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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 09:38:38 -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/t125934003622uvmfmyczps6eo.htm/, Retrieved Mon, 29 Apr 2024 02:05:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60978, Retrieved Mon, 29 Apr 2024 02:05:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-27 16:22:38] [9b30bff5dd5a100f8196daf92e735633]
-   P           [(Partial) Autocorrelation Function] [] [2009-11-27 16:35:19] [9b30bff5dd5a100f8196daf92e735633]
-   P               [(Partial) Autocorrelation Function] [] [2009-11-27 16:38:38] [54e293c1fb7c46e2abc5c1dda68d8adb] [Current]
-   P                 [(Partial) Autocorrelation Function] [] [2009-12-04 18:37:56] [badc6a9acdc45286bea7f74742e15a21]
-   P                 [(Partial) Autocorrelation Function] [WS 9 review] [2009-12-09 15:37:33] [830e13ac5e5ac1e5b21c6af0c149b21d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
274412
272433
268361
268586
264768
269974
304744
309365
308347
298427
289231
291975
294912
293488
290555
284736
281818
287854
316263
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860

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=60978&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=60978&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60978&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
10.0846620.68780.246994
20.1223690.99410.161895
30.0501580.40750.342485
40.1062480.86320.195587
50.0677490.55040.291953
60.0437030.3550.361845
70.0340740.27680.391392
80.0917290.74520.229396
90.1076930.87490.1924
10-0.093983-0.76350.223936
110.1862471.51310.067517
12-0.14916-1.21180.114958
13-0.018606-0.15120.440156
140.1367921.11130.135235
150.1317711.07050.144145
160.0205890.16730.433835
17-0.037181-0.30210.381778
180.0524620.42620.335672
190.0858970.69780.243867
200.0486310.39510.34703
21-0.119042-0.96710.168511
220.0212610.17270.431697
230.0519380.42190.337217
24-0.224665-1.82520.036249
25-0.128924-1.04740.149372
26-0.195361-1.58710.058633
27-0.082866-0.67320.251582
28-0.131487-1.06820.14466
290.0143370.11650.453815
30-0.09469-0.76930.22224
31-0.075324-0.61190.271342
32-0.127245-1.03370.152515
330.0014750.0120.495238
340.0396840.32240.374087
35-0.085137-0.69170.245789
36-0.02447-0.19880.421518

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.084662 & 0.6878 & 0.246994 \tabularnewline
2 & 0.122369 & 0.9941 & 0.161895 \tabularnewline
3 & 0.050158 & 0.4075 & 0.342485 \tabularnewline
4 & 0.106248 & 0.8632 & 0.195587 \tabularnewline
5 & 0.067749 & 0.5504 & 0.291953 \tabularnewline
6 & 0.043703 & 0.355 & 0.361845 \tabularnewline
7 & 0.034074 & 0.2768 & 0.391392 \tabularnewline
8 & 0.091729 & 0.7452 & 0.229396 \tabularnewline
9 & 0.107693 & 0.8749 & 0.1924 \tabularnewline
10 & -0.093983 & -0.7635 & 0.223936 \tabularnewline
11 & 0.186247 & 1.5131 & 0.067517 \tabularnewline
12 & -0.14916 & -1.2118 & 0.114958 \tabularnewline
13 & -0.018606 & -0.1512 & 0.440156 \tabularnewline
14 & 0.136792 & 1.1113 & 0.135235 \tabularnewline
15 & 0.131771 & 1.0705 & 0.144145 \tabularnewline
16 & 0.020589 & 0.1673 & 0.433835 \tabularnewline
17 & -0.037181 & -0.3021 & 0.381778 \tabularnewline
18 & 0.052462 & 0.4262 & 0.335672 \tabularnewline
19 & 0.085897 & 0.6978 & 0.243867 \tabularnewline
20 & 0.048631 & 0.3951 & 0.34703 \tabularnewline
21 & -0.119042 & -0.9671 & 0.168511 \tabularnewline
22 & 0.021261 & 0.1727 & 0.431697 \tabularnewline
23 & 0.051938 & 0.4219 & 0.337217 \tabularnewline
24 & -0.224665 & -1.8252 & 0.036249 \tabularnewline
25 & -0.128924 & -1.0474 & 0.149372 \tabularnewline
26 & -0.195361 & -1.5871 & 0.058633 \tabularnewline
27 & -0.082866 & -0.6732 & 0.251582 \tabularnewline
28 & -0.131487 & -1.0682 & 0.14466 \tabularnewline
29 & 0.014337 & 0.1165 & 0.453815 \tabularnewline
30 & -0.09469 & -0.7693 & 0.22224 \tabularnewline
31 & -0.075324 & -0.6119 & 0.271342 \tabularnewline
32 & -0.127245 & -1.0337 & 0.152515 \tabularnewline
33 & 0.001475 & 0.012 & 0.495238 \tabularnewline
34 & 0.039684 & 0.3224 & 0.374087 \tabularnewline
35 & -0.085137 & -0.6917 & 0.245789 \tabularnewline
36 & -0.02447 & -0.1988 & 0.421518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60978&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]0.084662[/C][C]0.6878[/C][C]0.246994[/C][/ROW]
[ROW][C]2[/C][C]0.122369[/C][C]0.9941[/C][C]0.161895[/C][/ROW]
[ROW][C]3[/C][C]0.050158[/C][C]0.4075[/C][C]0.342485[/C][/ROW]
[ROW][C]4[/C][C]0.106248[/C][C]0.8632[/C][C]0.195587[/C][/ROW]
[ROW][C]5[/C][C]0.067749[/C][C]0.5504[/C][C]0.291953[/C][/ROW]
[ROW][C]6[/C][C]0.043703[/C][C]0.355[/C][C]0.361845[/C][/ROW]
[ROW][C]7[/C][C]0.034074[/C][C]0.2768[/C][C]0.391392[/C][/ROW]
[ROW][C]8[/C][C]0.091729[/C][C]0.7452[/C][C]0.229396[/C][/ROW]
[ROW][C]9[/C][C]0.107693[/C][C]0.8749[/C][C]0.1924[/C][/ROW]
[ROW][C]10[/C][C]-0.093983[/C][C]-0.7635[/C][C]0.223936[/C][/ROW]
[ROW][C]11[/C][C]0.186247[/C][C]1.5131[/C][C]0.067517[/C][/ROW]
[ROW][C]12[/C][C]-0.14916[/C][C]-1.2118[/C][C]0.114958[/C][/ROW]
[ROW][C]13[/C][C]-0.018606[/C][C]-0.1512[/C][C]0.440156[/C][/ROW]
[ROW][C]14[/C][C]0.136792[/C][C]1.1113[/C][C]0.135235[/C][/ROW]
[ROW][C]15[/C][C]0.131771[/C][C]1.0705[/C][C]0.144145[/C][/ROW]
[ROW][C]16[/C][C]0.020589[/C][C]0.1673[/C][C]0.433835[/C][/ROW]
[ROW][C]17[/C][C]-0.037181[/C][C]-0.3021[/C][C]0.381778[/C][/ROW]
[ROW][C]18[/C][C]0.052462[/C][C]0.4262[/C][C]0.335672[/C][/ROW]
[ROW][C]19[/C][C]0.085897[/C][C]0.6978[/C][C]0.243867[/C][/ROW]
[ROW][C]20[/C][C]0.048631[/C][C]0.3951[/C][C]0.34703[/C][/ROW]
[ROW][C]21[/C][C]-0.119042[/C][C]-0.9671[/C][C]0.168511[/C][/ROW]
[ROW][C]22[/C][C]0.021261[/C][C]0.1727[/C][C]0.431697[/C][/ROW]
[ROW][C]23[/C][C]0.051938[/C][C]0.4219[/C][C]0.337217[/C][/ROW]
[ROW][C]24[/C][C]-0.224665[/C][C]-1.8252[/C][C]0.036249[/C][/ROW]
[ROW][C]25[/C][C]-0.128924[/C][C]-1.0474[/C][C]0.149372[/C][/ROW]
[ROW][C]26[/C][C]-0.195361[/C][C]-1.5871[/C][C]0.058633[/C][/ROW]
[ROW][C]27[/C][C]-0.082866[/C][C]-0.6732[/C][C]0.251582[/C][/ROW]
[ROW][C]28[/C][C]-0.131487[/C][C]-1.0682[/C][C]0.14466[/C][/ROW]
[ROW][C]29[/C][C]0.014337[/C][C]0.1165[/C][C]0.453815[/C][/ROW]
[ROW][C]30[/C][C]-0.09469[/C][C]-0.7693[/C][C]0.22224[/C][/ROW]
[ROW][C]31[/C][C]-0.075324[/C][C]-0.6119[/C][C]0.271342[/C][/ROW]
[ROW][C]32[/C][C]-0.127245[/C][C]-1.0337[/C][C]0.152515[/C][/ROW]
[ROW][C]33[/C][C]0.001475[/C][C]0.012[/C][C]0.495238[/C][/ROW]
[ROW][C]34[/C][C]0.039684[/C][C]0.3224[/C][C]0.374087[/C][/ROW]
[ROW][C]35[/C][C]-0.085137[/C][C]-0.6917[/C][C]0.245789[/C][/ROW]
[ROW][C]36[/C][C]-0.02447[/C][C]-0.1988[/C][C]0.421518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60978&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60978&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
10.0846620.68780.246994
20.1223690.99410.161895
30.0501580.40750.342485
40.1062480.86320.195587
50.0677490.55040.291953
60.0437030.3550.361845
70.0340740.27680.391392
80.0917290.74520.229396
90.1076930.87490.1924
10-0.093983-0.76350.223936
110.1862471.51310.067517
12-0.14916-1.21180.114958
13-0.018606-0.15120.440156
140.1367921.11130.135235
150.1317711.07050.144145
160.0205890.16730.433835
17-0.037181-0.30210.381778
180.0524620.42620.335672
190.0858970.69780.243867
200.0486310.39510.34703
21-0.119042-0.96710.168511
220.0212610.17270.431697
230.0519380.42190.337217
24-0.224665-1.82520.036249
25-0.128924-1.04740.149372
26-0.195361-1.58710.058633
27-0.082866-0.67320.251582
28-0.131487-1.06820.14466
290.0143370.11650.453815
30-0.09469-0.76930.22224
31-0.075324-0.61190.271342
32-0.127245-1.03370.152515
330.0014750.0120.495238
340.0396840.32240.374087
35-0.085137-0.69170.245789
36-0.02447-0.19880.421518






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0846620.68780.246994
20.1160330.94270.174647
30.031830.25860.398378
40.0879710.71470.238664
50.0460510.37410.354756
60.013560.11020.456308
70.0117540.09550.462108
80.072510.58910.278912
90.0838540.68120.249055
10-0.13703-1.11320.134822
110.1816031.47530.072437
12-0.192218-1.56160.061584
13-0.043782-0.35570.361606
140.1981651.60990.056096
150.0927730.75370.226858
16-0.030438-0.24730.402729
17-0.070898-0.5760.283293
180.0616110.50050.309184
190.0522550.42450.336283
20-0.009952-0.08090.467902
21-0.061804-0.50210.308633
22-0.081716-0.66390.254544
230.0855710.69520.244691
24-0.287366-2.33460.011309
25-0.14591-1.18540.12006
26-0.119599-0.97160.167392
27-0.007935-0.06450.474398
28-0.070797-0.57520.283571
290.0358790.29150.385798
30-0.043444-0.35290.362627
31-0.050871-0.41330.340372
32-0.00087-0.00710.49719
330.069960.56840.285859
34-0.012533-0.10180.459606
350.0966570.78520.217561
36-0.038164-0.310.378751

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.084662 & 0.6878 & 0.246994 \tabularnewline
2 & 0.116033 & 0.9427 & 0.174647 \tabularnewline
3 & 0.03183 & 0.2586 & 0.398378 \tabularnewline
4 & 0.087971 & 0.7147 & 0.238664 \tabularnewline
5 & 0.046051 & 0.3741 & 0.354756 \tabularnewline
6 & 0.01356 & 0.1102 & 0.456308 \tabularnewline
7 & 0.011754 & 0.0955 & 0.462108 \tabularnewline
8 & 0.07251 & 0.5891 & 0.278912 \tabularnewline
9 & 0.083854 & 0.6812 & 0.249055 \tabularnewline
10 & -0.13703 & -1.1132 & 0.134822 \tabularnewline
11 & 0.181603 & 1.4753 & 0.072437 \tabularnewline
12 & -0.192218 & -1.5616 & 0.061584 \tabularnewline
13 & -0.043782 & -0.3557 & 0.361606 \tabularnewline
14 & 0.198165 & 1.6099 & 0.056096 \tabularnewline
15 & 0.092773 & 0.7537 & 0.226858 \tabularnewline
16 & -0.030438 & -0.2473 & 0.402729 \tabularnewline
17 & -0.070898 & -0.576 & 0.283293 \tabularnewline
18 & 0.061611 & 0.5005 & 0.309184 \tabularnewline
19 & 0.052255 & 0.4245 & 0.336283 \tabularnewline
20 & -0.009952 & -0.0809 & 0.467902 \tabularnewline
21 & -0.061804 & -0.5021 & 0.308633 \tabularnewline
22 & -0.081716 & -0.6639 & 0.254544 \tabularnewline
23 & 0.085571 & 0.6952 & 0.244691 \tabularnewline
24 & -0.287366 & -2.3346 & 0.011309 \tabularnewline
25 & -0.14591 & -1.1854 & 0.12006 \tabularnewline
26 & -0.119599 & -0.9716 & 0.167392 \tabularnewline
27 & -0.007935 & -0.0645 & 0.474398 \tabularnewline
28 & -0.070797 & -0.5752 & 0.283571 \tabularnewline
29 & 0.035879 & 0.2915 & 0.385798 \tabularnewline
30 & -0.043444 & -0.3529 & 0.362627 \tabularnewline
31 & -0.050871 & -0.4133 & 0.340372 \tabularnewline
32 & -0.00087 & -0.0071 & 0.49719 \tabularnewline
33 & 0.06996 & 0.5684 & 0.285859 \tabularnewline
34 & -0.012533 & -0.1018 & 0.459606 \tabularnewline
35 & 0.096657 & 0.7852 & 0.217561 \tabularnewline
36 & -0.038164 & -0.31 & 0.378751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60978&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]0.084662[/C][C]0.6878[/C][C]0.246994[/C][/ROW]
[ROW][C]2[/C][C]0.116033[/C][C]0.9427[/C][C]0.174647[/C][/ROW]
[ROW][C]3[/C][C]0.03183[/C][C]0.2586[/C][C]0.398378[/C][/ROW]
[ROW][C]4[/C][C]0.087971[/C][C]0.7147[/C][C]0.238664[/C][/ROW]
[ROW][C]5[/C][C]0.046051[/C][C]0.3741[/C][C]0.354756[/C][/ROW]
[ROW][C]6[/C][C]0.01356[/C][C]0.1102[/C][C]0.456308[/C][/ROW]
[ROW][C]7[/C][C]0.011754[/C][C]0.0955[/C][C]0.462108[/C][/ROW]
[ROW][C]8[/C][C]0.07251[/C][C]0.5891[/C][C]0.278912[/C][/ROW]
[ROW][C]9[/C][C]0.083854[/C][C]0.6812[/C][C]0.249055[/C][/ROW]
[ROW][C]10[/C][C]-0.13703[/C][C]-1.1132[/C][C]0.134822[/C][/ROW]
[ROW][C]11[/C][C]0.181603[/C][C]1.4753[/C][C]0.072437[/C][/ROW]
[ROW][C]12[/C][C]-0.192218[/C][C]-1.5616[/C][C]0.061584[/C][/ROW]
[ROW][C]13[/C][C]-0.043782[/C][C]-0.3557[/C][C]0.361606[/C][/ROW]
[ROW][C]14[/C][C]0.198165[/C][C]1.6099[/C][C]0.056096[/C][/ROW]
[ROW][C]15[/C][C]0.092773[/C][C]0.7537[/C][C]0.226858[/C][/ROW]
[ROW][C]16[/C][C]-0.030438[/C][C]-0.2473[/C][C]0.402729[/C][/ROW]
[ROW][C]17[/C][C]-0.070898[/C][C]-0.576[/C][C]0.283293[/C][/ROW]
[ROW][C]18[/C][C]0.061611[/C][C]0.5005[/C][C]0.309184[/C][/ROW]
[ROW][C]19[/C][C]0.052255[/C][C]0.4245[/C][C]0.336283[/C][/ROW]
[ROW][C]20[/C][C]-0.009952[/C][C]-0.0809[/C][C]0.467902[/C][/ROW]
[ROW][C]21[/C][C]-0.061804[/C][C]-0.5021[/C][C]0.308633[/C][/ROW]
[ROW][C]22[/C][C]-0.081716[/C][C]-0.6639[/C][C]0.254544[/C][/ROW]
[ROW][C]23[/C][C]0.085571[/C][C]0.6952[/C][C]0.244691[/C][/ROW]
[ROW][C]24[/C][C]-0.287366[/C][C]-2.3346[/C][C]0.011309[/C][/ROW]
[ROW][C]25[/C][C]-0.14591[/C][C]-1.1854[/C][C]0.12006[/C][/ROW]
[ROW][C]26[/C][C]-0.119599[/C][C]-0.9716[/C][C]0.167392[/C][/ROW]
[ROW][C]27[/C][C]-0.007935[/C][C]-0.0645[/C][C]0.474398[/C][/ROW]
[ROW][C]28[/C][C]-0.070797[/C][C]-0.5752[/C][C]0.283571[/C][/ROW]
[ROW][C]29[/C][C]0.035879[/C][C]0.2915[/C][C]0.385798[/C][/ROW]
[ROW][C]30[/C][C]-0.043444[/C][C]-0.3529[/C][C]0.362627[/C][/ROW]
[ROW][C]31[/C][C]-0.050871[/C][C]-0.4133[/C][C]0.340372[/C][/ROW]
[ROW][C]32[/C][C]-0.00087[/C][C]-0.0071[/C][C]0.49719[/C][/ROW]
[ROW][C]33[/C][C]0.06996[/C][C]0.5684[/C][C]0.285859[/C][/ROW]
[ROW][C]34[/C][C]-0.012533[/C][C]-0.1018[/C][C]0.459606[/C][/ROW]
[ROW][C]35[/C][C]0.096657[/C][C]0.7852[/C][C]0.217561[/C][/ROW]
[ROW][C]36[/C][C]-0.038164[/C][C]-0.31[/C][C]0.378751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60978&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60978&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
10.0846620.68780.246994
20.1160330.94270.174647
30.031830.25860.398378
40.0879710.71470.238664
50.0460510.37410.354756
60.013560.11020.456308
70.0117540.09550.462108
80.072510.58910.278912
90.0838540.68120.249055
10-0.13703-1.11320.134822
110.1816031.47530.072437
12-0.192218-1.56160.061584
13-0.043782-0.35570.361606
140.1981651.60990.056096
150.0927730.75370.226858
16-0.030438-0.24730.402729
17-0.070898-0.5760.283293
180.0616110.50050.309184
190.0522550.42450.336283
20-0.009952-0.08090.467902
21-0.061804-0.50210.308633
22-0.081716-0.66390.254544
230.0855710.69520.244691
24-0.287366-2.33460.011309
25-0.14591-1.18540.12006
26-0.119599-0.97160.167392
27-0.007935-0.06450.474398
28-0.070797-0.57520.283571
290.0358790.29150.385798
30-0.043444-0.35290.362627
31-0.050871-0.41330.340372
32-0.00087-0.00710.49719
330.069960.56840.285859
34-0.012533-0.10180.459606
350.0966570.78520.217561
36-0.038164-0.310.378751


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')