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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, 11 Dec 2009 04:55:02 -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/11/t12605326722mmczbwcdz2z1ho.htm/, Retrieved Mon, 29 Apr 2024 05:49:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66041, Retrieved Mon, 29 Apr 2024 05:49:36 +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]
-    D        [(Partial) Autocorrelation Function] [WS 8, ACF model 1] [2009-11-27 23:37:27] [96e597a9107bfe8c07649cce3d4f6fec]
-               [(Partial) Autocorrelation Function] [WS 9, ACF model (...] [2009-12-04 11:59:07] [96e597a9107bfe8c07649cce3d4f6fec]
-   PD            [(Partial) Autocorrelation Function] [WS 9, ACF model (...] [2009-12-04 12:03:38] [96e597a9107bfe8c07649cce3d4f6fec]
-                   [(Partial) Autocorrelation Function] [WS 10, ACF model ...] [2009-12-11 10:41:25] [96e597a9107bfe8c07649cce3d4f6fec]
-   PD                  [(Partial) Autocorrelation Function] [WS 10, ACF model ...] [2009-12-11 11:55:02] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.8
93.8
107.6
101
95.4
96.5
89.2
87.1
110.5
110.8
104.2
88.9
89.8
90
93.9
91.3
87.8
99.7
73.5
79.2
96.9
95.2
95.6
89.7
92.8
88
101.1
92.7
95.8
103.8
81.8
87.1
105.9
108.1
102.6
93.7
103.5
100.6
113.3
102.4
102.1
106.9
87.3
93.1
109.1
120.3
104.9
92.6
109.8
111.4
117.9
121.6
117.8
124.2
106.8
102.7
116.8
113.6
96.1
85

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66041&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66041&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66041&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.426011-2.92060.002676
20.1120520.76820.223108
30.0505720.34670.36518
40.0089410.06130.475692
5-0.163559-1.12130.133927
60.0765130.52460.301181
70.1180960.80960.211119
8-0.248836-1.70590.047311
90.1859861.27510.104279
10-0.223247-1.53050.066298
110.1693321.16090.125777
12-0.133129-0.91270.183033
130.0598310.41020.341769
140.0093250.06390.47465
150.0045330.03110.487669
16-0.020022-0.13730.445705
170.0445420.30540.380718
18-0.045555-0.31230.378093
19-0.016281-0.11160.455801
200.0009530.00650.497408
210.0424570.29110.386139
22-0.041428-0.2840.388823
230.098220.67340.252008
24-0.120621-0.82690.206226
250.0433070.29690.383927
260.1317360.90310.18553
27-0.191721-1.31440.097549
280.1480871.01520.157596
29-0.024112-0.16530.434708
30-0.028114-0.19270.423996
31-0.088824-0.60890.272745
320.1596091.09420.139717
33-0.202196-1.38620.086116
340.0123190.08450.466526
35-0.02033-0.13940.444873
36-0.104854-0.71880.237898

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.426011 & -2.9206 & 0.002676 \tabularnewline
2 & 0.112052 & 0.7682 & 0.223108 \tabularnewline
3 & 0.050572 & 0.3467 & 0.36518 \tabularnewline
4 & 0.008941 & 0.0613 & 0.475692 \tabularnewline
5 & -0.163559 & -1.1213 & 0.133927 \tabularnewline
6 & 0.076513 & 0.5246 & 0.301181 \tabularnewline
7 & 0.118096 & 0.8096 & 0.211119 \tabularnewline
8 & -0.248836 & -1.7059 & 0.047311 \tabularnewline
9 & 0.185986 & 1.2751 & 0.104279 \tabularnewline
10 & -0.223247 & -1.5305 & 0.066298 \tabularnewline
11 & 0.169332 & 1.1609 & 0.125777 \tabularnewline
12 & -0.133129 & -0.9127 & 0.183033 \tabularnewline
13 & 0.059831 & 0.4102 & 0.341769 \tabularnewline
14 & 0.009325 & 0.0639 & 0.47465 \tabularnewline
15 & 0.004533 & 0.0311 & 0.487669 \tabularnewline
16 & -0.020022 & -0.1373 & 0.445705 \tabularnewline
17 & 0.044542 & 0.3054 & 0.380718 \tabularnewline
18 & -0.045555 & -0.3123 & 0.378093 \tabularnewline
19 & -0.016281 & -0.1116 & 0.455801 \tabularnewline
20 & 0.000953 & 0.0065 & 0.497408 \tabularnewline
21 & 0.042457 & 0.2911 & 0.386139 \tabularnewline
22 & -0.041428 & -0.284 & 0.388823 \tabularnewline
23 & 0.09822 & 0.6734 & 0.252008 \tabularnewline
24 & -0.120621 & -0.8269 & 0.206226 \tabularnewline
25 & 0.043307 & 0.2969 & 0.383927 \tabularnewline
26 & 0.131736 & 0.9031 & 0.18553 \tabularnewline
27 & -0.191721 & -1.3144 & 0.097549 \tabularnewline
28 & 0.148087 & 1.0152 & 0.157596 \tabularnewline
29 & -0.024112 & -0.1653 & 0.434708 \tabularnewline
30 & -0.028114 & -0.1927 & 0.423996 \tabularnewline
31 & -0.088824 & -0.6089 & 0.272745 \tabularnewline
32 & 0.159609 & 1.0942 & 0.139717 \tabularnewline
33 & -0.202196 & -1.3862 & 0.086116 \tabularnewline
34 & 0.012319 & 0.0845 & 0.466526 \tabularnewline
35 & -0.02033 & -0.1394 & 0.444873 \tabularnewline
36 & -0.104854 & -0.7188 & 0.237898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66041&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]-0.426011[/C][C]-2.9206[/C][C]0.002676[/C][/ROW]
[ROW][C]2[/C][C]0.112052[/C][C]0.7682[/C][C]0.223108[/C][/ROW]
[ROW][C]3[/C][C]0.050572[/C][C]0.3467[/C][C]0.36518[/C][/ROW]
[ROW][C]4[/C][C]0.008941[/C][C]0.0613[/C][C]0.475692[/C][/ROW]
[ROW][C]5[/C][C]-0.163559[/C][C]-1.1213[/C][C]0.133927[/C][/ROW]
[ROW][C]6[/C][C]0.076513[/C][C]0.5246[/C][C]0.301181[/C][/ROW]
[ROW][C]7[/C][C]0.118096[/C][C]0.8096[/C][C]0.211119[/C][/ROW]
[ROW][C]8[/C][C]-0.248836[/C][C]-1.7059[/C][C]0.047311[/C][/ROW]
[ROW][C]9[/C][C]0.185986[/C][C]1.2751[/C][C]0.104279[/C][/ROW]
[ROW][C]10[/C][C]-0.223247[/C][C]-1.5305[/C][C]0.066298[/C][/ROW]
[ROW][C]11[/C][C]0.169332[/C][C]1.1609[/C][C]0.125777[/C][/ROW]
[ROW][C]12[/C][C]-0.133129[/C][C]-0.9127[/C][C]0.183033[/C][/ROW]
[ROW][C]13[/C][C]0.059831[/C][C]0.4102[/C][C]0.341769[/C][/ROW]
[ROW][C]14[/C][C]0.009325[/C][C]0.0639[/C][C]0.47465[/C][/ROW]
[ROW][C]15[/C][C]0.004533[/C][C]0.0311[/C][C]0.487669[/C][/ROW]
[ROW][C]16[/C][C]-0.020022[/C][C]-0.1373[/C][C]0.445705[/C][/ROW]
[ROW][C]17[/C][C]0.044542[/C][C]0.3054[/C][C]0.380718[/C][/ROW]
[ROW][C]18[/C][C]-0.045555[/C][C]-0.3123[/C][C]0.378093[/C][/ROW]
[ROW][C]19[/C][C]-0.016281[/C][C]-0.1116[/C][C]0.455801[/C][/ROW]
[ROW][C]20[/C][C]0.000953[/C][C]0.0065[/C][C]0.497408[/C][/ROW]
[ROW][C]21[/C][C]0.042457[/C][C]0.2911[/C][C]0.386139[/C][/ROW]
[ROW][C]22[/C][C]-0.041428[/C][C]-0.284[/C][C]0.388823[/C][/ROW]
[ROW][C]23[/C][C]0.09822[/C][C]0.6734[/C][C]0.252008[/C][/ROW]
[ROW][C]24[/C][C]-0.120621[/C][C]-0.8269[/C][C]0.206226[/C][/ROW]
[ROW][C]25[/C][C]0.043307[/C][C]0.2969[/C][C]0.383927[/C][/ROW]
[ROW][C]26[/C][C]0.131736[/C][C]0.9031[/C][C]0.18553[/C][/ROW]
[ROW][C]27[/C][C]-0.191721[/C][C]-1.3144[/C][C]0.097549[/C][/ROW]
[ROW][C]28[/C][C]0.148087[/C][C]1.0152[/C][C]0.157596[/C][/ROW]
[ROW][C]29[/C][C]-0.024112[/C][C]-0.1653[/C][C]0.434708[/C][/ROW]
[ROW][C]30[/C][C]-0.028114[/C][C]-0.1927[/C][C]0.423996[/C][/ROW]
[ROW][C]31[/C][C]-0.088824[/C][C]-0.6089[/C][C]0.272745[/C][/ROW]
[ROW][C]32[/C][C]0.159609[/C][C]1.0942[/C][C]0.139717[/C][/ROW]
[ROW][C]33[/C][C]-0.202196[/C][C]-1.3862[/C][C]0.086116[/C][/ROW]
[ROW][C]34[/C][C]0.012319[/C][C]0.0845[/C][C]0.466526[/C][/ROW]
[ROW][C]35[/C][C]-0.02033[/C][C]-0.1394[/C][C]0.444873[/C][/ROW]
[ROW][C]36[/C][C]-0.104854[/C][C]-0.7188[/C][C]0.237898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66041&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66041&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
1-0.426011-2.92060.002676
20.1120520.76820.223108
30.0505720.34670.36518
40.0089410.06130.475692
5-0.163559-1.12130.133927
60.0765130.52460.301181
70.1180960.80960.211119
8-0.248836-1.70590.047311
90.1859861.27510.104279
10-0.223247-1.53050.066298
110.1693321.16090.125777
12-0.133129-0.91270.183033
130.0598310.41020.341769
140.0093250.06390.47465
150.0045330.03110.487669
16-0.020022-0.13730.445705
170.0445420.30540.380718
18-0.045555-0.31230.378093
19-0.016281-0.11160.455801
200.0009530.00650.497408
210.0424570.29110.386139
22-0.041428-0.2840.388823
230.098220.67340.252008
24-0.120621-0.82690.206226
250.0433070.29690.383927
260.1317360.90310.18553
27-0.191721-1.31440.097549
280.1480871.01520.157596
29-0.024112-0.16530.434708
30-0.028114-0.19270.423996
31-0.088824-0.60890.272745
320.1596091.09420.139717
33-0.202196-1.38620.086116
340.0123190.08450.466526
35-0.02033-0.13940.444873
36-0.104854-0.71880.237898






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.426011-2.92060.002676
2-0.084828-0.58160.281823
30.0814880.55870.289524
40.0891490.61120.272015
5-0.166021-1.13820.130407
6-0.095582-0.65530.257741
70.1698791.16460.125022
8-0.122813-0.8420.202036
90.0082560.05660.477553
10-0.233176-1.59860.058309
110.0593150.40660.343059
120.0116380.07980.468373
13-0.056399-0.38670.350379
140.0097450.06680.473508
150.0139340.09550.462153
16-0.007537-0.05170.479505
170.0741710.50850.306744
18-0.136238-0.9340.17754
190.0099620.06830.472919
20-0.089182-0.61140.27194
210.0877610.60170.275146
22-0.004778-0.03280.487003
230.0854010.58550.280512
24-0.103576-0.71010.240582
25-0.016269-0.11150.455834
260.1915121.31290.097789
27-0.065389-0.44830.328004
28-0.022543-0.15450.438921
290.0288740.1980.421968
30-0.038965-0.26710.395268
310.0129730.08890.464756
32-0.029295-0.20080.420845
33-0.106515-0.73020.234438
34-0.092064-0.63120.265496
35-0.143307-0.98250.165451
36-0.112534-0.77150.222138

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.426011 & -2.9206 & 0.002676 \tabularnewline
2 & -0.084828 & -0.5816 & 0.281823 \tabularnewline
3 & 0.081488 & 0.5587 & 0.289524 \tabularnewline
4 & 0.089149 & 0.6112 & 0.272015 \tabularnewline
5 & -0.166021 & -1.1382 & 0.130407 \tabularnewline
6 & -0.095582 & -0.6553 & 0.257741 \tabularnewline
7 & 0.169879 & 1.1646 & 0.125022 \tabularnewline
8 & -0.122813 & -0.842 & 0.202036 \tabularnewline
9 & 0.008256 & 0.0566 & 0.477553 \tabularnewline
10 & -0.233176 & -1.5986 & 0.058309 \tabularnewline
11 & 0.059315 & 0.4066 & 0.343059 \tabularnewline
12 & 0.011638 & 0.0798 & 0.468373 \tabularnewline
13 & -0.056399 & -0.3867 & 0.350379 \tabularnewline
14 & 0.009745 & 0.0668 & 0.473508 \tabularnewline
15 & 0.013934 & 0.0955 & 0.462153 \tabularnewline
16 & -0.007537 & -0.0517 & 0.479505 \tabularnewline
17 & 0.074171 & 0.5085 & 0.306744 \tabularnewline
18 & -0.136238 & -0.934 & 0.17754 \tabularnewline
19 & 0.009962 & 0.0683 & 0.472919 \tabularnewline
20 & -0.089182 & -0.6114 & 0.27194 \tabularnewline
21 & 0.087761 & 0.6017 & 0.275146 \tabularnewline
22 & -0.004778 & -0.0328 & 0.487003 \tabularnewline
23 & 0.085401 & 0.5855 & 0.280512 \tabularnewline
24 & -0.103576 & -0.7101 & 0.240582 \tabularnewline
25 & -0.016269 & -0.1115 & 0.455834 \tabularnewline
26 & 0.191512 & 1.3129 & 0.097789 \tabularnewline
27 & -0.065389 & -0.4483 & 0.328004 \tabularnewline
28 & -0.022543 & -0.1545 & 0.438921 \tabularnewline
29 & 0.028874 & 0.198 & 0.421968 \tabularnewline
30 & -0.038965 & -0.2671 & 0.395268 \tabularnewline
31 & 0.012973 & 0.0889 & 0.464756 \tabularnewline
32 & -0.029295 & -0.2008 & 0.420845 \tabularnewline
33 & -0.106515 & -0.7302 & 0.234438 \tabularnewline
34 & -0.092064 & -0.6312 & 0.265496 \tabularnewline
35 & -0.143307 & -0.9825 & 0.165451 \tabularnewline
36 & -0.112534 & -0.7715 & 0.222138 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66041&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]-0.426011[/C][C]-2.9206[/C][C]0.002676[/C][/ROW]
[ROW][C]2[/C][C]-0.084828[/C][C]-0.5816[/C][C]0.281823[/C][/ROW]
[ROW][C]3[/C][C]0.081488[/C][C]0.5587[/C][C]0.289524[/C][/ROW]
[ROW][C]4[/C][C]0.089149[/C][C]0.6112[/C][C]0.272015[/C][/ROW]
[ROW][C]5[/C][C]-0.166021[/C][C]-1.1382[/C][C]0.130407[/C][/ROW]
[ROW][C]6[/C][C]-0.095582[/C][C]-0.6553[/C][C]0.257741[/C][/ROW]
[ROW][C]7[/C][C]0.169879[/C][C]1.1646[/C][C]0.125022[/C][/ROW]
[ROW][C]8[/C][C]-0.122813[/C][C]-0.842[/C][C]0.202036[/C][/ROW]
[ROW][C]9[/C][C]0.008256[/C][C]0.0566[/C][C]0.477553[/C][/ROW]
[ROW][C]10[/C][C]-0.233176[/C][C]-1.5986[/C][C]0.058309[/C][/ROW]
[ROW][C]11[/C][C]0.059315[/C][C]0.4066[/C][C]0.343059[/C][/ROW]
[ROW][C]12[/C][C]0.011638[/C][C]0.0798[/C][C]0.468373[/C][/ROW]
[ROW][C]13[/C][C]-0.056399[/C][C]-0.3867[/C][C]0.350379[/C][/ROW]
[ROW][C]14[/C][C]0.009745[/C][C]0.0668[/C][C]0.473508[/C][/ROW]
[ROW][C]15[/C][C]0.013934[/C][C]0.0955[/C][C]0.462153[/C][/ROW]
[ROW][C]16[/C][C]-0.007537[/C][C]-0.0517[/C][C]0.479505[/C][/ROW]
[ROW][C]17[/C][C]0.074171[/C][C]0.5085[/C][C]0.306744[/C][/ROW]
[ROW][C]18[/C][C]-0.136238[/C][C]-0.934[/C][C]0.17754[/C][/ROW]
[ROW][C]19[/C][C]0.009962[/C][C]0.0683[/C][C]0.472919[/C][/ROW]
[ROW][C]20[/C][C]-0.089182[/C][C]-0.6114[/C][C]0.27194[/C][/ROW]
[ROW][C]21[/C][C]0.087761[/C][C]0.6017[/C][C]0.275146[/C][/ROW]
[ROW][C]22[/C][C]-0.004778[/C][C]-0.0328[/C][C]0.487003[/C][/ROW]
[ROW][C]23[/C][C]0.085401[/C][C]0.5855[/C][C]0.280512[/C][/ROW]
[ROW][C]24[/C][C]-0.103576[/C][C]-0.7101[/C][C]0.240582[/C][/ROW]
[ROW][C]25[/C][C]-0.016269[/C][C]-0.1115[/C][C]0.455834[/C][/ROW]
[ROW][C]26[/C][C]0.191512[/C][C]1.3129[/C][C]0.097789[/C][/ROW]
[ROW][C]27[/C][C]-0.065389[/C][C]-0.4483[/C][C]0.328004[/C][/ROW]
[ROW][C]28[/C][C]-0.022543[/C][C]-0.1545[/C][C]0.438921[/C][/ROW]
[ROW][C]29[/C][C]0.028874[/C][C]0.198[/C][C]0.421968[/C][/ROW]
[ROW][C]30[/C][C]-0.038965[/C][C]-0.2671[/C][C]0.395268[/C][/ROW]
[ROW][C]31[/C][C]0.012973[/C][C]0.0889[/C][C]0.464756[/C][/ROW]
[ROW][C]32[/C][C]-0.029295[/C][C]-0.2008[/C][C]0.420845[/C][/ROW]
[ROW][C]33[/C][C]-0.106515[/C][C]-0.7302[/C][C]0.234438[/C][/ROW]
[ROW][C]34[/C][C]-0.092064[/C][C]-0.6312[/C][C]0.265496[/C][/ROW]
[ROW][C]35[/C][C]-0.143307[/C][C]-0.9825[/C][C]0.165451[/C][/ROW]
[ROW][C]36[/C][C]-0.112534[/C][C]-0.7715[/C][C]0.222138[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66041&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66041&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
1-0.426011-2.92060.002676
2-0.084828-0.58160.281823
30.0814880.55870.289524
40.0891490.61120.272015
5-0.166021-1.13820.130407
6-0.095582-0.65530.257741
70.1698791.16460.125022
8-0.122813-0.8420.202036
90.0082560.05660.477553
10-0.233176-1.59860.058309
110.0593150.40660.343059
120.0116380.07980.468373
13-0.056399-0.38670.350379
140.0097450.06680.473508
150.0139340.09550.462153
16-0.007537-0.05170.479505
170.0741710.50850.306744
18-0.136238-0.9340.17754
190.0099620.06830.472919
20-0.089182-0.61140.27194
210.0877610.60170.275146
22-0.004778-0.03280.487003
230.0854010.58550.280512
24-0.103576-0.71010.240582
25-0.016269-0.11150.455834
260.1915121.31290.097789
27-0.065389-0.44830.328004
28-0.022543-0.15450.438921
290.0288740.1980.421968
30-0.038965-0.26710.395268
310.0129730.08890.464756
32-0.029295-0.20080.420845
33-0.106515-0.73020.234438
34-0.092064-0.63120.265496
35-0.143307-0.98250.165451
36-0.112534-0.77150.222138


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -1.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -1.0 ; 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')