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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 08:16:37 -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/t1259507953fuha6rukx4onqsb.htm/, Retrieved Thu, 18 Apr 2024 23:15:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61626, Retrieved Thu, 18 Apr 2024 23:15:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [workshop 8] [2009-11-25 11:50:24] [309ee52d0058ff0a6f7eec15e07b2d9f]
-   P             [(Partial) Autocorrelation Function] [workshop 8] [2009-11-29 15:16:37] [6198946fb53eb5eb18db46bb758f7fde] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.6348
0.634
0.62915
0.62168
0.61328
0.6089
0.60857
0.62672
0.62291
0.62393
0.61838
0.62012
0.61659
0.6116
0.61573
0.61407
0.62823
0.64405
0.6387
0.63633
0.63059
0.62994
0.63709
0.64217
0.65711
0.66977
0.68255
0.68902
0.71322
0.70224
0.70045
0.69919
0.69693
0.69763
0.69278
0.70196
0.69215
0.6769
0.67124
0.66532
0.67157
0.66428
0.66576
0.66942
0.6813
0.69144
0.69862
0.695
0.69867
0.68968
0.69233
0.68293
0.68399
0.66895
0.68756
0.68527
0.6776
0.68137
0.67933
0.67922

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=61626&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=61626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61626&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
10.0918180.70530.241711
20.2246121.72530.044856
3-0.040114-0.30810.379536
4-0.037949-0.29150.385849
5-0.081593-0.62670.266627
6-0.120781-0.92770.178662
7-0.025875-0.19870.421572
8-0.041654-0.320.375067
90.0107560.08260.467216
100.0985560.7570.226024
11-0.050622-0.38880.349399
12-0.066166-0.50820.306592
13-0.310588-2.38570.010139
14-0.090028-0.69150.245976
15-0.092981-0.71420.23896
160.0276740.21260.416199
170.1229680.94450.174373
180.0880690.67650.250693
190.1975961.51780.067208
20-0.039402-0.30260.381611
210.0044270.0340.486495
22-0.085181-0.65430.257735
23-0.165593-1.27190.104192
24-0.041958-0.32230.374187
25-0.28273-2.17170.016956
260.0871470.66940.252929
27-0.021867-0.1680.433592
280.0809180.62150.268318
290.0601960.46240.322757
30-0.050093-0.38480.350895
31-0.024941-0.19160.424367
32-0.036525-0.28060.390017
330.056840.43660.331998
34-0.044871-0.34470.365788
350.0118120.09070.464008
36-0.039345-0.30220.381775

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.091818 & 0.7053 & 0.241711 \tabularnewline
2 & 0.224612 & 1.7253 & 0.044856 \tabularnewline
3 & -0.040114 & -0.3081 & 0.379536 \tabularnewline
4 & -0.037949 & -0.2915 & 0.385849 \tabularnewline
5 & -0.081593 & -0.6267 & 0.266627 \tabularnewline
6 & -0.120781 & -0.9277 & 0.178662 \tabularnewline
7 & -0.025875 & -0.1987 & 0.421572 \tabularnewline
8 & -0.041654 & -0.32 & 0.375067 \tabularnewline
9 & 0.010756 & 0.0826 & 0.467216 \tabularnewline
10 & 0.098556 & 0.757 & 0.226024 \tabularnewline
11 & -0.050622 & -0.3888 & 0.349399 \tabularnewline
12 & -0.066166 & -0.5082 & 0.306592 \tabularnewline
13 & -0.310588 & -2.3857 & 0.010139 \tabularnewline
14 & -0.090028 & -0.6915 & 0.245976 \tabularnewline
15 & -0.092981 & -0.7142 & 0.23896 \tabularnewline
16 & 0.027674 & 0.2126 & 0.416199 \tabularnewline
17 & 0.122968 & 0.9445 & 0.174373 \tabularnewline
18 & 0.088069 & 0.6765 & 0.250693 \tabularnewline
19 & 0.197596 & 1.5178 & 0.067208 \tabularnewline
20 & -0.039402 & -0.3026 & 0.381611 \tabularnewline
21 & 0.004427 & 0.034 & 0.486495 \tabularnewline
22 & -0.085181 & -0.6543 & 0.257735 \tabularnewline
23 & -0.165593 & -1.2719 & 0.104192 \tabularnewline
24 & -0.041958 & -0.3223 & 0.374187 \tabularnewline
25 & -0.28273 & -2.1717 & 0.016956 \tabularnewline
26 & 0.087147 & 0.6694 & 0.252929 \tabularnewline
27 & -0.021867 & -0.168 & 0.433592 \tabularnewline
28 & 0.080918 & 0.6215 & 0.268318 \tabularnewline
29 & 0.060196 & 0.4624 & 0.322757 \tabularnewline
30 & -0.050093 & -0.3848 & 0.350895 \tabularnewline
31 & -0.024941 & -0.1916 & 0.424367 \tabularnewline
32 & -0.036525 & -0.2806 & 0.390017 \tabularnewline
33 & 0.05684 & 0.4366 & 0.331998 \tabularnewline
34 & -0.044871 & -0.3447 & 0.365788 \tabularnewline
35 & 0.011812 & 0.0907 & 0.464008 \tabularnewline
36 & -0.039345 & -0.3022 & 0.381775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61626&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]0.091818[/C][C]0.7053[/C][C]0.241711[/C][/ROW]
[ROW][C]2[/C][C]0.224612[/C][C]1.7253[/C][C]0.044856[/C][/ROW]
[ROW][C]3[/C][C]-0.040114[/C][C]-0.3081[/C][C]0.379536[/C][/ROW]
[ROW][C]4[/C][C]-0.037949[/C][C]-0.2915[/C][C]0.385849[/C][/ROW]
[ROW][C]5[/C][C]-0.081593[/C][C]-0.6267[/C][C]0.266627[/C][/ROW]
[ROW][C]6[/C][C]-0.120781[/C][C]-0.9277[/C][C]0.178662[/C][/ROW]
[ROW][C]7[/C][C]-0.025875[/C][C]-0.1987[/C][C]0.421572[/C][/ROW]
[ROW][C]8[/C][C]-0.041654[/C][C]-0.32[/C][C]0.375067[/C][/ROW]
[ROW][C]9[/C][C]0.010756[/C][C]0.0826[/C][C]0.467216[/C][/ROW]
[ROW][C]10[/C][C]0.098556[/C][C]0.757[/C][C]0.226024[/C][/ROW]
[ROW][C]11[/C][C]-0.050622[/C][C]-0.3888[/C][C]0.349399[/C][/ROW]
[ROW][C]12[/C][C]-0.066166[/C][C]-0.5082[/C][C]0.306592[/C][/ROW]
[ROW][C]13[/C][C]-0.310588[/C][C]-2.3857[/C][C]0.010139[/C][/ROW]
[ROW][C]14[/C][C]-0.090028[/C][C]-0.6915[/C][C]0.245976[/C][/ROW]
[ROW][C]15[/C][C]-0.092981[/C][C]-0.7142[/C][C]0.23896[/C][/ROW]
[ROW][C]16[/C][C]0.027674[/C][C]0.2126[/C][C]0.416199[/C][/ROW]
[ROW][C]17[/C][C]0.122968[/C][C]0.9445[/C][C]0.174373[/C][/ROW]
[ROW][C]18[/C][C]0.088069[/C][C]0.6765[/C][C]0.250693[/C][/ROW]
[ROW][C]19[/C][C]0.197596[/C][C]1.5178[/C][C]0.067208[/C][/ROW]
[ROW][C]20[/C][C]-0.039402[/C][C]-0.3026[/C][C]0.381611[/C][/ROW]
[ROW][C]21[/C][C]0.004427[/C][C]0.034[/C][C]0.486495[/C][/ROW]
[ROW][C]22[/C][C]-0.085181[/C][C]-0.6543[/C][C]0.257735[/C][/ROW]
[ROW][C]23[/C][C]-0.165593[/C][C]-1.2719[/C][C]0.104192[/C][/ROW]
[ROW][C]24[/C][C]-0.041958[/C][C]-0.3223[/C][C]0.374187[/C][/ROW]
[ROW][C]25[/C][C]-0.28273[/C][C]-2.1717[/C][C]0.016956[/C][/ROW]
[ROW][C]26[/C][C]0.087147[/C][C]0.6694[/C][C]0.252929[/C][/ROW]
[ROW][C]27[/C][C]-0.021867[/C][C]-0.168[/C][C]0.433592[/C][/ROW]
[ROW][C]28[/C][C]0.080918[/C][C]0.6215[/C][C]0.268318[/C][/ROW]
[ROW][C]29[/C][C]0.060196[/C][C]0.4624[/C][C]0.322757[/C][/ROW]
[ROW][C]30[/C][C]-0.050093[/C][C]-0.3848[/C][C]0.350895[/C][/ROW]
[ROW][C]31[/C][C]-0.024941[/C][C]-0.1916[/C][C]0.424367[/C][/ROW]
[ROW][C]32[/C][C]-0.036525[/C][C]-0.2806[/C][C]0.390017[/C][/ROW]
[ROW][C]33[/C][C]0.05684[/C][C]0.4366[/C][C]0.331998[/C][/ROW]
[ROW][C]34[/C][C]-0.044871[/C][C]-0.3447[/C][C]0.365788[/C][/ROW]
[ROW][C]35[/C][C]0.011812[/C][C]0.0907[/C][C]0.464008[/C][/ROW]
[ROW][C]36[/C][C]-0.039345[/C][C]-0.3022[/C][C]0.381775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61626&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
10.0918180.70530.241711
20.2246121.72530.044856
3-0.040114-0.30810.379536
4-0.037949-0.29150.385849
5-0.081593-0.62670.266627
6-0.120781-0.92770.178662
7-0.025875-0.19870.421572
8-0.041654-0.320.375067
90.0107560.08260.467216
100.0985560.7570.226024
11-0.050622-0.38880.349399
12-0.066166-0.50820.306592
13-0.310588-2.38570.010139
14-0.090028-0.69150.245976
15-0.092981-0.71420.23896
160.0276740.21260.416199
170.1229680.94450.174373
180.0880690.67650.250693
190.1975961.51780.067208
20-0.039402-0.30260.381611
210.0044270.0340.486495
22-0.085181-0.65430.257735
23-0.165593-1.27190.104192
24-0.041958-0.32230.374187
25-0.28273-2.17170.016956
260.0871470.66940.252929
27-0.021867-0.1680.433592
280.0809180.62150.268318
290.0601960.46240.322757
30-0.050093-0.38480.350895
31-0.024941-0.19160.424367
32-0.036525-0.28060.390017
330.056840.43660.331998
34-0.044871-0.34470.365788
350.0118120.09070.464008
36-0.039345-0.30220.381775






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0918180.70530.241711
20.218021.67460.049649
3-0.080746-0.62020.26875
4-0.0823-0.63220.264862
5-0.04796-0.36840.356951
6-0.092249-0.70860.240688
70.0160420.12320.451176
8-0.001569-0.0120.495214
9-0.001682-0.01290.494869
100.1008570.77470.220805
11-0.091997-0.70660.241284
12-0.124821-0.95880.170793
13-0.288184-2.21360.015368
14-0.021581-0.16580.434452
150.0593580.45590.325055
160.053860.41370.340294
170.1083520.83230.204306
180.0089360.06860.472755
190.0772190.59310.277681
20-0.140418-1.07860.142584
21-0.088908-0.68290.248666
22-0.015048-0.11560.454186
23-0.070174-0.5390.295952
240.0261590.20090.420722
25-0.30468-2.34030.011335
26-0.002835-0.02180.491351
270.0291140.22360.411909
280.0026660.02050.491865
290.0602160.46250.322702
30-0.035301-0.27120.39361
31-0.023331-0.17920.429195
320.0594820.45690.324714
330.0153170.11760.453373
34-0.129811-0.99710.161394
35-0.029582-0.22720.410517
36-0.174426-1.33980.092725

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.091818 & 0.7053 & 0.241711 \tabularnewline
2 & 0.21802 & 1.6746 & 0.049649 \tabularnewline
3 & -0.080746 & -0.6202 & 0.26875 \tabularnewline
4 & -0.0823 & -0.6322 & 0.264862 \tabularnewline
5 & -0.04796 & -0.3684 & 0.356951 \tabularnewline
6 & -0.092249 & -0.7086 & 0.240688 \tabularnewline
7 & 0.016042 & 0.1232 & 0.451176 \tabularnewline
8 & -0.001569 & -0.012 & 0.495214 \tabularnewline
9 & -0.001682 & -0.0129 & 0.494869 \tabularnewline
10 & 0.100857 & 0.7747 & 0.220805 \tabularnewline
11 & -0.091997 & -0.7066 & 0.241284 \tabularnewline
12 & -0.124821 & -0.9588 & 0.170793 \tabularnewline
13 & -0.288184 & -2.2136 & 0.015368 \tabularnewline
14 & -0.021581 & -0.1658 & 0.434452 \tabularnewline
15 & 0.059358 & 0.4559 & 0.325055 \tabularnewline
16 & 0.05386 & 0.4137 & 0.340294 \tabularnewline
17 & 0.108352 & 0.8323 & 0.204306 \tabularnewline
18 & 0.008936 & 0.0686 & 0.472755 \tabularnewline
19 & 0.077219 & 0.5931 & 0.277681 \tabularnewline
20 & -0.140418 & -1.0786 & 0.142584 \tabularnewline
21 & -0.088908 & -0.6829 & 0.248666 \tabularnewline
22 & -0.015048 & -0.1156 & 0.454186 \tabularnewline
23 & -0.070174 & -0.539 & 0.295952 \tabularnewline
24 & 0.026159 & 0.2009 & 0.420722 \tabularnewline
25 & -0.30468 & -2.3403 & 0.011335 \tabularnewline
26 & -0.002835 & -0.0218 & 0.491351 \tabularnewline
27 & 0.029114 & 0.2236 & 0.411909 \tabularnewline
28 & 0.002666 & 0.0205 & 0.491865 \tabularnewline
29 & 0.060216 & 0.4625 & 0.322702 \tabularnewline
30 & -0.035301 & -0.2712 & 0.39361 \tabularnewline
31 & -0.023331 & -0.1792 & 0.429195 \tabularnewline
32 & 0.059482 & 0.4569 & 0.324714 \tabularnewline
33 & 0.015317 & 0.1176 & 0.453373 \tabularnewline
34 & -0.129811 & -0.9971 & 0.161394 \tabularnewline
35 & -0.029582 & -0.2272 & 0.410517 \tabularnewline
36 & -0.174426 & -1.3398 & 0.092725 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61626&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]0.091818[/C][C]0.7053[/C][C]0.241711[/C][/ROW]
[ROW][C]2[/C][C]0.21802[/C][C]1.6746[/C][C]0.049649[/C][/ROW]
[ROW][C]3[/C][C]-0.080746[/C][C]-0.6202[/C][C]0.26875[/C][/ROW]
[ROW][C]4[/C][C]-0.0823[/C][C]-0.6322[/C][C]0.264862[/C][/ROW]
[ROW][C]5[/C][C]-0.04796[/C][C]-0.3684[/C][C]0.356951[/C][/ROW]
[ROW][C]6[/C][C]-0.092249[/C][C]-0.7086[/C][C]0.240688[/C][/ROW]
[ROW][C]7[/C][C]0.016042[/C][C]0.1232[/C][C]0.451176[/C][/ROW]
[ROW][C]8[/C][C]-0.001569[/C][C]-0.012[/C][C]0.495214[/C][/ROW]
[ROW][C]9[/C][C]-0.001682[/C][C]-0.0129[/C][C]0.494869[/C][/ROW]
[ROW][C]10[/C][C]0.100857[/C][C]0.7747[/C][C]0.220805[/C][/ROW]
[ROW][C]11[/C][C]-0.091997[/C][C]-0.7066[/C][C]0.241284[/C][/ROW]
[ROW][C]12[/C][C]-0.124821[/C][C]-0.9588[/C][C]0.170793[/C][/ROW]
[ROW][C]13[/C][C]-0.288184[/C][C]-2.2136[/C][C]0.015368[/C][/ROW]
[ROW][C]14[/C][C]-0.021581[/C][C]-0.1658[/C][C]0.434452[/C][/ROW]
[ROW][C]15[/C][C]0.059358[/C][C]0.4559[/C][C]0.325055[/C][/ROW]
[ROW][C]16[/C][C]0.05386[/C][C]0.4137[/C][C]0.340294[/C][/ROW]
[ROW][C]17[/C][C]0.108352[/C][C]0.8323[/C][C]0.204306[/C][/ROW]
[ROW][C]18[/C][C]0.008936[/C][C]0.0686[/C][C]0.472755[/C][/ROW]
[ROW][C]19[/C][C]0.077219[/C][C]0.5931[/C][C]0.277681[/C][/ROW]
[ROW][C]20[/C][C]-0.140418[/C][C]-1.0786[/C][C]0.142584[/C][/ROW]
[ROW][C]21[/C][C]-0.088908[/C][C]-0.6829[/C][C]0.248666[/C][/ROW]
[ROW][C]22[/C][C]-0.015048[/C][C]-0.1156[/C][C]0.454186[/C][/ROW]
[ROW][C]23[/C][C]-0.070174[/C][C]-0.539[/C][C]0.295952[/C][/ROW]
[ROW][C]24[/C][C]0.026159[/C][C]0.2009[/C][C]0.420722[/C][/ROW]
[ROW][C]25[/C][C]-0.30468[/C][C]-2.3403[/C][C]0.011335[/C][/ROW]
[ROW][C]26[/C][C]-0.002835[/C][C]-0.0218[/C][C]0.491351[/C][/ROW]
[ROW][C]27[/C][C]0.029114[/C][C]0.2236[/C][C]0.411909[/C][/ROW]
[ROW][C]28[/C][C]0.002666[/C][C]0.0205[/C][C]0.491865[/C][/ROW]
[ROW][C]29[/C][C]0.060216[/C][C]0.4625[/C][C]0.322702[/C][/ROW]
[ROW][C]30[/C][C]-0.035301[/C][C]-0.2712[/C][C]0.39361[/C][/ROW]
[ROW][C]31[/C][C]-0.023331[/C][C]-0.1792[/C][C]0.429195[/C][/ROW]
[ROW][C]32[/C][C]0.059482[/C][C]0.4569[/C][C]0.324714[/C][/ROW]
[ROW][C]33[/C][C]0.015317[/C][C]0.1176[/C][C]0.453373[/C][/ROW]
[ROW][C]34[/C][C]-0.129811[/C][C]-0.9971[/C][C]0.161394[/C][/ROW]
[ROW][C]35[/C][C]-0.029582[/C][C]-0.2272[/C][C]0.410517[/C][/ROW]
[ROW][C]36[/C][C]-0.174426[/C][C]-1.3398[/C][C]0.092725[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61626&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61626&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
10.0918180.70530.241711
20.218021.67460.049649
3-0.080746-0.62020.26875
4-0.0823-0.63220.264862
5-0.04796-0.36840.356951
6-0.092249-0.70860.240688
70.0160420.12320.451176
8-0.001569-0.0120.495214
9-0.001682-0.01290.494869
100.1008570.77470.220805
11-0.091997-0.70660.241284
12-0.124821-0.95880.170793
13-0.288184-2.21360.015368
14-0.021581-0.16580.434452
150.0593580.45590.325055
160.053860.41370.340294
170.1083520.83230.204306
180.0089360.06860.472755
190.0772190.59310.277681
20-0.140418-1.07860.142584
21-0.088908-0.68290.248666
22-0.015048-0.11560.454186
23-0.070174-0.5390.295952
240.0261590.20090.420722
25-0.30468-2.34030.011335
26-0.002835-0.02180.491351
270.0291140.22360.411909
280.0026660.02050.491865
290.0602160.46250.322702
30-0.035301-0.27120.39361
31-0.023331-0.17920.429195
320.0594820.45690.324714
330.0153170.11760.453373
34-0.129811-0.99710.161394
35-0.029582-0.22720.410517
36-0.174426-1.33980.092725


Figures (Output of Computation)

Input Parameters & R Code

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