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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, 27 Nov 2009 05:10:08 -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/t1259323851oc5xmbcxgje3del.htm/, Retrieved Mon, 29 Apr 2024 22:15:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60610, Retrieved Mon, 29 Apr 2024 22:15:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

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] [] [2009-11-27 12:10:08] [4996e0131d5120d29a6e9a8dccb25dc3] [Current]
-   P             [(Partial) Autocorrelation Function] [Gegevens stationa...] [2009-12-19 09:00:27] [e3c32faf833f030d3b397185b633f75f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
19
18
19
19
22
23
20
14
14
14
15
11
17
16
20
24
23
20
21
19
23
23
23
23
27
26
17
24
26
24
27
27
26
24
23
23
24
17
21
19
22
22
18
16
14
12
14
16
8
3
0
5
1
1
3
6
7
8
14
14
13

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=60610&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=60610&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60610&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
10.8383065.86810
20.7706425.39451e-06
30.676594.73619e-06
40.590634.13446.9e-05
50.5208523.6460.000322
60.4471693.13020.001471
70.39212.74470.004221
80.354172.47920.008328
90.3182342.22760.015264
100.2256571.57960.060317
110.1556011.08920.140696
120.0147140.1030.459193
130.0188760.13210.447709
14-0.068878-0.48210.315926
15-0.085562-0.59890.275989
16-0.09527-0.66690.253985
17-0.146593-1.02610.154931
18-0.198313-1.38820.085679
19-0.246646-1.72650.045277
20-0.289518-2.02660.02408
21-0.348015-2.43610.009264
22-0.331695-2.32190.01222
23-0.354916-2.48440.008221
24-0.3376-2.36320.011065
25-0.34404-2.40830.009918
26-0.308867-2.16210.017762
27-0.329019-2.30310.012778
28-0.352878-2.47010.008517
29-0.360594-2.52420.007444
30-0.348778-2.44140.009143
31-0.306151-2.14310.01855
32-0.268865-1.88210.032887
33-0.225879-1.58120.060138
34-0.187039-1.30930.098274
35-0.11081-0.77570.220836
36-0.073843-0.51690.303775

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.838306 & 5.8681 & 0 \tabularnewline
2 & 0.770642 & 5.3945 & 1e-06 \tabularnewline
3 & 0.67659 & 4.7361 & 9e-06 \tabularnewline
4 & 0.59063 & 4.1344 & 6.9e-05 \tabularnewline
5 & 0.520852 & 3.646 & 0.000322 \tabularnewline
6 & 0.447169 & 3.1302 & 0.001471 \tabularnewline
7 & 0.3921 & 2.7447 & 0.004221 \tabularnewline
8 & 0.35417 & 2.4792 & 0.008328 \tabularnewline
9 & 0.318234 & 2.2276 & 0.015264 \tabularnewline
10 & 0.225657 & 1.5796 & 0.060317 \tabularnewline
11 & 0.155601 & 1.0892 & 0.140696 \tabularnewline
12 & 0.014714 & 0.103 & 0.459193 \tabularnewline
13 & 0.018876 & 0.1321 & 0.447709 \tabularnewline
14 & -0.068878 & -0.4821 & 0.315926 \tabularnewline
15 & -0.085562 & -0.5989 & 0.275989 \tabularnewline
16 & -0.09527 & -0.6669 & 0.253985 \tabularnewline
17 & -0.146593 & -1.0261 & 0.154931 \tabularnewline
18 & -0.198313 & -1.3882 & 0.085679 \tabularnewline
19 & -0.246646 & -1.7265 & 0.045277 \tabularnewline
20 & -0.289518 & -2.0266 & 0.02408 \tabularnewline
21 & -0.348015 & -2.4361 & 0.009264 \tabularnewline
22 & -0.331695 & -2.3219 & 0.01222 \tabularnewline
23 & -0.354916 & -2.4844 & 0.008221 \tabularnewline
24 & -0.3376 & -2.3632 & 0.011065 \tabularnewline
25 & -0.34404 & -2.4083 & 0.009918 \tabularnewline
26 & -0.308867 & -2.1621 & 0.017762 \tabularnewline
27 & -0.329019 & -2.3031 & 0.012778 \tabularnewline
28 & -0.352878 & -2.4701 & 0.008517 \tabularnewline
29 & -0.360594 & -2.5242 & 0.007444 \tabularnewline
30 & -0.348778 & -2.4414 & 0.009143 \tabularnewline
31 & -0.306151 & -2.1431 & 0.01855 \tabularnewline
32 & -0.268865 & -1.8821 & 0.032887 \tabularnewline
33 & -0.225879 & -1.5812 & 0.060138 \tabularnewline
34 & -0.187039 & -1.3093 & 0.098274 \tabularnewline
35 & -0.11081 & -0.7757 & 0.220836 \tabularnewline
36 & -0.073843 & -0.5169 & 0.303775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60610&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]0.838306[/C][C]5.8681[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.770642[/C][C]5.3945[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.67659[/C][C]4.7361[/C][C]9e-06[/C][/ROW]
[ROW][C]4[/C][C]0.59063[/C][C]4.1344[/C][C]6.9e-05[/C][/ROW]
[ROW][C]5[/C][C]0.520852[/C][C]3.646[/C][C]0.000322[/C][/ROW]
[ROW][C]6[/C][C]0.447169[/C][C]3.1302[/C][C]0.001471[/C][/ROW]
[ROW][C]7[/C][C]0.3921[/C][C]2.7447[/C][C]0.004221[/C][/ROW]
[ROW][C]8[/C][C]0.35417[/C][C]2.4792[/C][C]0.008328[/C][/ROW]
[ROW][C]9[/C][C]0.318234[/C][C]2.2276[/C][C]0.015264[/C][/ROW]
[ROW][C]10[/C][C]0.225657[/C][C]1.5796[/C][C]0.060317[/C][/ROW]
[ROW][C]11[/C][C]0.155601[/C][C]1.0892[/C][C]0.140696[/C][/ROW]
[ROW][C]12[/C][C]0.014714[/C][C]0.103[/C][C]0.459193[/C][/ROW]
[ROW][C]13[/C][C]0.018876[/C][C]0.1321[/C][C]0.447709[/C][/ROW]
[ROW][C]14[/C][C]-0.068878[/C][C]-0.4821[/C][C]0.315926[/C][/ROW]
[ROW][C]15[/C][C]-0.085562[/C][C]-0.5989[/C][C]0.275989[/C][/ROW]
[ROW][C]16[/C][C]-0.09527[/C][C]-0.6669[/C][C]0.253985[/C][/ROW]
[ROW][C]17[/C][C]-0.146593[/C][C]-1.0261[/C][C]0.154931[/C][/ROW]
[ROW][C]18[/C][C]-0.198313[/C][C]-1.3882[/C][C]0.085679[/C][/ROW]
[ROW][C]19[/C][C]-0.246646[/C][C]-1.7265[/C][C]0.045277[/C][/ROW]
[ROW][C]20[/C][C]-0.289518[/C][C]-2.0266[/C][C]0.02408[/C][/ROW]
[ROW][C]21[/C][C]-0.348015[/C][C]-2.4361[/C][C]0.009264[/C][/ROW]
[ROW][C]22[/C][C]-0.331695[/C][C]-2.3219[/C][C]0.01222[/C][/ROW]
[ROW][C]23[/C][C]-0.354916[/C][C]-2.4844[/C][C]0.008221[/C][/ROW]
[ROW][C]24[/C][C]-0.3376[/C][C]-2.3632[/C][C]0.011065[/C][/ROW]
[ROW][C]25[/C][C]-0.34404[/C][C]-2.4083[/C][C]0.009918[/C][/ROW]
[ROW][C]26[/C][C]-0.308867[/C][C]-2.1621[/C][C]0.017762[/C][/ROW]
[ROW][C]27[/C][C]-0.329019[/C][C]-2.3031[/C][C]0.012778[/C][/ROW]
[ROW][C]28[/C][C]-0.352878[/C][C]-2.4701[/C][C]0.008517[/C][/ROW]
[ROW][C]29[/C][C]-0.360594[/C][C]-2.5242[/C][C]0.007444[/C][/ROW]
[ROW][C]30[/C][C]-0.348778[/C][C]-2.4414[/C][C]0.009143[/C][/ROW]
[ROW][C]31[/C][C]-0.306151[/C][C]-2.1431[/C][C]0.01855[/C][/ROW]
[ROW][C]32[/C][C]-0.268865[/C][C]-1.8821[/C][C]0.032887[/C][/ROW]
[ROW][C]33[/C][C]-0.225879[/C][C]-1.5812[/C][C]0.060138[/C][/ROW]
[ROW][C]34[/C][C]-0.187039[/C][C]-1.3093[/C][C]0.098274[/C][/ROW]
[ROW][C]35[/C][C]-0.11081[/C][C]-0.7757[/C][C]0.220836[/C][/ROW]
[ROW][C]36[/C][C]-0.073843[/C][C]-0.5169[/C][C]0.303775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60610&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60610&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
10.8383065.86810
20.7706425.39451e-06
30.676594.73619e-06
40.590634.13446.9e-05
50.5208523.6460.000322
60.4471693.13020.001471
70.39212.74470.004221
80.354172.47920.008328
90.3182342.22760.015264
100.2256571.57960.060317
110.1556011.08920.140696
120.0147140.1030.459193
130.0188760.13210.447709
14-0.068878-0.48210.315926
15-0.085562-0.59890.275989
16-0.09527-0.66690.253985
17-0.146593-1.02610.154931
18-0.198313-1.38820.085679
19-0.246646-1.72650.045277
20-0.289518-2.02660.02408
21-0.348015-2.43610.009264
22-0.331695-2.32190.01222
23-0.354916-2.48440.008221
24-0.3376-2.36320.011065
25-0.34404-2.40830.009918
26-0.308867-2.16210.017762
27-0.329019-2.30310.012778
28-0.352878-2.47010.008517
29-0.360594-2.52420.007444
30-0.348778-2.44140.009143
31-0.306151-2.14310.01855
32-0.268865-1.88210.032887
33-0.225879-1.58120.060138
34-0.187039-1.30930.098274
35-0.11081-0.77570.220836
36-0.073843-0.51690.303775






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8383065.86810
20.228381.59870.058163
3-0.047402-0.33180.370722
4-0.05066-0.35460.362197
50.0107130.0750.470263
6-0.029546-0.20680.418503
70.0115880.08110.467839
80.0521340.36490.358364
90.013540.09480.462437
10-0.225255-1.57680.06064
11-0.087208-0.61050.272191
12-0.28852-2.01960.024454
130.3264132.28490.013343
14-0.161359-1.12950.13209
150.1199550.83970.202582
160.0006520.00460.49819
17-0.179796-1.25860.107074
18-0.209627-1.46740.07433
190.0173890.12170.451808
200.0416670.29170.385884
21-0.022697-0.15890.437207
220.1177750.82440.206846
23-0.040181-0.28130.389846
24-0.22112-1.54780.064048
250.0788370.55190.291776
26-0.005466-0.03830.484818
270.0210740.14750.441665
28-0.07137-0.49960.3098
29-0.075235-0.52660.300407
300.027880.19520.423039
310.0637430.44620.328708
320.024940.17460.431063
33-0.055059-0.38540.350799
340.2003541.40250.083538
35-0.006046-0.04230.483207
36-0.038741-0.27120.393693

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.838306 & 5.8681 & 0 \tabularnewline
2 & 0.22838 & 1.5987 & 0.058163 \tabularnewline
3 & -0.047402 & -0.3318 & 0.370722 \tabularnewline
4 & -0.05066 & -0.3546 & 0.362197 \tabularnewline
5 & 0.010713 & 0.075 & 0.470263 \tabularnewline
6 & -0.029546 & -0.2068 & 0.418503 \tabularnewline
7 & 0.011588 & 0.0811 & 0.467839 \tabularnewline
8 & 0.052134 & 0.3649 & 0.358364 \tabularnewline
9 & 0.01354 & 0.0948 & 0.462437 \tabularnewline
10 & -0.225255 & -1.5768 & 0.06064 \tabularnewline
11 & -0.087208 & -0.6105 & 0.272191 \tabularnewline
12 & -0.28852 & -2.0196 & 0.024454 \tabularnewline
13 & 0.326413 & 2.2849 & 0.013343 \tabularnewline
14 & -0.161359 & -1.1295 & 0.13209 \tabularnewline
15 & 0.119955 & 0.8397 & 0.202582 \tabularnewline
16 & 0.000652 & 0.0046 & 0.49819 \tabularnewline
17 & -0.179796 & -1.2586 & 0.107074 \tabularnewline
18 & -0.209627 & -1.4674 & 0.07433 \tabularnewline
19 & 0.017389 & 0.1217 & 0.451808 \tabularnewline
20 & 0.041667 & 0.2917 & 0.385884 \tabularnewline
21 & -0.022697 & -0.1589 & 0.437207 \tabularnewline
22 & 0.117775 & 0.8244 & 0.206846 \tabularnewline
23 & -0.040181 & -0.2813 & 0.389846 \tabularnewline
24 & -0.22112 & -1.5478 & 0.064048 \tabularnewline
25 & 0.078837 & 0.5519 & 0.291776 \tabularnewline
26 & -0.005466 & -0.0383 & 0.484818 \tabularnewline
27 & 0.021074 & 0.1475 & 0.441665 \tabularnewline
28 & -0.07137 & -0.4996 & 0.3098 \tabularnewline
29 & -0.075235 & -0.5266 & 0.300407 \tabularnewline
30 & 0.02788 & 0.1952 & 0.423039 \tabularnewline
31 & 0.063743 & 0.4462 & 0.328708 \tabularnewline
32 & 0.02494 & 0.1746 & 0.431063 \tabularnewline
33 & -0.055059 & -0.3854 & 0.350799 \tabularnewline
34 & 0.200354 & 1.4025 & 0.083538 \tabularnewline
35 & -0.006046 & -0.0423 & 0.483207 \tabularnewline
36 & -0.038741 & -0.2712 & 0.393693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60610&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]0.838306[/C][C]5.8681[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.22838[/C][C]1.5987[/C][C]0.058163[/C][/ROW]
[ROW][C]3[/C][C]-0.047402[/C][C]-0.3318[/C][C]0.370722[/C][/ROW]
[ROW][C]4[/C][C]-0.05066[/C][C]-0.3546[/C][C]0.362197[/C][/ROW]
[ROW][C]5[/C][C]0.010713[/C][C]0.075[/C][C]0.470263[/C][/ROW]
[ROW][C]6[/C][C]-0.029546[/C][C]-0.2068[/C][C]0.418503[/C][/ROW]
[ROW][C]7[/C][C]0.011588[/C][C]0.0811[/C][C]0.467839[/C][/ROW]
[ROW][C]8[/C][C]0.052134[/C][C]0.3649[/C][C]0.358364[/C][/ROW]
[ROW][C]9[/C][C]0.01354[/C][C]0.0948[/C][C]0.462437[/C][/ROW]
[ROW][C]10[/C][C]-0.225255[/C][C]-1.5768[/C][C]0.06064[/C][/ROW]
[ROW][C]11[/C][C]-0.087208[/C][C]-0.6105[/C][C]0.272191[/C][/ROW]
[ROW][C]12[/C][C]-0.28852[/C][C]-2.0196[/C][C]0.024454[/C][/ROW]
[ROW][C]13[/C][C]0.326413[/C][C]2.2849[/C][C]0.013343[/C][/ROW]
[ROW][C]14[/C][C]-0.161359[/C][C]-1.1295[/C][C]0.13209[/C][/ROW]
[ROW][C]15[/C][C]0.119955[/C][C]0.8397[/C][C]0.202582[/C][/ROW]
[ROW][C]16[/C][C]0.000652[/C][C]0.0046[/C][C]0.49819[/C][/ROW]
[ROW][C]17[/C][C]-0.179796[/C][C]-1.2586[/C][C]0.107074[/C][/ROW]
[ROW][C]18[/C][C]-0.209627[/C][C]-1.4674[/C][C]0.07433[/C][/ROW]
[ROW][C]19[/C][C]0.017389[/C][C]0.1217[/C][C]0.451808[/C][/ROW]
[ROW][C]20[/C][C]0.041667[/C][C]0.2917[/C][C]0.385884[/C][/ROW]
[ROW][C]21[/C][C]-0.022697[/C][C]-0.1589[/C][C]0.437207[/C][/ROW]
[ROW][C]22[/C][C]0.117775[/C][C]0.8244[/C][C]0.206846[/C][/ROW]
[ROW][C]23[/C][C]-0.040181[/C][C]-0.2813[/C][C]0.389846[/C][/ROW]
[ROW][C]24[/C][C]-0.22112[/C][C]-1.5478[/C][C]0.064048[/C][/ROW]
[ROW][C]25[/C][C]0.078837[/C][C]0.5519[/C][C]0.291776[/C][/ROW]
[ROW][C]26[/C][C]-0.005466[/C][C]-0.0383[/C][C]0.484818[/C][/ROW]
[ROW][C]27[/C][C]0.021074[/C][C]0.1475[/C][C]0.441665[/C][/ROW]
[ROW][C]28[/C][C]-0.07137[/C][C]-0.4996[/C][C]0.3098[/C][/ROW]
[ROW][C]29[/C][C]-0.075235[/C][C]-0.5266[/C][C]0.300407[/C][/ROW]
[ROW][C]30[/C][C]0.02788[/C][C]0.1952[/C][C]0.423039[/C][/ROW]
[ROW][C]31[/C][C]0.063743[/C][C]0.4462[/C][C]0.328708[/C][/ROW]
[ROW][C]32[/C][C]0.02494[/C][C]0.1746[/C][C]0.431063[/C][/ROW]
[ROW][C]33[/C][C]-0.055059[/C][C]-0.3854[/C][C]0.350799[/C][/ROW]
[ROW][C]34[/C][C]0.200354[/C][C]1.4025[/C][C]0.083538[/C][/ROW]
[ROW][C]35[/C][C]-0.006046[/C][C]-0.0423[/C][C]0.483207[/C][/ROW]
[ROW][C]36[/C][C]-0.038741[/C][C]-0.2712[/C][C]0.393693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60610&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60610&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
10.8383065.86810
20.228381.59870.058163
3-0.047402-0.33180.370722
4-0.05066-0.35460.362197
50.0107130.0750.470263
6-0.029546-0.20680.418503
70.0115880.08110.467839
80.0521340.36490.358364
90.013540.09480.462437
10-0.225255-1.57680.06064
11-0.087208-0.61050.272191
12-0.28852-2.01960.024454
130.3264132.28490.013343
14-0.161359-1.12950.13209
150.1199550.83970.202582
160.0006520.00460.49819
17-0.179796-1.25860.107074
18-0.209627-1.46740.07433
190.0173890.12170.451808
200.0416670.29170.385884
21-0.022697-0.15890.437207
220.1177750.82440.206846
23-0.040181-0.28130.389846
24-0.22112-1.54780.064048
250.0788370.55190.291776
26-0.005466-0.03830.484818
270.0210740.14750.441665
28-0.07137-0.49960.3098
29-0.075235-0.52660.300407
300.027880.19520.423039
310.0637430.44620.328708
320.024940.17460.431063
33-0.055059-0.38540.350799
340.2003541.40250.083538
35-0.006046-0.04230.483207
36-0.038741-0.27120.393693


Figures (Output of Computation)

Input Parameters & R Code

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