & -0.418592 & -2.808 & 0.003673 \tabularnewline
31 & -0.398154 & -2.6709 & 0.005246 \tabularnewline
32 & -0.384314 & -2.5781 & 0.00664 \tabularnewline
33 & -0.372112 & -2.4962 & 0.008142 \tabularnewline
34 & -0.351525 & -2.3581 & 0.011387 \tabularnewline
35 & -0.333533 & -2.2374 & 0.015129 \tabularnewline
36 & -0.311768 & -2.0914 & 0.021084 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61624&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]0.947183[/C][C]6.3539[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.897254[/C][C]6.019[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.839757[/C][C]5.6333[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.776192[/C][C]5.2069[/C][C]2e-06[/C][/ROW]
[ROW][C]5[/C][C]0.71849[/C][C]4.8198[/C][C]8e-06[/C][/ROW]
[ROW][C]6[/C][C]0.653221[/C][C]4.3819[/C][C]3.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.583276[/C][C]3.9127[/C][C]0.000153[/C][/ROW]
[ROW][C]8[/C][C]0.51352[/C][C]3.4448[/C][C]0.000624[/C][/ROW]
[ROW][C]9[/C][C]0.448473[/C][C]3.0084[/C][C]0.002145[/C][/ROW]
[ROW][C]10[/C][C]0.38068[/C][C]2.5537[/C][C]0.007059[/C][/ROW]
[ROW][C]11[/C][C]0.320627[/C][C]2.1508[/C][C]0.018448[/C][/ROW]
[ROW][C]12[/C][C]0.252064[/C][C]1.6909[/C][C]0.048886[/C][/ROW]
[ROW][C]13[/C][C]0.187407[/C][C]1.2572[/C][C]0.107591[/C][/ROW]
[ROW][C]14[/C][C]0.122015[/C][C]0.8185[/C][C]0.208692[/C][/ROW]
[ROW][C]15[/C][C]0.048706[/C][C]0.3267[/C][C]0.372695[/C][/ROW]
[ROW][C]16[/C][C]-0.012128[/C][C]-0.0814[/C][C]0.467759[/C][/ROW]
[ROW][C]17[/C][C]-0.081843[/C][C]-0.549[/C][C]0.292854[/C][/ROW]
[ROW][C]18[/C][C]-0.146833[/C][C]-0.985[/C][C]0.164949[/C][/ROW]
[ROW][C]19[/C][C]-0.207791[/C][C]-1.3939[/C][C]0.085096[/C][/ROW]
[ROW][C]20[/C][C]-0.269797[/C][C]-1.8099[/C][C]0.0385[/C][/ROW]
[ROW][C]21[/C][C]-0.327259[/C][C]-2.1953[/C][C]0.01667[/C][/ROW]
[ROW][C]22[/C][C]-0.371126[/C][C]-2.4896[/C][C]0.008276[/C][/ROW]
[ROW][C]23[/C][C]-0.400678[/C][C]-2.6878[/C][C]0.005023[/C][/ROW]
[ROW][C]24[/C][C]-0.420659[/C][C]-2.8219[/C][C]0.003541[/C][/ROW]
[ROW][C]25[/C][C]-0.430833[/C][C]-2.8901[/C][C]0.002954[/C][/ROW]
[ROW][C]26[/C][C]-0.437582[/C][C]-2.9354[/C][C]0.002615[/C][/ROW]
[ROW][C]27[/C][C]-0.444494[/C][C]-2.9818[/C][C]0.002307[/C][/ROW]
[ROW][C]28[/C][C]-0.438669[/C][C]-2.9427[/C][C]0.002564[/C][/ROW]
[ROW][C]29[/C][C]-0.424888[/C][C]-2.8502[/C][C]0.003285[/C][/ROW]
[ROW][C]30[/C][C]-0.418592[/C][C]-2.808[/C][C]0.003673[/C][/ROW]
[ROW][C]31[/C][C]-0.398154[/C][C]-2.6709[/C][C]0.005246[/C][/ROW]
[ROW][C]32[/C][C]-0.384314[/C][C]-2.5781[/C][C]0.00664[/C][/ROW]
[ROW][C]33[/C][C]-0.372112[/C][C]-2.4962[/C][C]0.008142[/C][/ROW]
[ROW][C]34[/C][C]-0.351525[/C][C]-2.3581[/C][C]0.011387[/C][/ROW]
[ROW][C]35[/C][C]-0.333533[/C][C]-2.2374[/C][C]0.015129[/C][/ROW]
[ROW][C]36[/C][C]-0.311768[/C][C]-2.0914[/C][C]0.021084[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61624&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61624&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
10.9471836.35390
20.8972546.0190
30.8397575.63331e-06
40.7761925.20692e-06
50.718494.81988e-06
60.6532214.38193.5e-05
70.5832763.91270.000153
80.513523.44480.000624
90.4484733.00840.002145
100.380682.55370.007059
110.3206272.15080.018448
120.2520641.69090.048886
130.1874071.25720.107591
140.1220150.81850.208692
150.0487060.32670.372695
16-0.012128-0.08140.467759
17-0.081843-0.5490.292854
18-0.146833-0.9850.164949
19-0.207791-1.39390.085096
20-0.269797-1.80990.0385
21-0.327259-2.19530.01667
22-0.371126-2.48960.008276
23-0.400678-2.68780.005023
24-0.420659-2.82190.003541
25-0.430833-2.89010.002954
26-0.437582-2.93540.002615
27-0.444494-2.98180.002307
28-0.438669-2.94270.002564
29-0.424888-2.85020.003285
30-0.418592-2.8080.003673
31-0.398154-2.67090.005246
32-0.384314-2.57810.00664
33-0.372112-2.49620.008142
34-0.351525-2.35810.011387
35-0.333533-2.23740.015129
36-0.311768-2.09140.021084






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9471836.35390
20.0009560.00640.497456
3-0.099171-0.66530.254639
4-0.094831-0.63610.263951
50.0232450.15590.438393
6-0.096582-0.64790.260174
7-0.095199-0.63860.263156
8-0.04335-0.29080.386269
90.0186050.12480.450617
10-0.072035-0.48320.315638
110.0177440.1190.452891
12-0.12245-0.82140.20787
13-0.017478-0.11720.453592
14-0.067809-0.45490.325692
15-0.130425-0.87490.193133
160.035810.24020.405626
17-0.127972-0.85850.197594
18-0.037903-0.25430.400226
19-0.036689-0.24610.403354
20-0.072636-0.48730.314221
21-0.047446-0.31830.375873
220.0490360.32890.371862
230.0923010.61920.269462
240.0315450.21160.416684
250.0090870.0610.475832
260.0161710.10850.45705
27-0.091338-0.61270.271574
280.0790460.53030.29927
290.0399960.26830.394846
30-0.139606-0.93650.177006
310.1201570.8060.21223
32-0.090487-0.6070.27345
33-0.053837-0.36120.359838
340.0274070.18390.427478
35-0.052983-0.35540.361968
36-0.007271-0.04880.480658

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947183 & 6.3539 & 0 \tabularnewline
2 & 0.000956 & 0.0064 & 0.497456 \tabularnewline
3 & -0.099171 & -0.6653 & 0.254639 \tabularnewline
4 & -0.094831 & -0.6361 & 0.263951 \tabularnewline
5 & 0.023245 & 0.1559 & 0.438393 \tabularnewline
6 & -0.096582 & -0.6479 & 0.260174 \tabularnewline
7 & -0.095199 & -0.6386 & 0.263156 \tabularnewline
8 & -0.04335 & -0.2908 & 0.386269 \tabularnewline
9 & 0.018605 & 0.1248 & 0.450617 \tabularnewline
10 & -0.072035 & -0.4832 & 0.315638 \tabularnewline
11 & 0.017744 & 0.119 & 0.452891 \tabularnewline
12 & -0.12245 & -0.8214 & 0.20787 \tabularnewline
13 & -0.017478 & -0.1172 & 0.453592 \tabularnewline
14 & -0.067809 & -0.4549 & 0.325692 \tabularnewline
15 & -0.130425 & -0.8749 & 0.193133 \tabularnewline
16 & 0.03581 & 0.2402 & 0.405626 \tabularnewline
17 & -0.127972 & -0.8585 & 0.197594 \tabularnewline
18 & -0.037903 & -0.2543 & 0.400226 \tabularnewline
19 & -0.036689 & -0.2461 & 0.403354 \tabularnewline
20 & -0.072636 & -0.4873 & 0.314221 \tabularnewline
21 & -0.047446 & -0.3183 & 0.375873 \tabularnewline
22 & 0.049036 & 0.3289 & 0.371862 \tabularnewline
23 & 0.092301 & 0.6192 & 0.269462 \tabularnewline
24 & 0.031545 & 0.2116 & 0.416684 \tabularnewline
25 & 0.009087 & 0.061 & 0.475832 \tabularnewline
26 & 0.016171 & 0.1085 & 0.45705 \tabularnewline
27 & -0.091338 & -0.6127 & 0.271574 \tabularnewline
28 & 0.079046 & 0.5303 & 0.29927 \tabularnewline
29 & 0.039996 & 0.2683 & 0.394846 \tabularnewline
30 & -0.139606 & -0.9365 & 0.177006 \tabularnewline
31 & 0.120157 & 0.806 & 0.21223 \tabularnewline
32 & -0.090487 & -0.607 & 0.27345 \tabularnewline
33 & -0.053837 & -0.3612 & 0.359838 \tabularnewline
34 & 0.027407 & 0.1839 & 0.427478 \tabularnewline
35 & -0.052983 & -0.3554 & 0.361968 \tabularnewline
36 & -0.007271 & -0.0488 & 0.480658 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61624&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]0.947183[/C][C]6.3539[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.000956[/C][C]0.0064[/C][C]0.497456[/C][/ROW]
[ROW][C]3[/C][C]-0.099171[/C][C]-0.6653[/C][C]0.254639[/C][/ROW]
[ROW][C]4[/C][C]-0.094831[/C][C]-0.6361[/C][C]0.263951[/C][/ROW]
[ROW][C]5[/C][C]0.023245[/C][C]0.1559[/C][C]0.438393[/C][/ROW]
[ROW][C]6[/C][C]-0.096582[/C][C]-0.6479[/C][C]0.260174[/C][/ROW]
[ROW][C]7[/C][C]-0.095199[/C][C]-0.6386[/C][C]0.263156[/C][/ROW]
[ROW][C]8[/C][C]-0.04335[/C][C]-0.2908[/C][C]0.386269[/C][/ROW]
[ROW][C]9[/C][C]0.018605[/C][C]0.1248[/C][C]0.450617[/C][/ROW]
[ROW][C]10[/C][C]-0.072035[/C][C]-0.4832[/C][C]0.315638[/C][/ROW]
[ROW][C]11[/C][C]0.017744[/C][C]0.119[/C][C]0.452891[/C][/ROW]
[ROW][C]12[/C][C]-0.12245[/C][C]-0.8214[/C][C]0.20787[/C][/ROW]
[ROW][C]13[/C][C]-0.017478[/C][C]-0.1172[/C][C]0.453592[/C][/ROW]
[ROW][C]14[/C][C]-0.067809[/C][C]-0.4549[/C][C]0.325692[/C][/ROW]
[ROW][C]15[/C][C]-0.130425[/C][C]-0.8749[/C][C]0.193133[/C][/ROW]
[ROW][C]16[/C][C]0.03581[/C][C]0.2402[/C][C]0.405626[/C][/ROW]
[ROW][C]17[/C][C]-0.127972[/C][C]-0.8585[/C][C]0.197594[/C][/ROW]
[ROW][C]18[/C][C]-0.037903[/C][C]-0.2543[/C][C]0.400226[/C][/ROW]
[ROW][C]19[/C][C]-0.036689[/C][C]-0.2461[/C][C]0.403354[/C][/ROW]
[ROW][C]20[/C][C]-0.072636[/C][C]-0.4873[/C][C]0.314221[/C][/ROW]
[ROW][C]21[/C][C]-0.047446[/C][C]-0.3183[/C][C]0.375873[/C][/ROW]
[ROW][C]22[/C][C]0.049036[/C][C]0.3289[/C][C]0.371862[/C][/ROW]
[ROW][C]23[/C][C]0.092301[/C][C]0.6192[/C][C]0.269462[/C][/ROW]
[ROW][C]24[/C][C]0.031545[/C][C]0.2116[/C][C]0.416684[/C][/ROW]
[ROW][C]25[/C][C]0.009087[/C][C]0.061[/C][C]0.475832[/C][/ROW]
[ROW][C]26[/C][C]0.016171[/C][C]0.1085[/C][C]0.45705[/C][/ROW]
[ROW][C]27[/C][C]-0.091338[/C][C]-0.6127[/C][C]0.271574[/C][/ROW]
[ROW][C]28[/C][C]0.079046[/C][C]0.5303[/C][C]0.29927[/C][/ROW]
[ROW][C]29[/C][C]0.039996[/C][C]0.2683[/C][C]0.394846[/C][/ROW]
[ROW][C]30[/C][C]-0.139606[/C][C]-0.9365[/C][C]0.177006[/C][/ROW]
[ROW][C]31[/C][C]0.120157[/C][C]0.806[/C][C]0.21223[/C][/ROW]
[ROW][C]32[/C][C]-0.090487[/C][C]-0.607[/C][C]0.27345[/C][/ROW]
[ROW][C]33[/C][C]-0.053837[/C][C]-0.3612[/C][C]0.359838[/C][/ROW]
[ROW][C]34[/C][C]0.027407[/C][C]0.1839[/C][C]0.427478[/C][/ROW]
[ROW][C]35[/C][C]-0.052983[/C][C]-0.3554[/C][C]0.361968[/C][/ROW]
[ROW][C]36[/C][C]-0.007271[/C][C]-0.0488[/C][C]0.480658[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61624&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61624&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
10.9471836.35390
20.0009560.00640.497456
3-0.099171-0.66530.254639
4-0.094831-0.63610.263951
50.0232450.15590.438393
6-0.096582-0.64790.260174
7-0.095199-0.63860.263156
8-0.04335-0.29080.386269
90.0186050.12480.450617
10-0.072035-0.48320.315638
110.0177440.1190.452891
12-0.12245-0.82140.20787
13-0.017478-0.11720.453592
14-0.067809-0.45490.325692
15-0.130425-0.87490.193133
160.035810.24020.405626
17-0.127972-0.85850.197594
18-0.037903-0.25430.400226
19-0.036689-0.24610.403354
20-0.072636-0.48730.314221
21-0.047446-0.31830.375873
220.0490360.32890.371862
230.0923010.61920.269462
240.0315450.21160.416684
250.0090870.0610.475832
260.0161710.10850.45705
27-0.091338-0.61270.271574
280.0790460.53030.29927
290.0399960.26830.394846
30-0.139606-0.93650.177006
310.1201570.8060.21223
32-0.090487-0.6070.27345
33-0.053837-0.36120.359838
340.0274070.18390.427478
35-0.052983-0.35540.361968
36-0.007271-0.04880.480658


Figures (Output of Computation)

Input Parameters & R Code

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