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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 computationMon, 30 Nov 2009 04:44:53 -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/30/t1259581533ste6vd5wzwrzqcq.htm/, Retrieved Wed, 01 May 2024 20:42:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61727, Retrieved Wed, 01 May 2024 20:42:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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] [ACF D=d=o, lambda=1] [2009-11-30 11:39:52] [005293453b571dbccb80b45226e44173]
-   P             [(Partial) Autocorrelation Function] [ACF d=D=lambda=1] [2009-11-30 11:44:53] [b02b8a83db8a631da1ab9c106b4cdcf2] [Current]
-   P               [(Partial) Autocorrelation Function] [d=2 en D=1] [2009-11-30 19:33:11] [cd6314e7e707a6546bd4604c9d1f2b69]
-   P                 [(Partial) Autocorrelation Function] [d=1 en D=2] [2009-11-30 19:37:11] [cd6314e7e707a6546bd4604c9d1f2b69]
-   P                   [(Partial) Autocorrelation Function] [d=D=2] [2009-11-30 19:39:04] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
244.576
241.572
240.541
236.089
236.997
264.579
270.349
269.645
267.037
258.113
262.813
267.413
267.366
264.777
258.863
254.844
254.868
277.267
285.351
286.602
283.042
276.687
277.915
277.128
277.103
275.037
270.150
267.140
264.993
287.259
291.186
292.300
288.186
281.477
282.656
280.190
280.408
276.836
275.216
274.352
271.311
289.802
290.726
292.300
278.506
269.826
265.861
269.034
264.176
255.198
253.353
246.057
235.372
258.556
260.993
254.663
250.643
243.422
247.105
248.541
245.039
237.080
237.085
225.554
226.839
247.934
248.333
246.969
245.098
246.263
255.765
264.319
268.347
273.046
273.963
267.430
271.993
292.710
295.881

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=61727&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=61727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61727&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
10.1140340.92640.178802
20.2913832.36720.010432
30.3291212.67380.004722
40.1887931.53380.064934
50.0991870.80580.211626
60.2213271.79810.03837
70.0913770.74240.230253
80.1654151.34380.091801
90.1043340.84760.199858
10-0.075943-0.6170.269689
110.3236132.6290.005321
12-0.132632-1.07750.142588
130.0413190.33570.36909
140.110010.89370.187357
150.0749710.60910.272284
16-0.045142-0.36670.357496
170.0928690.75450.226625
18-0.079744-0.64780.259666
190.0125720.10210.45948
20-0.073345-0.59590.276653
21-0.117155-0.95180.172343
22-0.00729-0.05920.476475
23-0.171724-1.39510.083832
24-0.141254-1.14760.127648
25-0.118431-0.96210.169747
26-0.049247-0.40010.345193
27-0.147319-1.19680.117828
28-0.084788-0.68880.246675
29-0.064767-0.52620.300266
30-0.080606-0.65480.257422
31-0.061788-0.5020.308681
320.0042410.03450.486309
33-0.050752-0.41230.340724
34-0.075166-0.61070.271763
350.0640220.52010.30236
36-0.086548-0.70310.242228

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.114034 & 0.9264 & 0.178802 \tabularnewline
2 & 0.291383 & 2.3672 & 0.010432 \tabularnewline
3 & 0.329121 & 2.6738 & 0.004722 \tabularnewline
4 & 0.188793 & 1.5338 & 0.064934 \tabularnewline
5 & 0.099187 & 0.8058 & 0.211626 \tabularnewline
6 & 0.221327 & 1.7981 & 0.03837 \tabularnewline
7 & 0.091377 & 0.7424 & 0.230253 \tabularnewline
8 & 0.165415 & 1.3438 & 0.091801 \tabularnewline
9 & 0.104334 & 0.8476 & 0.199858 \tabularnewline
10 & -0.075943 & -0.617 & 0.269689 \tabularnewline
11 & 0.323613 & 2.629 & 0.005321 \tabularnewline
12 & -0.132632 & -1.0775 & 0.142588 \tabularnewline
13 & 0.041319 & 0.3357 & 0.36909 \tabularnewline
14 & 0.11001 & 0.8937 & 0.187357 \tabularnewline
15 & 0.074971 & 0.6091 & 0.272284 \tabularnewline
16 & -0.045142 & -0.3667 & 0.357496 \tabularnewline
17 & 0.092869 & 0.7545 & 0.226625 \tabularnewline
18 & -0.079744 & -0.6478 & 0.259666 \tabularnewline
19 & 0.012572 & 0.1021 & 0.45948 \tabularnewline
20 & -0.073345 & -0.5959 & 0.276653 \tabularnewline
21 & -0.117155 & -0.9518 & 0.172343 \tabularnewline
22 & -0.00729 & -0.0592 & 0.476475 \tabularnewline
23 & -0.171724 & -1.3951 & 0.083832 \tabularnewline
24 & -0.141254 & -1.1476 & 0.127648 \tabularnewline
25 & -0.118431 & -0.9621 & 0.169747 \tabularnewline
26 & -0.049247 & -0.4001 & 0.345193 \tabularnewline
27 & -0.147319 & -1.1968 & 0.117828 \tabularnewline
28 & -0.084788 & -0.6888 & 0.246675 \tabularnewline
29 & -0.064767 & -0.5262 & 0.300266 \tabularnewline
30 & -0.080606 & -0.6548 & 0.257422 \tabularnewline
31 & -0.061788 & -0.502 & 0.308681 \tabularnewline
32 & 0.004241 & 0.0345 & 0.486309 \tabularnewline
33 & -0.050752 & -0.4123 & 0.340724 \tabularnewline
34 & -0.075166 & -0.6107 & 0.271763 \tabularnewline
35 & 0.064022 & 0.5201 & 0.30236 \tabularnewline
36 & -0.086548 & -0.7031 & 0.242228 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61727&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]0.114034[/C][C]0.9264[/C][C]0.178802[/C][/ROW]
[ROW][C]2[/C][C]0.291383[/C][C]2.3672[/C][C]0.010432[/C][/ROW]
[ROW][C]3[/C][C]0.329121[/C][C]2.6738[/C][C]0.004722[/C][/ROW]
[ROW][C]4[/C][C]0.188793[/C][C]1.5338[/C][C]0.064934[/C][/ROW]
[ROW][C]5[/C][C]0.099187[/C][C]0.8058[/C][C]0.211626[/C][/ROW]
[ROW][C]6[/C][C]0.221327[/C][C]1.7981[/C][C]0.03837[/C][/ROW]
[ROW][C]7[/C][C]0.091377[/C][C]0.7424[/C][C]0.230253[/C][/ROW]
[ROW][C]8[/C][C]0.165415[/C][C]1.3438[/C][C]0.091801[/C][/ROW]
[ROW][C]9[/C][C]0.104334[/C][C]0.8476[/C][C]0.199858[/C][/ROW]
[ROW][C]10[/C][C]-0.075943[/C][C]-0.617[/C][C]0.269689[/C][/ROW]
[ROW][C]11[/C][C]0.323613[/C][C]2.629[/C][C]0.005321[/C][/ROW]
[ROW][C]12[/C][C]-0.132632[/C][C]-1.0775[/C][C]0.142588[/C][/ROW]
[ROW][C]13[/C][C]0.041319[/C][C]0.3357[/C][C]0.36909[/C][/ROW]
[ROW][C]14[/C][C]0.11001[/C][C]0.8937[/C][C]0.187357[/C][/ROW]
[ROW][C]15[/C][C]0.074971[/C][C]0.6091[/C][C]0.272284[/C][/ROW]
[ROW][C]16[/C][C]-0.045142[/C][C]-0.3667[/C][C]0.357496[/C][/ROW]
[ROW][C]17[/C][C]0.092869[/C][C]0.7545[/C][C]0.226625[/C][/ROW]
[ROW][C]18[/C][C]-0.079744[/C][C]-0.6478[/C][C]0.259666[/C][/ROW]
[ROW][C]19[/C][C]0.012572[/C][C]0.1021[/C][C]0.45948[/C][/ROW]
[ROW][C]20[/C][C]-0.073345[/C][C]-0.5959[/C][C]0.276653[/C][/ROW]
[ROW][C]21[/C][C]-0.117155[/C][C]-0.9518[/C][C]0.172343[/C][/ROW]
[ROW][C]22[/C][C]-0.00729[/C][C]-0.0592[/C][C]0.476475[/C][/ROW]
[ROW][C]23[/C][C]-0.171724[/C][C]-1.3951[/C][C]0.083832[/C][/ROW]
[ROW][C]24[/C][C]-0.141254[/C][C]-1.1476[/C][C]0.127648[/C][/ROW]
[ROW][C]25[/C][C]-0.118431[/C][C]-0.9621[/C][C]0.169747[/C][/ROW]
[ROW][C]26[/C][C]-0.049247[/C][C]-0.4001[/C][C]0.345193[/C][/ROW]
[ROW][C]27[/C][C]-0.147319[/C][C]-1.1968[/C][C]0.117828[/C][/ROW]
[ROW][C]28[/C][C]-0.084788[/C][C]-0.6888[/C][C]0.246675[/C][/ROW]
[ROW][C]29[/C][C]-0.064767[/C][C]-0.5262[/C][C]0.300266[/C][/ROW]
[ROW][C]30[/C][C]-0.080606[/C][C]-0.6548[/C][C]0.257422[/C][/ROW]
[ROW][C]31[/C][C]-0.061788[/C][C]-0.502[/C][C]0.308681[/C][/ROW]
[ROW][C]32[/C][C]0.004241[/C][C]0.0345[/C][C]0.486309[/C][/ROW]
[ROW][C]33[/C][C]-0.050752[/C][C]-0.4123[/C][C]0.340724[/C][/ROW]
[ROW][C]34[/C][C]-0.075166[/C][C]-0.6107[/C][C]0.271763[/C][/ROW]
[ROW][C]35[/C][C]0.064022[/C][C]0.5201[/C][C]0.30236[/C][/ROW]
[ROW][C]36[/C][C]-0.086548[/C][C]-0.7031[/C][C]0.242228[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61727&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
10.1140340.92640.178802
20.2913832.36720.010432
30.3291212.67380.004722
40.1887931.53380.064934
50.0991870.80580.211626
60.2213271.79810.03837
70.0913770.74240.230253
80.1654151.34380.091801
90.1043340.84760.199858
10-0.075943-0.6170.269689
110.3236132.6290.005321
12-0.132632-1.07750.142588
130.0413190.33570.36909
140.110010.89370.187357
150.0749710.60910.272284
16-0.045142-0.36670.357496
170.0928690.75450.226625
18-0.079744-0.64780.259666
190.0125720.10210.45948
20-0.073345-0.59590.276653
21-0.117155-0.95180.172343
22-0.00729-0.05920.476475
23-0.171724-1.39510.083832
24-0.141254-1.14760.127648
25-0.118431-0.96210.169747
26-0.049247-0.40010.345193
27-0.147319-1.19680.117828
28-0.084788-0.68880.246675
29-0.064767-0.52620.300266
30-0.080606-0.65480.257422
31-0.061788-0.5020.308681
320.0042410.03450.486309
33-0.050752-0.41230.340724
34-0.075166-0.61070.271763
350.0640220.52010.30236
36-0.086548-0.70310.242228






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1140340.92640.178802
20.2820472.29140.012571
30.3006152.44220.008642
40.0973640.7910.215892
5-0.085511-0.69470.244844
60.0634740.51570.303904
70.0064590.05250.479154
80.0938970.76280.224144
90.0065490.05320.478865
10-0.22985-1.86730.03315
110.2936442.38560.009965
12-0.189155-1.53670.064573
13-0.01313-0.10670.457687
140.0449320.3650.358129
150.0891270.72410.235792
16-0.00258-0.0210.491672
17-0.092611-0.75240.227251
18-0.087864-0.71380.238931
19-0.007822-0.06360.47476
20-0.072469-0.58870.279021
21-0.010045-0.08160.467603
22-0.128931-1.04740.149359
23-0.019628-0.15950.436898
24-0.067009-0.54440.294005
25-0.074461-0.60490.273652
260.1050070.85310.198349
270.044190.3590.360371
28-0.073425-0.59650.276437
290.0668790.54330.294367
30-0.081634-0.66320.254756
310.1104040.89690.186508
320.0814480.66170.255237
33-0.0581-0.4720.319238
34-0.05517-0.44820.327738
350.1287411.04590.149713
36-0.034183-0.27770.391055

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.114034 & 0.9264 & 0.178802 \tabularnewline
2 & 0.282047 & 2.2914 & 0.012571 \tabularnewline
3 & 0.300615 & 2.4422 & 0.008642 \tabularnewline
4 & 0.097364 & 0.791 & 0.215892 \tabularnewline
5 & -0.085511 & -0.6947 & 0.244844 \tabularnewline
6 & 0.063474 & 0.5157 & 0.303904 \tabularnewline
7 & 0.006459 & 0.0525 & 0.479154 \tabularnewline
8 & 0.093897 & 0.7628 & 0.224144 \tabularnewline
9 & 0.006549 & 0.0532 & 0.478865 \tabularnewline
10 & -0.22985 & -1.8673 & 0.03315 \tabularnewline
11 & 0.293644 & 2.3856 & 0.009965 \tabularnewline
12 & -0.189155 & -1.5367 & 0.064573 \tabularnewline
13 & -0.01313 & -0.1067 & 0.457687 \tabularnewline
14 & 0.044932 & 0.365 & 0.358129 \tabularnewline
15 & 0.089127 & 0.7241 & 0.235792 \tabularnewline
16 & -0.00258 & -0.021 & 0.491672 \tabularnewline
17 & -0.092611 & -0.7524 & 0.227251 \tabularnewline
18 & -0.087864 & -0.7138 & 0.238931 \tabularnewline
19 & -0.007822 & -0.0636 & 0.47476 \tabularnewline
20 & -0.072469 & -0.5887 & 0.279021 \tabularnewline
21 & -0.010045 & -0.0816 & 0.467603 \tabularnewline
22 & -0.128931 & -1.0474 & 0.149359 \tabularnewline
23 & -0.019628 & -0.1595 & 0.436898 \tabularnewline
24 & -0.067009 & -0.5444 & 0.294005 \tabularnewline
25 & -0.074461 & -0.6049 & 0.273652 \tabularnewline
26 & 0.105007 & 0.8531 & 0.198349 \tabularnewline
27 & 0.04419 & 0.359 & 0.360371 \tabularnewline
28 & -0.073425 & -0.5965 & 0.276437 \tabularnewline
29 & 0.066879 & 0.5433 & 0.294367 \tabularnewline
30 & -0.081634 & -0.6632 & 0.254756 \tabularnewline
31 & 0.110404 & 0.8969 & 0.186508 \tabularnewline
32 & 0.081448 & 0.6617 & 0.255237 \tabularnewline
33 & -0.0581 & -0.472 & 0.319238 \tabularnewline
34 & -0.05517 & -0.4482 & 0.327738 \tabularnewline
35 & 0.128741 & 1.0459 & 0.149713 \tabularnewline
36 & -0.034183 & -0.2777 & 0.391055 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61727&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]0.114034[/C][C]0.9264[/C][C]0.178802[/C][/ROW]
[ROW][C]2[/C][C]0.282047[/C][C]2.2914[/C][C]0.012571[/C][/ROW]
[ROW][C]3[/C][C]0.300615[/C][C]2.4422[/C][C]0.008642[/C][/ROW]
[ROW][C]4[/C][C]0.097364[/C][C]0.791[/C][C]0.215892[/C][/ROW]
[ROW][C]5[/C][C]-0.085511[/C][C]-0.6947[/C][C]0.244844[/C][/ROW]
[ROW][C]6[/C][C]0.063474[/C][C]0.5157[/C][C]0.303904[/C][/ROW]
[ROW][C]7[/C][C]0.006459[/C][C]0.0525[/C][C]0.479154[/C][/ROW]
[ROW][C]8[/C][C]0.093897[/C][C]0.7628[/C][C]0.224144[/C][/ROW]
[ROW][C]9[/C][C]0.006549[/C][C]0.0532[/C][C]0.478865[/C][/ROW]
[ROW][C]10[/C][C]-0.22985[/C][C]-1.8673[/C][C]0.03315[/C][/ROW]
[ROW][C]11[/C][C]0.293644[/C][C]2.3856[/C][C]0.009965[/C][/ROW]
[ROW][C]12[/C][C]-0.189155[/C][C]-1.5367[/C][C]0.064573[/C][/ROW]
[ROW][C]13[/C][C]-0.01313[/C][C]-0.1067[/C][C]0.457687[/C][/ROW]
[ROW][C]14[/C][C]0.044932[/C][C]0.365[/C][C]0.358129[/C][/ROW]
[ROW][C]15[/C][C]0.089127[/C][C]0.7241[/C][C]0.235792[/C][/ROW]
[ROW][C]16[/C][C]-0.00258[/C][C]-0.021[/C][C]0.491672[/C][/ROW]
[ROW][C]17[/C][C]-0.092611[/C][C]-0.7524[/C][C]0.227251[/C][/ROW]
[ROW][C]18[/C][C]-0.087864[/C][C]-0.7138[/C][C]0.238931[/C][/ROW]
[ROW][C]19[/C][C]-0.007822[/C][C]-0.0636[/C][C]0.47476[/C][/ROW]
[ROW][C]20[/C][C]-0.072469[/C][C]-0.5887[/C][C]0.279021[/C][/ROW]
[ROW][C]21[/C][C]-0.010045[/C][C]-0.0816[/C][C]0.467603[/C][/ROW]
[ROW][C]22[/C][C]-0.128931[/C][C]-1.0474[/C][C]0.149359[/C][/ROW]
[ROW][C]23[/C][C]-0.019628[/C][C]-0.1595[/C][C]0.436898[/C][/ROW]
[ROW][C]24[/C][C]-0.067009[/C][C]-0.5444[/C][C]0.294005[/C][/ROW]
[ROW][C]25[/C][C]-0.074461[/C][C]-0.6049[/C][C]0.273652[/C][/ROW]
[ROW][C]26[/C][C]0.105007[/C][C]0.8531[/C][C]0.198349[/C][/ROW]
[ROW][C]27[/C][C]0.04419[/C][C]0.359[/C][C]0.360371[/C][/ROW]
[ROW][C]28[/C][C]-0.073425[/C][C]-0.5965[/C][C]0.276437[/C][/ROW]
[ROW][C]29[/C][C]0.066879[/C][C]0.5433[/C][C]0.294367[/C][/ROW]
[ROW][C]30[/C][C]-0.081634[/C][C]-0.6632[/C][C]0.254756[/C][/ROW]
[ROW][C]31[/C][C]0.110404[/C][C]0.8969[/C][C]0.186508[/C][/ROW]
[ROW][C]32[/C][C]0.081448[/C][C]0.6617[/C][C]0.255237[/C][/ROW]
[ROW][C]33[/C][C]-0.0581[/C][C]-0.472[/C][C]0.319238[/C][/ROW]
[ROW][C]34[/C][C]-0.05517[/C][C]-0.4482[/C][C]0.327738[/C][/ROW]
[ROW][C]35[/C][C]0.128741[/C][C]1.0459[/C][C]0.149713[/C][/ROW]
[ROW][C]36[/C][C]-0.034183[/C][C]-0.2777[/C][C]0.391055[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61727&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61727&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
10.1140340.92640.178802
20.2820472.29140.012571
30.3006152.44220.008642
40.0973640.7910.215892
5-0.085511-0.69470.244844
60.0634740.51570.303904
70.0064590.05250.479154
80.0938970.76280.224144
90.0065490.05320.478865
10-0.22985-1.86730.03315
110.2936442.38560.009965
12-0.189155-1.53670.064573
13-0.01313-0.10670.457687
140.0449320.3650.358129
150.0891270.72410.235792
16-0.00258-0.0210.491672
17-0.092611-0.75240.227251
18-0.087864-0.71380.238931
19-0.007822-0.06360.47476
20-0.072469-0.58870.279021
21-0.010045-0.08160.467603
22-0.128931-1.04740.149359
23-0.019628-0.15950.436898
24-0.067009-0.54440.294005
25-0.074461-0.60490.273652
260.1050070.85310.198349
270.044190.3590.360371
28-0.073425-0.59650.276437
290.0668790.54330.294367
30-0.081634-0.66320.254756
310.1104040.89690.186508
320.0814480.66170.255237
33-0.0581-0.4720.319238
34-0.05517-0.44820.327738
350.1287411.04590.149713
36-0.034183-0.27770.391055


Figures (Output of Computation)

Input Parameters & R Code

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