FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSat, 26 Dec 2009 11:28:28 -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/26/t1261852210m8m0yqp1jm58ucr.htm/, Retrieved Sun, 28 Apr 2024 19:50:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70767, Retrieved Sun, 28 Apr 2024 19:50:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [paper ind pr ACF 2] [2009-12-23 19:41:43] [af8eb90b4bf1bcfcc4325c143dbee260]
-   PD            [(Partial) Autocorrelation Function] [paper] [2009-12-26 18:28:28] [ac4f1d4b47349b2602192853b2bc5b72] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70767&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]8 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=70767&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70767&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 time8 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0254840.15290.439664
20.3284711.97080.028235
30.2221171.33270.095501
40.1752021.05120.150084
50.2449061.46940.0752
60.0640770.38450.351449
70.1218790.73130.234673
80.113130.67880.250809
90.0701480.42090.338169
100.0440780.26450.396463
11-0.001609-0.00970.496176
12-0.064506-0.3870.350504
130.0772440.46350.32291
14-0.118672-0.7120.240518
150.0073910.04430.482437
16-0.107076-0.64250.262324
17-0.014468-0.08680.465652
18-0.012958-0.07770.469229
19-0.063819-0.38290.352018
20-0.09752-0.58510.281059
21-0.009358-0.05620.477766
22-0.204027-1.22420.114422
230.074510.44710.328754
24-0.23844-1.43060.080578
25-0.142707-0.85620.198763
26-0.066423-0.39850.346293
27-0.187465-1.12480.134062
28-0.079276-0.47570.318597
29-0.18231-1.09390.140641
30-0.03444-0.20660.418729
31-0.126471-0.75880.226449
32-0.153221-0.91930.182022
33-0.108711-0.65230.259186
34-0.045959-0.27580.392158
35-0.009203-0.05520.478135
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.025484 & 0.1529 & 0.439664 \tabularnewline
2 & 0.328471 & 1.9708 & 0.028235 \tabularnewline
3 & 0.222117 & 1.3327 & 0.095501 \tabularnewline
4 & 0.175202 & 1.0512 & 0.150084 \tabularnewline
5 & 0.244906 & 1.4694 & 0.0752 \tabularnewline
6 & 0.064077 & 0.3845 & 0.351449 \tabularnewline
7 & 0.121879 & 0.7313 & 0.234673 \tabularnewline
8 & 0.11313 & 0.6788 & 0.250809 \tabularnewline
9 & 0.070148 & 0.4209 & 0.338169 \tabularnewline
10 & 0.044078 & 0.2645 & 0.396463 \tabularnewline
11 & -0.001609 & -0.0097 & 0.496176 \tabularnewline
12 & -0.064506 & -0.387 & 0.350504 \tabularnewline
13 & 0.077244 & 0.4635 & 0.32291 \tabularnewline
14 & -0.118672 & -0.712 & 0.240518 \tabularnewline
15 & 0.007391 & 0.0443 & 0.482437 \tabularnewline
16 & -0.107076 & -0.6425 & 0.262324 \tabularnewline
17 & -0.014468 & -0.0868 & 0.465652 \tabularnewline
18 & -0.012958 & -0.0777 & 0.469229 \tabularnewline
19 & -0.063819 & -0.3829 & 0.352018 \tabularnewline
20 & -0.09752 & -0.5851 & 0.281059 \tabularnewline
21 & -0.009358 & -0.0562 & 0.477766 \tabularnewline
22 & -0.204027 & -1.2242 & 0.114422 \tabularnewline
23 & 0.07451 & 0.4471 & 0.328754 \tabularnewline
24 & -0.23844 & -1.4306 & 0.080578 \tabularnewline
25 & -0.142707 & -0.8562 & 0.198763 \tabularnewline
26 & -0.066423 & -0.3985 & 0.346293 \tabularnewline
27 & -0.187465 & -1.1248 & 0.134062 \tabularnewline
28 & -0.079276 & -0.4757 & 0.318597 \tabularnewline
29 & -0.18231 & -1.0939 & 0.140641 \tabularnewline
30 & -0.03444 & -0.2066 & 0.418729 \tabularnewline
31 & -0.126471 & -0.7588 & 0.226449 \tabularnewline
32 & -0.153221 & -0.9193 & 0.182022 \tabularnewline
33 & -0.108711 & -0.6523 & 0.259186 \tabularnewline
34 & -0.045959 & -0.2758 & 0.392158 \tabularnewline
35 & -0.009203 & -0.0552 & 0.478135 \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70767&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]0.025484[/C][C]0.1529[/C][C]0.439664[/C][/ROW]
[ROW][C]2[/C][C]0.328471[/C][C]1.9708[/C][C]0.028235[/C][/ROW]
[ROW][C]3[/C][C]0.222117[/C][C]1.3327[/C][C]0.095501[/C][/ROW]
[ROW][C]4[/C][C]0.175202[/C][C]1.0512[/C][C]0.150084[/C][/ROW]
[ROW][C]5[/C][C]0.244906[/C][C]1.4694[/C][C]0.0752[/C][/ROW]
[ROW][C]6[/C][C]0.064077[/C][C]0.3845[/C][C]0.351449[/C][/ROW]
[ROW][C]7[/C][C]0.121879[/C][C]0.7313[/C][C]0.234673[/C][/ROW]
[ROW][C]8[/C][C]0.11313[/C][C]0.6788[/C][C]0.250809[/C][/ROW]
[ROW][C]9[/C][C]0.070148[/C][C]0.4209[/C][C]0.338169[/C][/ROW]
[ROW][C]10[/C][C]0.044078[/C][C]0.2645[/C][C]0.396463[/C][/ROW]
[ROW][C]11[/C][C]-0.001609[/C][C]-0.0097[/C][C]0.496176[/C][/ROW]
[ROW][C]12[/C][C]-0.064506[/C][C]-0.387[/C][C]0.350504[/C][/ROW]
[ROW][C]13[/C][C]0.077244[/C][C]0.4635[/C][C]0.32291[/C][/ROW]
[ROW][C]14[/C][C]-0.118672[/C][C]-0.712[/C][C]0.240518[/C][/ROW]
[ROW][C]15[/C][C]0.007391[/C][C]0.0443[/C][C]0.482437[/C][/ROW]
[ROW][C]16[/C][C]-0.107076[/C][C]-0.6425[/C][C]0.262324[/C][/ROW]
[ROW][C]17[/C][C]-0.014468[/C][C]-0.0868[/C][C]0.465652[/C][/ROW]
[ROW][C]18[/C][C]-0.012958[/C][C]-0.0777[/C][C]0.469229[/C][/ROW]
[ROW][C]19[/C][C]-0.063819[/C][C]-0.3829[/C][C]0.352018[/C][/ROW]
[ROW][C]20[/C][C]-0.09752[/C][C]-0.5851[/C][C]0.281059[/C][/ROW]
[ROW][C]21[/C][C]-0.009358[/C][C]-0.0562[/C][C]0.477766[/C][/ROW]
[ROW][C]22[/C][C]-0.204027[/C][C]-1.2242[/C][C]0.114422[/C][/ROW]
[ROW][C]23[/C][C]0.07451[/C][C]0.4471[/C][C]0.328754[/C][/ROW]
[ROW][C]24[/C][C]-0.23844[/C][C]-1.4306[/C][C]0.080578[/C][/ROW]
[ROW][C]25[/C][C]-0.142707[/C][C]-0.8562[/C][C]0.198763[/C][/ROW]
[ROW][C]26[/C][C]-0.066423[/C][C]-0.3985[/C][C]0.346293[/C][/ROW]
[ROW][C]27[/C][C]-0.187465[/C][C]-1.1248[/C][C]0.134062[/C][/ROW]
[ROW][C]28[/C][C]-0.079276[/C][C]-0.4757[/C][C]0.318597[/C][/ROW]
[ROW][C]29[/C][C]-0.18231[/C][C]-1.0939[/C][C]0.140641[/C][/ROW]
[ROW][C]30[/C][C]-0.03444[/C][C]-0.2066[/C][C]0.418729[/C][/ROW]
[ROW][C]31[/C][C]-0.126471[/C][C]-0.7588[/C][C]0.226449[/C][/ROW]
[ROW][C]32[/C][C]-0.153221[/C][C]-0.9193[/C][C]0.182022[/C][/ROW]
[ROW][C]33[/C][C]-0.108711[/C][C]-0.6523[/C][C]0.259186[/C][/ROW]
[ROW][C]34[/C][C]-0.045959[/C][C]-0.2758[/C][C]0.392158[/C][/ROW]
[ROW][C]35[/C][C]-0.009203[/C][C]-0.0552[/C][C]0.478135[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70767&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70767&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
10.0254840.15290.439664
20.3284711.97080.028235
30.2221171.33270.095501
40.1752021.05120.150084
50.2449061.46940.0752
60.0640770.38450.351449
70.1218790.73130.234673
80.113130.67880.250809
90.0701480.42090.338169
100.0440780.26450.396463
11-0.001609-0.00970.496176
12-0.064506-0.3870.350504
130.0772440.46350.32291
14-0.118672-0.7120.240518
150.0073910.04430.482437
16-0.107076-0.64250.262324
17-0.014468-0.08680.465652
18-0.012958-0.07770.469229
19-0.063819-0.38290.352018
20-0.09752-0.58510.281059
21-0.009358-0.05620.477766
22-0.204027-1.22420.114422
230.074510.44710.328754
24-0.23844-1.43060.080578
25-0.142707-0.85620.198763
26-0.066423-0.39850.346293
27-0.187465-1.12480.134062
28-0.079276-0.47570.318597
29-0.18231-1.09390.140641
30-0.03444-0.20660.418729
31-0.126471-0.75880.226449
32-0.153221-0.91930.182022
33-0.108711-0.65230.259186
34-0.045959-0.27580.392158
35-0.009203-0.05520.478135
36NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0254840.15290.439664
20.3280351.96820.028391
30.2333821.40030.084993
40.090150.54090.295954
50.1348680.80920.211855
6-0.048784-0.29270.385715
7-0.050716-0.30430.381326
80.023030.13820.445434
90.0091020.05460.478374
10-0.041869-0.25120.401539
11-0.063545-0.38130.352622
12-0.131423-0.78850.217772
130.0646730.3880.350136
14-0.063129-0.37880.35354
150.0050890.03050.487904
16-0.056522-0.33910.368241
170.0283530.17010.432935
180.0454340.27260.393357
190.0203860.12230.451663
20-0.098298-0.58980.279508
210.0221310.13280.447551
22-0.189735-1.13840.131234
230.1117460.67050.253417
24-0.1401-0.84060.20306
25-0.141643-0.84990.200511
26-0.024078-0.14450.442967
27-0.015228-0.09140.463853
28-0.04284-0.2570.399306
290.0092730.05560.477969
300.0738750.44320.330119
31-0.015148-0.09090.464042
32-0.118139-0.70880.241497
33-0.029294-0.17580.430733
340.0517940.31080.378887
350.1502980.90180.186582
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.025484 & 0.1529 & 0.439664 \tabularnewline
2 & 0.328035 & 1.9682 & 0.028391 \tabularnewline
3 & 0.233382 & 1.4003 & 0.084993 \tabularnewline
4 & 0.09015 & 0.5409 & 0.295954 \tabularnewline
5 & 0.134868 & 0.8092 & 0.211855 \tabularnewline
6 & -0.048784 & -0.2927 & 0.385715 \tabularnewline
7 & -0.050716 & -0.3043 & 0.381326 \tabularnewline
8 & 0.02303 & 0.1382 & 0.445434 \tabularnewline
9 & 0.009102 & 0.0546 & 0.478374 \tabularnewline
10 & -0.041869 & -0.2512 & 0.401539 \tabularnewline
11 & -0.063545 & -0.3813 & 0.352622 \tabularnewline
12 & -0.131423 & -0.7885 & 0.217772 \tabularnewline
13 & 0.064673 & 0.388 & 0.350136 \tabularnewline
14 & -0.063129 & -0.3788 & 0.35354 \tabularnewline
15 & 0.005089 & 0.0305 & 0.487904 \tabularnewline
16 & -0.056522 & -0.3391 & 0.368241 \tabularnewline
17 & 0.028353 & 0.1701 & 0.432935 \tabularnewline
18 & 0.045434 & 0.2726 & 0.393357 \tabularnewline
19 & 0.020386 & 0.1223 & 0.451663 \tabularnewline
20 & -0.098298 & -0.5898 & 0.279508 \tabularnewline
21 & 0.022131 & 0.1328 & 0.447551 \tabularnewline
22 & -0.189735 & -1.1384 & 0.131234 \tabularnewline
23 & 0.111746 & 0.6705 & 0.253417 \tabularnewline
24 & -0.1401 & -0.8406 & 0.20306 \tabularnewline
25 & -0.141643 & -0.8499 & 0.200511 \tabularnewline
26 & -0.024078 & -0.1445 & 0.442967 \tabularnewline
27 & -0.015228 & -0.0914 & 0.463853 \tabularnewline
28 & -0.04284 & -0.257 & 0.399306 \tabularnewline
29 & 0.009273 & 0.0556 & 0.477969 \tabularnewline
30 & 0.073875 & 0.4432 & 0.330119 \tabularnewline
31 & -0.015148 & -0.0909 & 0.464042 \tabularnewline
32 & -0.118139 & -0.7088 & 0.241497 \tabularnewline
33 & -0.029294 & -0.1758 & 0.430733 \tabularnewline
34 & 0.051794 & 0.3108 & 0.378887 \tabularnewline
35 & 0.150298 & 0.9018 & 0.186582 \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70767&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]0.025484[/C][C]0.1529[/C][C]0.439664[/C][/ROW]
[ROW][C]2[/C][C]0.328035[/C][C]1.9682[/C][C]0.028391[/C][/ROW]
[ROW][C]3[/C][C]0.233382[/C][C]1.4003[/C][C]0.084993[/C][/ROW]
[ROW][C]4[/C][C]0.09015[/C][C]0.5409[/C][C]0.295954[/C][/ROW]
[ROW][C]5[/C][C]0.134868[/C][C]0.8092[/C][C]0.211855[/C][/ROW]
[ROW][C]6[/C][C]-0.048784[/C][C]-0.2927[/C][C]0.385715[/C][/ROW]
[ROW][C]7[/C][C]-0.050716[/C][C]-0.3043[/C][C]0.381326[/C][/ROW]
[ROW][C]8[/C][C]0.02303[/C][C]0.1382[/C][C]0.445434[/C][/ROW]
[ROW][C]9[/C][C]0.009102[/C][C]0.0546[/C][C]0.478374[/C][/ROW]
[ROW][C]10[/C][C]-0.041869[/C][C]-0.2512[/C][C]0.401539[/C][/ROW]
[ROW][C]11[/C][C]-0.063545[/C][C]-0.3813[/C][C]0.352622[/C][/ROW]
[ROW][C]12[/C][C]-0.131423[/C][C]-0.7885[/C][C]0.217772[/C][/ROW]
[ROW][C]13[/C][C]0.064673[/C][C]0.388[/C][C]0.350136[/C][/ROW]
[ROW][C]14[/C][C]-0.063129[/C][C]-0.3788[/C][C]0.35354[/C][/ROW]
[ROW][C]15[/C][C]0.005089[/C][C]0.0305[/C][C]0.487904[/C][/ROW]
[ROW][C]16[/C][C]-0.056522[/C][C]-0.3391[/C][C]0.368241[/C][/ROW]
[ROW][C]17[/C][C]0.028353[/C][C]0.1701[/C][C]0.432935[/C][/ROW]
[ROW][C]18[/C][C]0.045434[/C][C]0.2726[/C][C]0.393357[/C][/ROW]
[ROW][C]19[/C][C]0.020386[/C][C]0.1223[/C][C]0.451663[/C][/ROW]
[ROW][C]20[/C][C]-0.098298[/C][C]-0.5898[/C][C]0.279508[/C][/ROW]
[ROW][C]21[/C][C]0.022131[/C][C]0.1328[/C][C]0.447551[/C][/ROW]
[ROW][C]22[/C][C]-0.189735[/C][C]-1.1384[/C][C]0.131234[/C][/ROW]
[ROW][C]23[/C][C]0.111746[/C][C]0.6705[/C][C]0.253417[/C][/ROW]
[ROW][C]24[/C][C]-0.1401[/C][C]-0.8406[/C][C]0.20306[/C][/ROW]
[ROW][C]25[/C][C]-0.141643[/C][C]-0.8499[/C][C]0.200511[/C][/ROW]
[ROW][C]26[/C][C]-0.024078[/C][C]-0.1445[/C][C]0.442967[/C][/ROW]
[ROW][C]27[/C][C]-0.015228[/C][C]-0.0914[/C][C]0.463853[/C][/ROW]
[ROW][C]28[/C][C]-0.04284[/C][C]-0.257[/C][C]0.399306[/C][/ROW]
[ROW][C]29[/C][C]0.009273[/C][C]0.0556[/C][C]0.477969[/C][/ROW]
[ROW][C]30[/C][C]0.073875[/C][C]0.4432[/C][C]0.330119[/C][/ROW]
[ROW][C]31[/C][C]-0.015148[/C][C]-0.0909[/C][C]0.464042[/C][/ROW]
[ROW][C]32[/C][C]-0.118139[/C][C]-0.7088[/C][C]0.241497[/C][/ROW]
[ROW][C]33[/C][C]-0.029294[/C][C]-0.1758[/C][C]0.430733[/C][/ROW]
[ROW][C]34[/C][C]0.051794[/C][C]0.3108[/C][C]0.378887[/C][/ROW]
[ROW][C]35[/C][C]0.150298[/C][C]0.9018[/C][C]0.186582[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70767&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70767&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
10.0254840.15290.439664
20.3280351.96820.028391
30.2333821.40030.084993
40.090150.54090.295954
50.1348680.80920.211855
6-0.048784-0.29270.385715
7-0.050716-0.30430.381326
80.023030.13820.445434
90.0091020.05460.478374
10-0.041869-0.25120.401539
11-0.063545-0.38130.352622
12-0.131423-0.78850.217772
130.0646730.3880.350136
14-0.063129-0.37880.35354
150.0050890.03050.487904
16-0.056522-0.33910.368241
170.0283530.17010.432935
180.0454340.27260.393357
190.0203860.12230.451663
20-0.098298-0.58980.279508
210.0221310.13280.447551
22-0.189735-1.13840.131234
230.1117460.67050.253417
24-0.1401-0.84060.20306
25-0.141643-0.84990.200511
26-0.024078-0.14450.442967
27-0.015228-0.09140.463853
28-0.04284-0.2570.399306
290.0092730.05560.477969
300.0738750.44320.330119
31-0.015148-0.09090.464042
32-0.118139-0.70880.241497
33-0.029294-0.17580.430733
340.0517940.31080.378887
350.1502980.90180.186582
36NANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; 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')