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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, 04 Dec 2009 10:22:42 -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/Dec/04/t1259947399atc24xzyw9me8vx.htm/, Retrieved Sat, 27 Apr 2024 13:33:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63934, Retrieved Sat, 27 Apr 2024 13:33:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

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] [WS8] [2009-11-25 21:40:51] [cd6314e7e707a6546bd4604c9d1f2b69]
-                 [(Partial) Autocorrelation Function] [Paper - ACF (3)] [2009-12-04 17:22:42] [ea241b681aafed79da4b5b99fad98471] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186412
189226
191563
188906
186005
195309
223532
226899
214126

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=63934&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=63934&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63934&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
1-0.072326-0.54120.295245
20.3400882.5450.006855
3-0.010209-0.07640.469688
40.2739622.05010.022521
50.1298910.9720.167611
60.0184990.13840.445196
70.1312010.98180.165207
8-0.094739-0.7090.240644
90.2810352.10310.019983
100.0109970.08230.467354
110.3231792.41840.009432
12-0.198264-1.48370.071751
130.1559911.16730.124011
140.1270950.95110.172822
150.1169010.87480.192708
16-0.061705-0.46180.323021
17-0.035112-0.26280.396852
180.0493410.36920.356672
19-0.004862-0.03640.485554
200.0592710.44350.32954
21-0.100211-0.74990.228225
22-0.023832-0.17830.429547
23-0.131591-0.98470.164494
24-0.013957-0.10440.458595
25-0.057215-0.42820.33509
26-0.158498-1.18610.120297
27-0.207639-1.55380.06293
28-0.070272-0.52590.300529
29-0.136052-1.01810.156499
30-0.091694-0.68620.247718
31-0.060622-0.45370.325916
32-0.099444-0.74420.229943
330.031170.23330.408206
34-0.098093-0.73410.232988
35-0.017303-0.12950.448718
36-0.084716-0.6340.264346

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.072326 & -0.5412 & 0.295245 \tabularnewline
2 & 0.340088 & 2.545 & 0.006855 \tabularnewline
3 & -0.010209 & -0.0764 & 0.469688 \tabularnewline
4 & 0.273962 & 2.0501 & 0.022521 \tabularnewline
5 & 0.129891 & 0.972 & 0.167611 \tabularnewline
6 & 0.018499 & 0.1384 & 0.445196 \tabularnewline
7 & 0.131201 & 0.9818 & 0.165207 \tabularnewline
8 & -0.094739 & -0.709 & 0.240644 \tabularnewline
9 & 0.281035 & 2.1031 & 0.019983 \tabularnewline
10 & 0.010997 & 0.0823 & 0.467354 \tabularnewline
11 & 0.323179 & 2.4184 & 0.009432 \tabularnewline
12 & -0.198264 & -1.4837 & 0.071751 \tabularnewline
13 & 0.155991 & 1.1673 & 0.124011 \tabularnewline
14 & 0.127095 & 0.9511 & 0.172822 \tabularnewline
15 & 0.116901 & 0.8748 & 0.192708 \tabularnewline
16 & -0.061705 & -0.4618 & 0.323021 \tabularnewline
17 & -0.035112 & -0.2628 & 0.396852 \tabularnewline
18 & 0.049341 & 0.3692 & 0.356672 \tabularnewline
19 & -0.004862 & -0.0364 & 0.485554 \tabularnewline
20 & 0.059271 & 0.4435 & 0.32954 \tabularnewline
21 & -0.100211 & -0.7499 & 0.228225 \tabularnewline
22 & -0.023832 & -0.1783 & 0.429547 \tabularnewline
23 & -0.131591 & -0.9847 & 0.164494 \tabularnewline
24 & -0.013957 & -0.1044 & 0.458595 \tabularnewline
25 & -0.057215 & -0.4282 & 0.33509 \tabularnewline
26 & -0.158498 & -1.1861 & 0.120297 \tabularnewline
27 & -0.207639 & -1.5538 & 0.06293 \tabularnewline
28 & -0.070272 & -0.5259 & 0.300529 \tabularnewline
29 & -0.136052 & -1.0181 & 0.156499 \tabularnewline
30 & -0.091694 & -0.6862 & 0.247718 \tabularnewline
31 & -0.060622 & -0.4537 & 0.325916 \tabularnewline
32 & -0.099444 & -0.7442 & 0.229943 \tabularnewline
33 & 0.03117 & 0.2333 & 0.408206 \tabularnewline
34 & -0.098093 & -0.7341 & 0.232988 \tabularnewline
35 & -0.017303 & -0.1295 & 0.448718 \tabularnewline
36 & -0.084716 & -0.634 & 0.264346 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63934&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]-0.072326[/C][C]-0.5412[/C][C]0.295245[/C][/ROW]
[ROW][C]2[/C][C]0.340088[/C][C]2.545[/C][C]0.006855[/C][/ROW]
[ROW][C]3[/C][C]-0.010209[/C][C]-0.0764[/C][C]0.469688[/C][/ROW]
[ROW][C]4[/C][C]0.273962[/C][C]2.0501[/C][C]0.022521[/C][/ROW]
[ROW][C]5[/C][C]0.129891[/C][C]0.972[/C][C]0.167611[/C][/ROW]
[ROW][C]6[/C][C]0.018499[/C][C]0.1384[/C][C]0.445196[/C][/ROW]
[ROW][C]7[/C][C]0.131201[/C][C]0.9818[/C][C]0.165207[/C][/ROW]
[ROW][C]8[/C][C]-0.094739[/C][C]-0.709[/C][C]0.240644[/C][/ROW]
[ROW][C]9[/C][C]0.281035[/C][C]2.1031[/C][C]0.019983[/C][/ROW]
[ROW][C]10[/C][C]0.010997[/C][C]0.0823[/C][C]0.467354[/C][/ROW]
[ROW][C]11[/C][C]0.323179[/C][C]2.4184[/C][C]0.009432[/C][/ROW]
[ROW][C]12[/C][C]-0.198264[/C][C]-1.4837[/C][C]0.071751[/C][/ROW]
[ROW][C]13[/C][C]0.155991[/C][C]1.1673[/C][C]0.124011[/C][/ROW]
[ROW][C]14[/C][C]0.127095[/C][C]0.9511[/C][C]0.172822[/C][/ROW]
[ROW][C]15[/C][C]0.116901[/C][C]0.8748[/C][C]0.192708[/C][/ROW]
[ROW][C]16[/C][C]-0.061705[/C][C]-0.4618[/C][C]0.323021[/C][/ROW]
[ROW][C]17[/C][C]-0.035112[/C][C]-0.2628[/C][C]0.396852[/C][/ROW]
[ROW][C]18[/C][C]0.049341[/C][C]0.3692[/C][C]0.356672[/C][/ROW]
[ROW][C]19[/C][C]-0.004862[/C][C]-0.0364[/C][C]0.485554[/C][/ROW]
[ROW][C]20[/C][C]0.059271[/C][C]0.4435[/C][C]0.32954[/C][/ROW]
[ROW][C]21[/C][C]-0.100211[/C][C]-0.7499[/C][C]0.228225[/C][/ROW]
[ROW][C]22[/C][C]-0.023832[/C][C]-0.1783[/C][C]0.429547[/C][/ROW]
[ROW][C]23[/C][C]-0.131591[/C][C]-0.9847[/C][C]0.164494[/C][/ROW]
[ROW][C]24[/C][C]-0.013957[/C][C]-0.1044[/C][C]0.458595[/C][/ROW]
[ROW][C]25[/C][C]-0.057215[/C][C]-0.4282[/C][C]0.33509[/C][/ROW]
[ROW][C]26[/C][C]-0.158498[/C][C]-1.1861[/C][C]0.120297[/C][/ROW]
[ROW][C]27[/C][C]-0.207639[/C][C]-1.5538[/C][C]0.06293[/C][/ROW]
[ROW][C]28[/C][C]-0.070272[/C][C]-0.5259[/C][C]0.300529[/C][/ROW]
[ROW][C]29[/C][C]-0.136052[/C][C]-1.0181[/C][C]0.156499[/C][/ROW]
[ROW][C]30[/C][C]-0.091694[/C][C]-0.6862[/C][C]0.247718[/C][/ROW]
[ROW][C]31[/C][C]-0.060622[/C][C]-0.4537[/C][C]0.325916[/C][/ROW]
[ROW][C]32[/C][C]-0.099444[/C][C]-0.7442[/C][C]0.229943[/C][/ROW]
[ROW][C]33[/C][C]0.03117[/C][C]0.2333[/C][C]0.408206[/C][/ROW]
[ROW][C]34[/C][C]-0.098093[/C][C]-0.7341[/C][C]0.232988[/C][/ROW]
[ROW][C]35[/C][C]-0.017303[/C][C]-0.1295[/C][C]0.448718[/C][/ROW]
[ROW][C]36[/C][C]-0.084716[/C][C]-0.634[/C][C]0.264346[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63934&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63934&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
1-0.072326-0.54120.295245
20.3400882.5450.006855
3-0.010209-0.07640.469688
40.2739622.05010.022521
50.1298910.9720.167611
60.0184990.13840.445196
70.1312010.98180.165207
8-0.094739-0.7090.240644
90.2810352.10310.019983
100.0109970.08230.467354
110.3231792.41840.009432
12-0.198264-1.48370.071751
130.1559911.16730.124011
140.1270950.95110.172822
150.1169010.87480.192708
16-0.061705-0.46180.323021
17-0.035112-0.26280.396852
180.0493410.36920.356672
19-0.004862-0.03640.485554
200.0592710.44350.32954
21-0.100211-0.74990.228225
22-0.023832-0.17830.429547
23-0.131591-0.98470.164494
24-0.013957-0.10440.458595
25-0.057215-0.42820.33509
26-0.158498-1.18610.120297
27-0.207639-1.55380.06293
28-0.070272-0.52590.300529
29-0.136052-1.01810.156499
30-0.091694-0.68620.247718
31-0.060622-0.45370.325916
32-0.099444-0.74420.229943
330.031170.23330.408206
34-0.098093-0.73410.232988
35-0.017303-0.12950.448718
36-0.084716-0.6340.264346






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.072326-0.54120.295245
20.3366182.5190.007325
30.0345270.25840.398532
40.1825291.36590.088712
50.1744021.30510.098597
6-0.11601-0.86810.194512
70.0419030.31360.377505
8-0.132368-0.99050.163083
90.1800671.34750.091623
100.1325380.99180.162776
110.2350271.75880.042039
12-0.214577-1.60570.056978
13-0.113118-0.84650.200439
140.1802531.34890.091401
150.0396850.2970.383793
16-0.177439-1.32780.094811
17-0.000518-0.00390.498461
18-0.03758-0.28120.389787
19-0.002793-0.02090.491699
20-0.041947-0.31390.377381
21-0.046457-0.34760.364704
22-0.07578-0.56710.28646
23-0.072672-0.54380.294359
24-0.168804-1.26320.105873
25-0.051564-0.38590.350528
26-0.012944-0.09690.461589
27-0.128702-0.96310.169815
28-0.097458-0.72930.234426
29-0.111991-0.83810.20278
300.0175750.13150.447919
310.1846691.38190.086239
320.0218890.16380.43524
330.1092870.81780.20846
34-0.008202-0.06140.475638
35-0.05999-0.44890.32761
360.055440.41490.339908

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.072326 & -0.5412 & 0.295245 \tabularnewline
2 & 0.336618 & 2.519 & 0.007325 \tabularnewline
3 & 0.034527 & 0.2584 & 0.398532 \tabularnewline
4 & 0.182529 & 1.3659 & 0.088712 \tabularnewline
5 & 0.174402 & 1.3051 & 0.098597 \tabularnewline
6 & -0.11601 & -0.8681 & 0.194512 \tabularnewline
7 & 0.041903 & 0.3136 & 0.377505 \tabularnewline
8 & -0.132368 & -0.9905 & 0.163083 \tabularnewline
9 & 0.180067 & 1.3475 & 0.091623 \tabularnewline
10 & 0.132538 & 0.9918 & 0.162776 \tabularnewline
11 & 0.235027 & 1.7588 & 0.042039 \tabularnewline
12 & -0.214577 & -1.6057 & 0.056978 \tabularnewline
13 & -0.113118 & -0.8465 & 0.200439 \tabularnewline
14 & 0.180253 & 1.3489 & 0.091401 \tabularnewline
15 & 0.039685 & 0.297 & 0.383793 \tabularnewline
16 & -0.177439 & -1.3278 & 0.094811 \tabularnewline
17 & -0.000518 & -0.0039 & 0.498461 \tabularnewline
18 & -0.03758 & -0.2812 & 0.389787 \tabularnewline
19 & -0.002793 & -0.0209 & 0.491699 \tabularnewline
20 & -0.041947 & -0.3139 & 0.377381 \tabularnewline
21 & -0.046457 & -0.3476 & 0.364704 \tabularnewline
22 & -0.07578 & -0.5671 & 0.28646 \tabularnewline
23 & -0.072672 & -0.5438 & 0.294359 \tabularnewline
24 & -0.168804 & -1.2632 & 0.105873 \tabularnewline
25 & -0.051564 & -0.3859 & 0.350528 \tabularnewline
26 & -0.012944 & -0.0969 & 0.461589 \tabularnewline
27 & -0.128702 & -0.9631 & 0.169815 \tabularnewline
28 & -0.097458 & -0.7293 & 0.234426 \tabularnewline
29 & -0.111991 & -0.8381 & 0.20278 \tabularnewline
30 & 0.017575 & 0.1315 & 0.447919 \tabularnewline
31 & 0.184669 & 1.3819 & 0.086239 \tabularnewline
32 & 0.021889 & 0.1638 & 0.43524 \tabularnewline
33 & 0.109287 & 0.8178 & 0.20846 \tabularnewline
34 & -0.008202 & -0.0614 & 0.475638 \tabularnewline
35 & -0.05999 & -0.4489 & 0.32761 \tabularnewline
36 & 0.05544 & 0.4149 & 0.339908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63934&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]-0.072326[/C][C]-0.5412[/C][C]0.295245[/C][/ROW]
[ROW][C]2[/C][C]0.336618[/C][C]2.519[/C][C]0.007325[/C][/ROW]
[ROW][C]3[/C][C]0.034527[/C][C]0.2584[/C][C]0.398532[/C][/ROW]
[ROW][C]4[/C][C]0.182529[/C][C]1.3659[/C][C]0.088712[/C][/ROW]
[ROW][C]5[/C][C]0.174402[/C][C]1.3051[/C][C]0.098597[/C][/ROW]
[ROW][C]6[/C][C]-0.11601[/C][C]-0.8681[/C][C]0.194512[/C][/ROW]
[ROW][C]7[/C][C]0.041903[/C][C]0.3136[/C][C]0.377505[/C][/ROW]
[ROW][C]8[/C][C]-0.132368[/C][C]-0.9905[/C][C]0.163083[/C][/ROW]
[ROW][C]9[/C][C]0.180067[/C][C]1.3475[/C][C]0.091623[/C][/ROW]
[ROW][C]10[/C][C]0.132538[/C][C]0.9918[/C][C]0.162776[/C][/ROW]
[ROW][C]11[/C][C]0.235027[/C][C]1.7588[/C][C]0.042039[/C][/ROW]
[ROW][C]12[/C][C]-0.214577[/C][C]-1.6057[/C][C]0.056978[/C][/ROW]
[ROW][C]13[/C][C]-0.113118[/C][C]-0.8465[/C][C]0.200439[/C][/ROW]
[ROW][C]14[/C][C]0.180253[/C][C]1.3489[/C][C]0.091401[/C][/ROW]
[ROW][C]15[/C][C]0.039685[/C][C]0.297[/C][C]0.383793[/C][/ROW]
[ROW][C]16[/C][C]-0.177439[/C][C]-1.3278[/C][C]0.094811[/C][/ROW]
[ROW][C]17[/C][C]-0.000518[/C][C]-0.0039[/C][C]0.498461[/C][/ROW]
[ROW][C]18[/C][C]-0.03758[/C][C]-0.2812[/C][C]0.389787[/C][/ROW]
[ROW][C]19[/C][C]-0.002793[/C][C]-0.0209[/C][C]0.491699[/C][/ROW]
[ROW][C]20[/C][C]-0.041947[/C][C]-0.3139[/C][C]0.377381[/C][/ROW]
[ROW][C]21[/C][C]-0.046457[/C][C]-0.3476[/C][C]0.364704[/C][/ROW]
[ROW][C]22[/C][C]-0.07578[/C][C]-0.5671[/C][C]0.28646[/C][/ROW]
[ROW][C]23[/C][C]-0.072672[/C][C]-0.5438[/C][C]0.294359[/C][/ROW]
[ROW][C]24[/C][C]-0.168804[/C][C]-1.2632[/C][C]0.105873[/C][/ROW]
[ROW][C]25[/C][C]-0.051564[/C][C]-0.3859[/C][C]0.350528[/C][/ROW]
[ROW][C]26[/C][C]-0.012944[/C][C]-0.0969[/C][C]0.461589[/C][/ROW]
[ROW][C]27[/C][C]-0.128702[/C][C]-0.9631[/C][C]0.169815[/C][/ROW]
[ROW][C]28[/C][C]-0.097458[/C][C]-0.7293[/C][C]0.234426[/C][/ROW]
[ROW][C]29[/C][C]-0.111991[/C][C]-0.8381[/C][C]0.20278[/C][/ROW]
[ROW][C]30[/C][C]0.017575[/C][C]0.1315[/C][C]0.447919[/C][/ROW]
[ROW][C]31[/C][C]0.184669[/C][C]1.3819[/C][C]0.086239[/C][/ROW]
[ROW][C]32[/C][C]0.021889[/C][C]0.1638[/C][C]0.43524[/C][/ROW]
[ROW][C]33[/C][C]0.109287[/C][C]0.8178[/C][C]0.20846[/C][/ROW]
[ROW][C]34[/C][C]-0.008202[/C][C]-0.0614[/C][C]0.475638[/C][/ROW]
[ROW][C]35[/C][C]-0.05999[/C][C]-0.4489[/C][C]0.32761[/C][/ROW]
[ROW][C]36[/C][C]0.05544[/C][C]0.4149[/C][C]0.339908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63934&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63934&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
1-0.072326-0.54120.295245
20.3366182.5190.007325
30.0345270.25840.398532
40.1825291.36590.088712
50.1744021.30510.098597
6-0.11601-0.86810.194512
70.0419030.31360.377505
8-0.132368-0.99050.163083
90.1800671.34750.091623
100.1325380.99180.162776
110.2350271.75880.042039
12-0.214577-1.60570.056978
13-0.113118-0.84650.200439
140.1802531.34890.091401
150.0396850.2970.383793
16-0.177439-1.32780.094811
17-0.000518-0.00390.498461
18-0.03758-0.28120.389787
19-0.002793-0.02090.491699
20-0.041947-0.31390.377381
21-0.046457-0.34760.364704
22-0.07578-0.56710.28646
23-0.072672-0.54380.294359
24-0.168804-1.26320.105873
25-0.051564-0.38590.350528
26-0.012944-0.09690.461589
27-0.128702-0.96310.169815
28-0.097458-0.72930.234426
29-0.111991-0.83810.20278
300.0175750.13150.447919
310.1846691.38190.086239
320.0218890.16380.43524
330.1092870.81780.20846
34-0.008202-0.06140.475638
35-0.05999-0.44890.32761
360.055440.41490.339908


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')