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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 10:21:41 -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/t1259342543bk7odqy3rszrymw.htm/, Retrieved Mon, 29 Apr 2024 05:53:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61027, Retrieved Mon, 29 Apr 2024 05:53:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

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]
F   PD        [(Partial) Autocorrelation Function] [workshop 8.2] [2009-11-25 20:32:59] [35f0fff14d789f48983afb62e692bd0d]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-27 17:21:41] [71596e6a53ccce532e52aaf6113616ef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
252.5
251.1
255.1
258.3
255.3
261.1
253.8
252.9
253.9
255.5
262
262.8
263.3
262.5
269.2
270.8
274.1
273
267.3
267.1
268.2
270.2
271.5
281
280.1
281.5
285.9
289.8
292.9
291.2
291.8
289.8
292.5
290.3
297.5
307.5
304.7
304.6
310.7
310.7
315.7
314.7
312.2
312.8
314.3
319.7
319.9
329.5
326.9
329.7
335.7
337.2
339.7
338.3
339.2
342.5
342.2
338.3
339
345.9

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=61027&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=61027&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61027&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
1-0.514831-3.92080.000118
20.0259440.19760.422031
30.0621480.47330.318887
4-0.162549-1.23790.110364
50.1494911.13850.129798
6-0.086942-0.66210.255256
70.1441831.09810.138357
8-0.254736-1.940.028623
90.2577021.96260.027248
10-0.233672-1.77960.040191
11-0.010079-0.07680.469538
120.2818442.14650.018015
13-0.101178-0.77050.222052
14-0.12097-0.92130.180359
150.1781241.35660.09009
16-0.116845-0.88990.188607
17-0.070971-0.54050.29546
180.1693351.28960.101151
19-0.164378-1.25190.107822
200.062790.47820.317154
210.087990.67010.252723
22-0.097954-0.7460.229341
23-0.142052-1.08180.141902
240.2435511.85480.034353
25-0.024499-0.18660.42632
26-0.069065-0.5260.300453
270.0733560.55870.289271
28-0.07624-0.58060.28187
29-0.035317-0.2690.394454
300.1002450.76340.224147
31-0.063061-0.48030.316425
32-0.063891-0.48660.314195
330.2121621.61580.055785
34-0.274373-2.08960.020527
350.1431641.09030.140043
360.0126270.09620.461862

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.514831 & -3.9208 & 0.000118 \tabularnewline
2 & 0.025944 & 0.1976 & 0.422031 \tabularnewline
3 & 0.062148 & 0.4733 & 0.318887 \tabularnewline
4 & -0.162549 & -1.2379 & 0.110364 \tabularnewline
5 & 0.149491 & 1.1385 & 0.129798 \tabularnewline
6 & -0.086942 & -0.6621 & 0.255256 \tabularnewline
7 & 0.144183 & 1.0981 & 0.138357 \tabularnewline
8 & -0.254736 & -1.94 & 0.028623 \tabularnewline
9 & 0.257702 & 1.9626 & 0.027248 \tabularnewline
10 & -0.233672 & -1.7796 & 0.040191 \tabularnewline
11 & -0.010079 & -0.0768 & 0.469538 \tabularnewline
12 & 0.281844 & 2.1465 & 0.018015 \tabularnewline
13 & -0.101178 & -0.7705 & 0.222052 \tabularnewline
14 & -0.12097 & -0.9213 & 0.180359 \tabularnewline
15 & 0.178124 & 1.3566 & 0.09009 \tabularnewline
16 & -0.116845 & -0.8899 & 0.188607 \tabularnewline
17 & -0.070971 & -0.5405 & 0.29546 \tabularnewline
18 & 0.169335 & 1.2896 & 0.101151 \tabularnewline
19 & -0.164378 & -1.2519 & 0.107822 \tabularnewline
20 & 0.06279 & 0.4782 & 0.317154 \tabularnewline
21 & 0.08799 & 0.6701 & 0.252723 \tabularnewline
22 & -0.097954 & -0.746 & 0.229341 \tabularnewline
23 & -0.142052 & -1.0818 & 0.141902 \tabularnewline
24 & 0.243551 & 1.8548 & 0.034353 \tabularnewline
25 & -0.024499 & -0.1866 & 0.42632 \tabularnewline
26 & -0.069065 & -0.526 & 0.300453 \tabularnewline
27 & 0.073356 & 0.5587 & 0.289271 \tabularnewline
28 & -0.07624 & -0.5806 & 0.28187 \tabularnewline
29 & -0.035317 & -0.269 & 0.394454 \tabularnewline
30 & 0.100245 & 0.7634 & 0.224147 \tabularnewline
31 & -0.063061 & -0.4803 & 0.316425 \tabularnewline
32 & -0.063891 & -0.4866 & 0.314195 \tabularnewline
33 & 0.212162 & 1.6158 & 0.055785 \tabularnewline
34 & -0.274373 & -2.0896 & 0.020527 \tabularnewline
35 & 0.143164 & 1.0903 & 0.140043 \tabularnewline
36 & 0.012627 & 0.0962 & 0.461862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61027&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]-0.514831[/C][C]-3.9208[/C][C]0.000118[/C][/ROW]
[ROW][C]2[/C][C]0.025944[/C][C]0.1976[/C][C]0.422031[/C][/ROW]
[ROW][C]3[/C][C]0.062148[/C][C]0.4733[/C][C]0.318887[/C][/ROW]
[ROW][C]4[/C][C]-0.162549[/C][C]-1.2379[/C][C]0.110364[/C][/ROW]
[ROW][C]5[/C][C]0.149491[/C][C]1.1385[/C][C]0.129798[/C][/ROW]
[ROW][C]6[/C][C]-0.086942[/C][C]-0.6621[/C][C]0.255256[/C][/ROW]
[ROW][C]7[/C][C]0.144183[/C][C]1.0981[/C][C]0.138357[/C][/ROW]
[ROW][C]8[/C][C]-0.254736[/C][C]-1.94[/C][C]0.028623[/C][/ROW]
[ROW][C]9[/C][C]0.257702[/C][C]1.9626[/C][C]0.027248[/C][/ROW]
[ROW][C]10[/C][C]-0.233672[/C][C]-1.7796[/C][C]0.040191[/C][/ROW]
[ROW][C]11[/C][C]-0.010079[/C][C]-0.0768[/C][C]0.469538[/C][/ROW]
[ROW][C]12[/C][C]0.281844[/C][C]2.1465[/C][C]0.018015[/C][/ROW]
[ROW][C]13[/C][C]-0.101178[/C][C]-0.7705[/C][C]0.222052[/C][/ROW]
[ROW][C]14[/C][C]-0.12097[/C][C]-0.9213[/C][C]0.180359[/C][/ROW]
[ROW][C]15[/C][C]0.178124[/C][C]1.3566[/C][C]0.09009[/C][/ROW]
[ROW][C]16[/C][C]-0.116845[/C][C]-0.8899[/C][C]0.188607[/C][/ROW]
[ROW][C]17[/C][C]-0.070971[/C][C]-0.5405[/C][C]0.29546[/C][/ROW]
[ROW][C]18[/C][C]0.169335[/C][C]1.2896[/C][C]0.101151[/C][/ROW]
[ROW][C]19[/C][C]-0.164378[/C][C]-1.2519[/C][C]0.107822[/C][/ROW]
[ROW][C]20[/C][C]0.06279[/C][C]0.4782[/C][C]0.317154[/C][/ROW]
[ROW][C]21[/C][C]0.08799[/C][C]0.6701[/C][C]0.252723[/C][/ROW]
[ROW][C]22[/C][C]-0.097954[/C][C]-0.746[/C][C]0.229341[/C][/ROW]
[ROW][C]23[/C][C]-0.142052[/C][C]-1.0818[/C][C]0.141902[/C][/ROW]
[ROW][C]24[/C][C]0.243551[/C][C]1.8548[/C][C]0.034353[/C][/ROW]
[ROW][C]25[/C][C]-0.024499[/C][C]-0.1866[/C][C]0.42632[/C][/ROW]
[ROW][C]26[/C][C]-0.069065[/C][C]-0.526[/C][C]0.300453[/C][/ROW]
[ROW][C]27[/C][C]0.073356[/C][C]0.5587[/C][C]0.289271[/C][/ROW]
[ROW][C]28[/C][C]-0.07624[/C][C]-0.5806[/C][C]0.28187[/C][/ROW]
[ROW][C]29[/C][C]-0.035317[/C][C]-0.269[/C][C]0.394454[/C][/ROW]
[ROW][C]30[/C][C]0.100245[/C][C]0.7634[/C][C]0.224147[/C][/ROW]
[ROW][C]31[/C][C]-0.063061[/C][C]-0.4803[/C][C]0.316425[/C][/ROW]
[ROW][C]32[/C][C]-0.063891[/C][C]-0.4866[/C][C]0.314195[/C][/ROW]
[ROW][C]33[/C][C]0.212162[/C][C]1.6158[/C][C]0.055785[/C][/ROW]
[ROW][C]34[/C][C]-0.274373[/C][C]-2.0896[/C][C]0.020527[/C][/ROW]
[ROW][C]35[/C][C]0.143164[/C][C]1.0903[/C][C]0.140043[/C][/ROW]
[ROW][C]36[/C][C]0.012627[/C][C]0.0962[/C][C]0.461862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61027&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61027&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
1-0.514831-3.92080.000118
20.0259440.19760.422031
30.0621480.47330.318887
4-0.162549-1.23790.110364
50.1494911.13850.129798
6-0.086942-0.66210.255256
70.1441831.09810.138357
8-0.254736-1.940.028623
90.2577021.96260.027248
10-0.233672-1.77960.040191
11-0.010079-0.07680.469538
120.2818442.14650.018015
13-0.101178-0.77050.222052
14-0.12097-0.92130.180359
150.1781241.35660.09009
16-0.116845-0.88990.188607
17-0.070971-0.54050.29546
180.1693351.28960.101151
19-0.164378-1.25190.107822
200.062790.47820.317154
210.087990.67010.252723
22-0.097954-0.7460.229341
23-0.142052-1.08180.141902
240.2435511.85480.034353
25-0.024499-0.18660.42632
26-0.069065-0.5260.300453
270.0733560.55870.289271
28-0.07624-0.58060.28187
29-0.035317-0.2690.394454
300.1002450.76340.224147
31-0.063061-0.48030.316425
32-0.063891-0.48660.314195
330.2121621.61580.055785
34-0.274373-2.08960.020527
350.1431641.09030.140043
360.0126270.09620.461862






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.514831-3.92080.000118
2-0.325338-2.47770.008079
3-0.133368-1.01570.156994
4-0.271598-2.06840.021534
5-0.121622-0.92620.179079
6-0.151634-1.15480.126452
70.0854580.65080.258862
8-0.2428-1.84910.03477
90.056420.42970.334509
10-0.237286-1.80710.037966
11-0.3203-2.43930.008897
12-0.066394-0.50560.307512
130.2182691.66230.050925
14-0.152916-1.16460.12448
150.2079761.58390.059327
160.085590.65180.258541
17-0.006438-0.0490.480531
18-0.051861-0.3950.34716
19-0.056385-0.42940.334607
20-0.133749-1.01860.156312
210.1107610.84350.201198
220.0647830.49340.311807
23-0.12373-0.94230.174974
24-0.114119-0.86910.194186
250.0903090.68780.247169
260.0912890.69520.244841
27-0.100555-0.76580.22345
280.0157590.120.452441
290.0178830.13620.44607
300.0020280.01540.493865
31-0.013229-0.10070.460048
32-0.038743-0.29510.384502
33-0.00682-0.05190.479376
34-0.169751-1.29280.100606
350.1306450.9950.161944
36-0.026833-0.20440.419397

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.514831 & -3.9208 & 0.000118 \tabularnewline
2 & -0.325338 & -2.4777 & 0.008079 \tabularnewline
3 & -0.133368 & -1.0157 & 0.156994 \tabularnewline
4 & -0.271598 & -2.0684 & 0.021534 \tabularnewline
5 & -0.121622 & -0.9262 & 0.179079 \tabularnewline
6 & -0.151634 & -1.1548 & 0.126452 \tabularnewline
7 & 0.085458 & 0.6508 & 0.258862 \tabularnewline
8 & -0.2428 & -1.8491 & 0.03477 \tabularnewline
9 & 0.05642 & 0.4297 & 0.334509 \tabularnewline
10 & -0.237286 & -1.8071 & 0.037966 \tabularnewline
11 & -0.3203 & -2.4393 & 0.008897 \tabularnewline
12 & -0.066394 & -0.5056 & 0.307512 \tabularnewline
13 & 0.218269 & 1.6623 & 0.050925 \tabularnewline
14 & -0.152916 & -1.1646 & 0.12448 \tabularnewline
15 & 0.207976 & 1.5839 & 0.059327 \tabularnewline
16 & 0.08559 & 0.6518 & 0.258541 \tabularnewline
17 & -0.006438 & -0.049 & 0.480531 \tabularnewline
18 & -0.051861 & -0.395 & 0.34716 \tabularnewline
19 & -0.056385 & -0.4294 & 0.334607 \tabularnewline
20 & -0.133749 & -1.0186 & 0.156312 \tabularnewline
21 & 0.110761 & 0.8435 & 0.201198 \tabularnewline
22 & 0.064783 & 0.4934 & 0.311807 \tabularnewline
23 & -0.12373 & -0.9423 & 0.174974 \tabularnewline
24 & -0.114119 & -0.8691 & 0.194186 \tabularnewline
25 & 0.090309 & 0.6878 & 0.247169 \tabularnewline
26 & 0.091289 & 0.6952 & 0.244841 \tabularnewline
27 & -0.100555 & -0.7658 & 0.22345 \tabularnewline
28 & 0.015759 & 0.12 & 0.452441 \tabularnewline
29 & 0.017883 & 0.1362 & 0.44607 \tabularnewline
30 & 0.002028 & 0.0154 & 0.493865 \tabularnewline
31 & -0.013229 & -0.1007 & 0.460048 \tabularnewline
32 & -0.038743 & -0.2951 & 0.384502 \tabularnewline
33 & -0.00682 & -0.0519 & 0.479376 \tabularnewline
34 & -0.169751 & -1.2928 & 0.100606 \tabularnewline
35 & 0.130645 & 0.995 & 0.161944 \tabularnewline
36 & -0.026833 & -0.2044 & 0.419397 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61027&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]-0.514831[/C][C]-3.9208[/C][C]0.000118[/C][/ROW]
[ROW][C]2[/C][C]-0.325338[/C][C]-2.4777[/C][C]0.008079[/C][/ROW]
[ROW][C]3[/C][C]-0.133368[/C][C]-1.0157[/C][C]0.156994[/C][/ROW]
[ROW][C]4[/C][C]-0.271598[/C][C]-2.0684[/C][C]0.021534[/C][/ROW]
[ROW][C]5[/C][C]-0.121622[/C][C]-0.9262[/C][C]0.179079[/C][/ROW]
[ROW][C]6[/C][C]-0.151634[/C][C]-1.1548[/C][C]0.126452[/C][/ROW]
[ROW][C]7[/C][C]0.085458[/C][C]0.6508[/C][C]0.258862[/C][/ROW]
[ROW][C]8[/C][C]-0.2428[/C][C]-1.8491[/C][C]0.03477[/C][/ROW]
[ROW][C]9[/C][C]0.05642[/C][C]0.4297[/C][C]0.334509[/C][/ROW]
[ROW][C]10[/C][C]-0.237286[/C][C]-1.8071[/C][C]0.037966[/C][/ROW]
[ROW][C]11[/C][C]-0.3203[/C][C]-2.4393[/C][C]0.008897[/C][/ROW]
[ROW][C]12[/C][C]-0.066394[/C][C]-0.5056[/C][C]0.307512[/C][/ROW]
[ROW][C]13[/C][C]0.218269[/C][C]1.6623[/C][C]0.050925[/C][/ROW]
[ROW][C]14[/C][C]-0.152916[/C][C]-1.1646[/C][C]0.12448[/C][/ROW]
[ROW][C]15[/C][C]0.207976[/C][C]1.5839[/C][C]0.059327[/C][/ROW]
[ROW][C]16[/C][C]0.08559[/C][C]0.6518[/C][C]0.258541[/C][/ROW]
[ROW][C]17[/C][C]-0.006438[/C][C]-0.049[/C][C]0.480531[/C][/ROW]
[ROW][C]18[/C][C]-0.051861[/C][C]-0.395[/C][C]0.34716[/C][/ROW]
[ROW][C]19[/C][C]-0.056385[/C][C]-0.4294[/C][C]0.334607[/C][/ROW]
[ROW][C]20[/C][C]-0.133749[/C][C]-1.0186[/C][C]0.156312[/C][/ROW]
[ROW][C]21[/C][C]0.110761[/C][C]0.8435[/C][C]0.201198[/C][/ROW]
[ROW][C]22[/C][C]0.064783[/C][C]0.4934[/C][C]0.311807[/C][/ROW]
[ROW][C]23[/C][C]-0.12373[/C][C]-0.9423[/C][C]0.174974[/C][/ROW]
[ROW][C]24[/C][C]-0.114119[/C][C]-0.8691[/C][C]0.194186[/C][/ROW]
[ROW][C]25[/C][C]0.090309[/C][C]0.6878[/C][C]0.247169[/C][/ROW]
[ROW][C]26[/C][C]0.091289[/C][C]0.6952[/C][C]0.244841[/C][/ROW]
[ROW][C]27[/C][C]-0.100555[/C][C]-0.7658[/C][C]0.22345[/C][/ROW]
[ROW][C]28[/C][C]0.015759[/C][C]0.12[/C][C]0.452441[/C][/ROW]
[ROW][C]29[/C][C]0.017883[/C][C]0.1362[/C][C]0.44607[/C][/ROW]
[ROW][C]30[/C][C]0.002028[/C][C]0.0154[/C][C]0.493865[/C][/ROW]
[ROW][C]31[/C][C]-0.013229[/C][C]-0.1007[/C][C]0.460048[/C][/ROW]
[ROW][C]32[/C][C]-0.038743[/C][C]-0.2951[/C][C]0.384502[/C][/ROW]
[ROW][C]33[/C][C]-0.00682[/C][C]-0.0519[/C][C]0.479376[/C][/ROW]
[ROW][C]34[/C][C]-0.169751[/C][C]-1.2928[/C][C]0.100606[/C][/ROW]
[ROW][C]35[/C][C]0.130645[/C][C]0.995[/C][C]0.161944[/C][/ROW]
[ROW][C]36[/C][C]-0.026833[/C][C]-0.2044[/C][C]0.419397[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61027&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61027&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
1-0.514831-3.92080.000118
2-0.325338-2.47770.008079
3-0.133368-1.01570.156994
4-0.271598-2.06840.021534
5-0.121622-0.92620.179079
6-0.151634-1.15480.126452
70.0854580.65080.258862
8-0.2428-1.84910.03477
90.056420.42970.334509
10-0.237286-1.80710.037966
11-0.3203-2.43930.008897
12-0.066394-0.50560.307512
130.2182691.66230.050925
14-0.152916-1.16460.12448
150.2079761.58390.059327
160.085590.65180.258541
17-0.006438-0.0490.480531
18-0.051861-0.3950.34716
19-0.056385-0.42940.334607
20-0.133749-1.01860.156312
210.1107610.84350.201198
220.0647830.49340.311807
23-0.12373-0.94230.174974
24-0.114119-0.86910.194186
250.0903090.68780.247169
260.0912890.69520.244841
27-0.100555-0.76580.22345
280.0157590.120.452441
290.0178830.13620.44607
300.0020280.01540.493865
31-0.013229-0.10070.460048
32-0.038743-0.29510.384502
33-0.00682-0.05190.479376
34-0.169751-1.29280.100606
350.1306450.9950.161944
36-0.026833-0.20440.419397


Figures (Output of Computation)

Input Parameters & R Code

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