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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 computationThu, 26 Nov 2009 16:50:07 -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/t1259279659uy2eo9tnofcref4.htm/, Retrieved Sun, 28 Apr 2024 19:34:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60450, Retrieved Sun, 28 Apr 2024 19:34:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

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]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-26 23:50:07] [90c9838c596c9c0a7d0d4c412ffe5b98] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-12 20:45:42] [0e3da40906c04c6abfe5eb434331b3f1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6802.96
7132.68
7073.29
7264.5
7105.33
7218.71
7225.72
7354.25
7745.46
8070.26
8366.33
8667.51
8854.34
9218.1
9332.9
9358.31
9248.66
9401.2
9652.04
9957.38
10110.63
10169.26
10343.78
10750.21
11337.5
11786.96
12083.04
12007.74
11745.93
11051.51
11445.9
11924.88
12247.63
12690.91
12910.7
13202.12
13654.67
13862.82
13523.93
14211.17
14510.35
14289.23
14111.82
13086.59
13351.54
13747.69
12855.61
12926.93
12121.95
11731.65
11639.51
12163.78
12029.53
11234.18
9852.13
9709.04
9332.75
7108.6
6691.49
6143.05

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=60450&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=60450&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60450&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
10.9268137.17910
20.8491266.57730
30.7666045.93810
40.7037785.45140
50.6360954.92723e-06
60.5595754.33442.8e-05
70.4952043.83580.000151
80.4391953.4020.000598
90.3823632.96180.002189
100.3166092.45240.008557
110.2525191.9560.027562
120.1843671.42810.079224
130.1265380.98020.165471
140.0701180.54310.294525
150.0180420.13980.444663
16-0.040815-0.31620.376491
17-0.107632-0.83370.203875
18-0.156577-1.21280.114972
19-0.192933-1.49450.070149
20-0.222739-1.72530.044808
21-0.251999-1.9520.027806
22-0.285936-2.21490.015289
23-0.307662-2.38310.010174
24-0.321315-2.48890.007803
25-0.328783-2.54670.006728
26-0.335169-2.59620.005918
27-0.338742-2.62390.005504
28-0.347341-2.69050.004614
29-0.364336-2.82210.003231
30-0.393428-3.04750.001714
31-0.420706-3.25880.000922
32-0.429498-3.32690.000752
33-0.426814-3.30618e-04
34-0.410992-3.18350.001153
35-0.390386-3.02390.001834
36-0.365195-2.82880.003172

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.926813 & 7.1791 & 0 \tabularnewline
2 & 0.849126 & 6.5773 & 0 \tabularnewline
3 & 0.766604 & 5.9381 & 0 \tabularnewline
4 & 0.703778 & 5.4514 & 0 \tabularnewline
5 & 0.636095 & 4.9272 & 3e-06 \tabularnewline
6 & 0.559575 & 4.3344 & 2.8e-05 \tabularnewline
7 & 0.495204 & 3.8358 & 0.000151 \tabularnewline
8 & 0.439195 & 3.402 & 0.000598 \tabularnewline
9 & 0.382363 & 2.9618 & 0.002189 \tabularnewline
10 & 0.316609 & 2.4524 & 0.008557 \tabularnewline
11 & 0.252519 & 1.956 & 0.027562 \tabularnewline
12 & 0.184367 & 1.4281 & 0.079224 \tabularnewline
13 & 0.126538 & 0.9802 & 0.165471 \tabularnewline
14 & 0.070118 & 0.5431 & 0.294525 \tabularnewline
15 & 0.018042 & 0.1398 & 0.444663 \tabularnewline
16 & -0.040815 & -0.3162 & 0.376491 \tabularnewline
17 & -0.107632 & -0.8337 & 0.203875 \tabularnewline
18 & -0.156577 & -1.2128 & 0.114972 \tabularnewline
19 & -0.192933 & -1.4945 & 0.070149 \tabularnewline
20 & -0.222739 & -1.7253 & 0.044808 \tabularnewline
21 & -0.251999 & -1.952 & 0.027806 \tabularnewline
22 & -0.285936 & -2.2149 & 0.015289 \tabularnewline
23 & -0.307662 & -2.3831 & 0.010174 \tabularnewline
24 & -0.321315 & -2.4889 & 0.007803 \tabularnewline
25 & -0.328783 & -2.5467 & 0.006728 \tabularnewline
26 & -0.335169 & -2.5962 & 0.005918 \tabularnewline
27 & -0.338742 & -2.6239 & 0.005504 \tabularnewline
28 & -0.347341 & -2.6905 & 0.004614 \tabularnewline
29 & -0.364336 & -2.8221 & 0.003231 \tabularnewline
30 & -0.393428 & -3.0475 & 0.001714 \tabularnewline
31 & -0.420706 & -3.2588 & 0.000922 \tabularnewline
32 & -0.429498 & -3.3269 & 0.000752 \tabularnewline
33 & -0.426814 & -3.3061 & 8e-04 \tabularnewline
34 & -0.410992 & -3.1835 & 0.001153 \tabularnewline
35 & -0.390386 & -3.0239 & 0.001834 \tabularnewline
36 & -0.365195 & -2.8288 & 0.003172 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60450&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]0.926813[/C][C]7.1791[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.849126[/C][C]6.5773[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.766604[/C][C]5.9381[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.703778[/C][C]5.4514[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.636095[/C][C]4.9272[/C][C]3e-06[/C][/ROW]
[ROW][C]6[/C][C]0.559575[/C][C]4.3344[/C][C]2.8e-05[/C][/ROW]
[ROW][C]7[/C][C]0.495204[/C][C]3.8358[/C][C]0.000151[/C][/ROW]
[ROW][C]8[/C][C]0.439195[/C][C]3.402[/C][C]0.000598[/C][/ROW]
[ROW][C]9[/C][C]0.382363[/C][C]2.9618[/C][C]0.002189[/C][/ROW]
[ROW][C]10[/C][C]0.316609[/C][C]2.4524[/C][C]0.008557[/C][/ROW]
[ROW][C]11[/C][C]0.252519[/C][C]1.956[/C][C]0.027562[/C][/ROW]
[ROW][C]12[/C][C]0.184367[/C][C]1.4281[/C][C]0.079224[/C][/ROW]
[ROW][C]13[/C][C]0.126538[/C][C]0.9802[/C][C]0.165471[/C][/ROW]
[ROW][C]14[/C][C]0.070118[/C][C]0.5431[/C][C]0.294525[/C][/ROW]
[ROW][C]15[/C][C]0.018042[/C][C]0.1398[/C][C]0.444663[/C][/ROW]
[ROW][C]16[/C][C]-0.040815[/C][C]-0.3162[/C][C]0.376491[/C][/ROW]
[ROW][C]17[/C][C]-0.107632[/C][C]-0.8337[/C][C]0.203875[/C][/ROW]
[ROW][C]18[/C][C]-0.156577[/C][C]-1.2128[/C][C]0.114972[/C][/ROW]
[ROW][C]19[/C][C]-0.192933[/C][C]-1.4945[/C][C]0.070149[/C][/ROW]
[ROW][C]20[/C][C]-0.222739[/C][C]-1.7253[/C][C]0.044808[/C][/ROW]
[ROW][C]21[/C][C]-0.251999[/C][C]-1.952[/C][C]0.027806[/C][/ROW]
[ROW][C]22[/C][C]-0.285936[/C][C]-2.2149[/C][C]0.015289[/C][/ROW]
[ROW][C]23[/C][C]-0.307662[/C][C]-2.3831[/C][C]0.010174[/C][/ROW]
[ROW][C]24[/C][C]-0.321315[/C][C]-2.4889[/C][C]0.007803[/C][/ROW]
[ROW][C]25[/C][C]-0.328783[/C][C]-2.5467[/C][C]0.006728[/C][/ROW]
[ROW][C]26[/C][C]-0.335169[/C][C]-2.5962[/C][C]0.005918[/C][/ROW]
[ROW][C]27[/C][C]-0.338742[/C][C]-2.6239[/C][C]0.005504[/C][/ROW]
[ROW][C]28[/C][C]-0.347341[/C][C]-2.6905[/C][C]0.004614[/C][/ROW]
[ROW][C]29[/C][C]-0.364336[/C][C]-2.8221[/C][C]0.003231[/C][/ROW]
[ROW][C]30[/C][C]-0.393428[/C][C]-3.0475[/C][C]0.001714[/C][/ROW]
[ROW][C]31[/C][C]-0.420706[/C][C]-3.2588[/C][C]0.000922[/C][/ROW]
[ROW][C]32[/C][C]-0.429498[/C][C]-3.3269[/C][C]0.000752[/C][/ROW]
[ROW][C]33[/C][C]-0.426814[/C][C]-3.3061[/C][C]8e-04[/C][/ROW]
[ROW][C]34[/C][C]-0.410992[/C][C]-3.1835[/C][C]0.001153[/C][/ROW]
[ROW][C]35[/C][C]-0.390386[/C][C]-3.0239[/C][C]0.001834[/C][/ROW]
[ROW][C]36[/C][C]-0.365195[/C][C]-2.8288[/C][C]0.003172[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60450&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60450&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
10.9268137.17910
20.8491266.57730
30.7666045.93810
40.7037785.45140
50.6360954.92723e-06
60.5595754.33442.8e-05
70.4952043.83580.000151
80.4391953.4020.000598
90.3823632.96180.002189
100.3166092.45240.008557
110.2525191.9560.027562
120.1843671.42810.079224
130.1265380.98020.165471
140.0701180.54310.294525
150.0180420.13980.444663
16-0.040815-0.31620.376491
17-0.107632-0.83370.203875
18-0.156577-1.21280.114972
19-0.192933-1.49450.070149
20-0.222739-1.72530.044808
21-0.251999-1.9520.027806
22-0.285936-2.21490.015289
23-0.307662-2.38310.010174
24-0.321315-2.48890.007803
25-0.328783-2.54670.006728
26-0.335169-2.59620.005918
27-0.338742-2.62390.005504
28-0.347341-2.69050.004614
29-0.364336-2.82210.003231
30-0.393428-3.04750.001714
31-0.420706-3.25880.000922
32-0.429498-3.32690.000752
33-0.426814-3.30618e-04
34-0.410992-3.18350.001153
35-0.390386-3.02390.001834
36-0.365195-2.82880.003172






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9268137.17910
2-0.069897-0.54140.295111
3-0.07556-0.58530.280276
40.0962260.74540.22948
5-0.08019-0.62120.268427
6-0.113315-0.87770.191794
70.0671860.52040.302343
80.0059270.04590.481767
9-0.078257-0.60620.273343
10-0.079154-0.61310.271056
11-0.017047-0.1320.447694
12-0.101229-0.78410.218028
130.0089250.06910.472557
14-0.019891-0.15410.439033
15-0.037532-0.29070.386133
16-0.102188-0.79150.215872
17-0.115034-0.8910.188231
180.0675580.52330.301346
190.0221310.17140.432233
20-0.035298-0.27340.392736
21-0.004053-0.03140.487531
22-0.084416-0.65390.257843
230.0027630.02140.491497
240.0156940.12160.451825
250.0148690.11520.454346
26-0.013338-0.10330.459029
27-0.01781-0.1380.44537
28-0.095908-0.74290.23022
29-0.128182-0.99290.162374
30-0.120584-0.9340.177013
31-0.035737-0.27680.391437
320.07920.61350.270938
330.0151450.11730.453503
340.01070.08290.46711
350.0166360.12890.448948
36-0.01445-0.11190.455627

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.926813 & 7.1791 & 0 \tabularnewline
2 & -0.069897 & -0.5414 & 0.295111 \tabularnewline
3 & -0.07556 & -0.5853 & 0.280276 \tabularnewline
4 & 0.096226 & 0.7454 & 0.22948 \tabularnewline
5 & -0.08019 & -0.6212 & 0.268427 \tabularnewline
6 & -0.113315 & -0.8777 & 0.191794 \tabularnewline
7 & 0.067186 & 0.5204 & 0.302343 \tabularnewline
8 & 0.005927 & 0.0459 & 0.481767 \tabularnewline
9 & -0.078257 & -0.6062 & 0.273343 \tabularnewline
10 & -0.079154 & -0.6131 & 0.271056 \tabularnewline
11 & -0.017047 & -0.132 & 0.447694 \tabularnewline
12 & -0.101229 & -0.7841 & 0.218028 \tabularnewline
13 & 0.008925 & 0.0691 & 0.472557 \tabularnewline
14 & -0.019891 & -0.1541 & 0.439033 \tabularnewline
15 & -0.037532 & -0.2907 & 0.386133 \tabularnewline
16 & -0.102188 & -0.7915 & 0.215872 \tabularnewline
17 & -0.115034 & -0.891 & 0.188231 \tabularnewline
18 & 0.067558 & 0.5233 & 0.301346 \tabularnewline
19 & 0.022131 & 0.1714 & 0.432233 \tabularnewline
20 & -0.035298 & -0.2734 & 0.392736 \tabularnewline
21 & -0.004053 & -0.0314 & 0.487531 \tabularnewline
22 & -0.084416 & -0.6539 & 0.257843 \tabularnewline
23 & 0.002763 & 0.0214 & 0.491497 \tabularnewline
24 & 0.015694 & 0.1216 & 0.451825 \tabularnewline
25 & 0.014869 & 0.1152 & 0.454346 \tabularnewline
26 & -0.013338 & -0.1033 & 0.459029 \tabularnewline
27 & -0.01781 & -0.138 & 0.44537 \tabularnewline
28 & -0.095908 & -0.7429 & 0.23022 \tabularnewline
29 & -0.128182 & -0.9929 & 0.162374 \tabularnewline
30 & -0.120584 & -0.934 & 0.177013 \tabularnewline
31 & -0.035737 & -0.2768 & 0.391437 \tabularnewline
32 & 0.0792 & 0.6135 & 0.270938 \tabularnewline
33 & 0.015145 & 0.1173 & 0.453503 \tabularnewline
34 & 0.0107 & 0.0829 & 0.46711 \tabularnewline
35 & 0.016636 & 0.1289 & 0.448948 \tabularnewline
36 & -0.01445 & -0.1119 & 0.455627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60450&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]0.926813[/C][C]7.1791[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.069897[/C][C]-0.5414[/C][C]0.295111[/C][/ROW]
[ROW][C]3[/C][C]-0.07556[/C][C]-0.5853[/C][C]0.280276[/C][/ROW]
[ROW][C]4[/C][C]0.096226[/C][C]0.7454[/C][C]0.22948[/C][/ROW]
[ROW][C]5[/C][C]-0.08019[/C][C]-0.6212[/C][C]0.268427[/C][/ROW]
[ROW][C]6[/C][C]-0.113315[/C][C]-0.8777[/C][C]0.191794[/C][/ROW]
[ROW][C]7[/C][C]0.067186[/C][C]0.5204[/C][C]0.302343[/C][/ROW]
[ROW][C]8[/C][C]0.005927[/C][C]0.0459[/C][C]0.481767[/C][/ROW]
[ROW][C]9[/C][C]-0.078257[/C][C]-0.6062[/C][C]0.273343[/C][/ROW]
[ROW][C]10[/C][C]-0.079154[/C][C]-0.6131[/C][C]0.271056[/C][/ROW]
[ROW][C]11[/C][C]-0.017047[/C][C]-0.132[/C][C]0.447694[/C][/ROW]
[ROW][C]12[/C][C]-0.101229[/C][C]-0.7841[/C][C]0.218028[/C][/ROW]
[ROW][C]13[/C][C]0.008925[/C][C]0.0691[/C][C]0.472557[/C][/ROW]
[ROW][C]14[/C][C]-0.019891[/C][C]-0.1541[/C][C]0.439033[/C][/ROW]
[ROW][C]15[/C][C]-0.037532[/C][C]-0.2907[/C][C]0.386133[/C][/ROW]
[ROW][C]16[/C][C]-0.102188[/C][C]-0.7915[/C][C]0.215872[/C][/ROW]
[ROW][C]17[/C][C]-0.115034[/C][C]-0.891[/C][C]0.188231[/C][/ROW]
[ROW][C]18[/C][C]0.067558[/C][C]0.5233[/C][C]0.301346[/C][/ROW]
[ROW][C]19[/C][C]0.022131[/C][C]0.1714[/C][C]0.432233[/C][/ROW]
[ROW][C]20[/C][C]-0.035298[/C][C]-0.2734[/C][C]0.392736[/C][/ROW]
[ROW][C]21[/C][C]-0.004053[/C][C]-0.0314[/C][C]0.487531[/C][/ROW]
[ROW][C]22[/C][C]-0.084416[/C][C]-0.6539[/C][C]0.257843[/C][/ROW]
[ROW][C]23[/C][C]0.002763[/C][C]0.0214[/C][C]0.491497[/C][/ROW]
[ROW][C]24[/C][C]0.015694[/C][C]0.1216[/C][C]0.451825[/C][/ROW]
[ROW][C]25[/C][C]0.014869[/C][C]0.1152[/C][C]0.454346[/C][/ROW]
[ROW][C]26[/C][C]-0.013338[/C][C]-0.1033[/C][C]0.459029[/C][/ROW]
[ROW][C]27[/C][C]-0.01781[/C][C]-0.138[/C][C]0.44537[/C][/ROW]
[ROW][C]28[/C][C]-0.095908[/C][C]-0.7429[/C][C]0.23022[/C][/ROW]
[ROW][C]29[/C][C]-0.128182[/C][C]-0.9929[/C][C]0.162374[/C][/ROW]
[ROW][C]30[/C][C]-0.120584[/C][C]-0.934[/C][C]0.177013[/C][/ROW]
[ROW][C]31[/C][C]-0.035737[/C][C]-0.2768[/C][C]0.391437[/C][/ROW]
[ROW][C]32[/C][C]0.0792[/C][C]0.6135[/C][C]0.270938[/C][/ROW]
[ROW][C]33[/C][C]0.015145[/C][C]0.1173[/C][C]0.453503[/C][/ROW]
[ROW][C]34[/C][C]0.0107[/C][C]0.0829[/C][C]0.46711[/C][/ROW]
[ROW][C]35[/C][C]0.016636[/C][C]0.1289[/C][C]0.448948[/C][/ROW]
[ROW][C]36[/C][C]-0.01445[/C][C]-0.1119[/C][C]0.455627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60450&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60450&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
10.9268137.17910
2-0.069897-0.54140.295111
3-0.07556-0.58530.280276
40.0962260.74540.22948
5-0.08019-0.62120.268427
6-0.113315-0.87770.191794
70.0671860.52040.302343
80.0059270.04590.481767
9-0.078257-0.60620.273343
10-0.079154-0.61310.271056
11-0.017047-0.1320.447694
12-0.101229-0.78410.218028
130.0089250.06910.472557
14-0.019891-0.15410.439033
15-0.037532-0.29070.386133
16-0.102188-0.79150.215872
17-0.115034-0.8910.188231
180.0675580.52330.301346
190.0221310.17140.432233
20-0.035298-0.27340.392736
21-0.004053-0.03140.487531
22-0.084416-0.65390.257843
230.0027630.02140.491497
240.0156940.12160.451825
250.0148690.11520.454346
26-0.013338-0.10330.459029
27-0.01781-0.1380.44537
28-0.095908-0.74290.23022
29-0.128182-0.99290.162374
30-0.120584-0.9340.177013
31-0.035737-0.27680.391437
320.07920.61350.270938
330.0151450.11730.453503
340.01070.08290.46711
350.0166360.12890.448948
36-0.01445-0.11190.455627


Figures (Output of Computation)

Input Parameters & R Code

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