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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, 06 Dec 2010 19:51:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/06/t1291664964idr7thdx40qdh0m.htm/, Retrieved Mon, 29 Apr 2024 05:35:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105830, Retrieved Mon, 29 Apr 2024 05:35:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

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] [ws8] [2009-11-24 20:12:27] [8b1aef4e7013bd33fbc2a5833375c5f5]
-    D          [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-06 19:25:07] [814f53995537cd15c528d8efbf1cf544]
-   PD              [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-06 19:51:05] [da925928e5a77063c5ecc7b801d712e1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
194.9
195.5
196
196.2
196.2
196.2
196.2
197
197.7
198
198.2
198.5
198.6
199.5
200
201.3
202.2
202.9
203.5
203.5
204
204.1
204.3
204.5
204.8
205.1
205.7
206.5
206.9
207.1
207.8
208
208.5
208.6
209
209.1
209.7
209.8
209.9
210
210.8
211.4
211.7
212
212.2
212.4
212.9
213.4
213.7
214
214.3
214.8
215
215.9
216.4
216.9
217.2
217.5
217.9
218.1
218.6
218.9
219.3
220.4
220.9
221
221.8
222
222.2
222.5
222.9
223.1

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=105830&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=105830&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105830&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
10.1495291.260.105906
20.1096970.92430.179224
3-0.100394-0.84590.200216
4-0.170159-1.43380.078012
5-0.16984-1.43110.078395
6-0.020204-0.17020.432651
7-0.02973-0.25050.401459
8-0.092451-0.7790.219281
9-0.075726-0.63810.262738
100.043710.36830.356869
11-0.113398-0.95550.171281
12-0.018586-0.15660.437999
130.1289961.08690.140371
140.0550690.4640.322026
150.0243350.2050.419061
16-0.032705-0.27560.391838
170.0466340.39290.347768
18-0.158094-1.33210.093539
190.0615710.51880.302754
20-0.057708-0.48630.314141
21-0.080332-0.67690.250336
22-0.161622-1.36190.088775
230.0866690.73030.233809
24-0.089381-0.75310.226929
250.0280540.23640.406905
260.0638820.53830.296035
270.0505140.42560.335828
28-0.042193-0.35550.361624
29-0.047717-0.40210.344419
30-0.066767-0.56260.287744
31-0.061086-0.51470.304174
32-0.017789-0.14990.440637
330.147321.24130.109283
340.0073120.06160.475522
35-0.064347-0.54220.294691
360.0718170.60510.273509

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.149529 & 1.26 & 0.105906 \tabularnewline
2 & 0.109697 & 0.9243 & 0.179224 \tabularnewline
3 & -0.100394 & -0.8459 & 0.200216 \tabularnewline
4 & -0.170159 & -1.4338 & 0.078012 \tabularnewline
5 & -0.16984 & -1.4311 & 0.078395 \tabularnewline
6 & -0.020204 & -0.1702 & 0.432651 \tabularnewline
7 & -0.02973 & -0.2505 & 0.401459 \tabularnewline
8 & -0.092451 & -0.779 & 0.219281 \tabularnewline
9 & -0.075726 & -0.6381 & 0.262738 \tabularnewline
10 & 0.04371 & 0.3683 & 0.356869 \tabularnewline
11 & -0.113398 & -0.9555 & 0.171281 \tabularnewline
12 & -0.018586 & -0.1566 & 0.437999 \tabularnewline
13 & 0.128996 & 1.0869 & 0.140371 \tabularnewline
14 & 0.055069 & 0.464 & 0.322026 \tabularnewline
15 & 0.024335 & 0.205 & 0.419061 \tabularnewline
16 & -0.032705 & -0.2756 & 0.391838 \tabularnewline
17 & 0.046634 & 0.3929 & 0.347768 \tabularnewline
18 & -0.158094 & -1.3321 & 0.093539 \tabularnewline
19 & 0.061571 & 0.5188 & 0.302754 \tabularnewline
20 & -0.057708 & -0.4863 & 0.314141 \tabularnewline
21 & -0.080332 & -0.6769 & 0.250336 \tabularnewline
22 & -0.161622 & -1.3619 & 0.088775 \tabularnewline
23 & 0.086669 & 0.7303 & 0.233809 \tabularnewline
24 & -0.089381 & -0.7531 & 0.226929 \tabularnewline
25 & 0.028054 & 0.2364 & 0.406905 \tabularnewline
26 & 0.063882 & 0.5383 & 0.296035 \tabularnewline
27 & 0.050514 & 0.4256 & 0.335828 \tabularnewline
28 & -0.042193 & -0.3555 & 0.361624 \tabularnewline
29 & -0.047717 & -0.4021 & 0.344419 \tabularnewline
30 & -0.066767 & -0.5626 & 0.287744 \tabularnewline
31 & -0.061086 & -0.5147 & 0.304174 \tabularnewline
32 & -0.017789 & -0.1499 & 0.440637 \tabularnewline
33 & 0.14732 & 1.2413 & 0.109283 \tabularnewline
34 & 0.007312 & 0.0616 & 0.475522 \tabularnewline
35 & -0.064347 & -0.5422 & 0.294691 \tabularnewline
36 & 0.071817 & 0.6051 & 0.273509 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105830&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]0.149529[/C][C]1.26[/C][C]0.105906[/C][/ROW]
[ROW][C]2[/C][C]0.109697[/C][C]0.9243[/C][C]0.179224[/C][/ROW]
[ROW][C]3[/C][C]-0.100394[/C][C]-0.8459[/C][C]0.200216[/C][/ROW]
[ROW][C]4[/C][C]-0.170159[/C][C]-1.4338[/C][C]0.078012[/C][/ROW]
[ROW][C]5[/C][C]-0.16984[/C][C]-1.4311[/C][C]0.078395[/C][/ROW]
[ROW][C]6[/C][C]-0.020204[/C][C]-0.1702[/C][C]0.432651[/C][/ROW]
[ROW][C]7[/C][C]-0.02973[/C][C]-0.2505[/C][C]0.401459[/C][/ROW]
[ROW][C]8[/C][C]-0.092451[/C][C]-0.779[/C][C]0.219281[/C][/ROW]
[ROW][C]9[/C][C]-0.075726[/C][C]-0.6381[/C][C]0.262738[/C][/ROW]
[ROW][C]10[/C][C]0.04371[/C][C]0.3683[/C][C]0.356869[/C][/ROW]
[ROW][C]11[/C][C]-0.113398[/C][C]-0.9555[/C][C]0.171281[/C][/ROW]
[ROW][C]12[/C][C]-0.018586[/C][C]-0.1566[/C][C]0.437999[/C][/ROW]
[ROW][C]13[/C][C]0.128996[/C][C]1.0869[/C][C]0.140371[/C][/ROW]
[ROW][C]14[/C][C]0.055069[/C][C]0.464[/C][C]0.322026[/C][/ROW]
[ROW][C]15[/C][C]0.024335[/C][C]0.205[/C][C]0.419061[/C][/ROW]
[ROW][C]16[/C][C]-0.032705[/C][C]-0.2756[/C][C]0.391838[/C][/ROW]
[ROW][C]17[/C][C]0.046634[/C][C]0.3929[/C][C]0.347768[/C][/ROW]
[ROW][C]18[/C][C]-0.158094[/C][C]-1.3321[/C][C]0.093539[/C][/ROW]
[ROW][C]19[/C][C]0.061571[/C][C]0.5188[/C][C]0.302754[/C][/ROW]
[ROW][C]20[/C][C]-0.057708[/C][C]-0.4863[/C][C]0.314141[/C][/ROW]
[ROW][C]21[/C][C]-0.080332[/C][C]-0.6769[/C][C]0.250336[/C][/ROW]
[ROW][C]22[/C][C]-0.161622[/C][C]-1.3619[/C][C]0.088775[/C][/ROW]
[ROW][C]23[/C][C]0.086669[/C][C]0.7303[/C][C]0.233809[/C][/ROW]
[ROW][C]24[/C][C]-0.089381[/C][C]-0.7531[/C][C]0.226929[/C][/ROW]
[ROW][C]25[/C][C]0.028054[/C][C]0.2364[/C][C]0.406905[/C][/ROW]
[ROW][C]26[/C][C]0.063882[/C][C]0.5383[/C][C]0.296035[/C][/ROW]
[ROW][C]27[/C][C]0.050514[/C][C]0.4256[/C][C]0.335828[/C][/ROW]
[ROW][C]28[/C][C]-0.042193[/C][C]-0.3555[/C][C]0.361624[/C][/ROW]
[ROW][C]29[/C][C]-0.047717[/C][C]-0.4021[/C][C]0.344419[/C][/ROW]
[ROW][C]30[/C][C]-0.066767[/C][C]-0.5626[/C][C]0.287744[/C][/ROW]
[ROW][C]31[/C][C]-0.061086[/C][C]-0.5147[/C][C]0.304174[/C][/ROW]
[ROW][C]32[/C][C]-0.017789[/C][C]-0.1499[/C][C]0.440637[/C][/ROW]
[ROW][C]33[/C][C]0.14732[/C][C]1.2413[/C][C]0.109283[/C][/ROW]
[ROW][C]34[/C][C]0.007312[/C][C]0.0616[/C][C]0.475522[/C][/ROW]
[ROW][C]35[/C][C]-0.064347[/C][C]-0.5422[/C][C]0.294691[/C][/ROW]
[ROW][C]36[/C][C]0.071817[/C][C]0.6051[/C][C]0.273509[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105830&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105830&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
10.1495291.260.105906
20.1096970.92430.179224
3-0.100394-0.84590.200216
4-0.170159-1.43380.078012
5-0.16984-1.43110.078395
6-0.020204-0.17020.432651
7-0.02973-0.25050.401459
8-0.092451-0.7790.219281
9-0.075726-0.63810.262738
100.043710.36830.356869
11-0.113398-0.95550.171281
12-0.018586-0.15660.437999
130.1289961.08690.140371
140.0550690.4640.322026
150.0243350.2050.419061
16-0.032705-0.27560.391838
170.0466340.39290.347768
18-0.158094-1.33210.093539
190.0615710.51880.302754
20-0.057708-0.48630.314141
21-0.080332-0.67690.250336
22-0.161622-1.36190.088775
230.0866690.73030.233809
24-0.089381-0.75310.226929
250.0280540.23640.406905
260.0638820.53830.296035
270.0505140.42560.335828
28-0.042193-0.35550.361624
29-0.047717-0.40210.344419
30-0.066767-0.56260.287744
31-0.061086-0.51470.304174
32-0.017789-0.14990.440637
330.147321.24130.109283
340.0073120.06160.475522
35-0.064347-0.54220.294691
360.0718170.60510.273509






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1495291.260.105906
20.0893360.75280.227043
3-0.132692-1.11810.13365
4-0.154538-1.30220.098534
5-0.108104-0.91090.182714
60.0431080.36320.358756
7-0.034552-0.29110.385896
8-0.152155-1.28210.101992
9-0.092912-0.78290.218148
100.0784940.66140.255246
11-0.147325-1.24140.109275
12-0.080087-0.67480.25099
130.1359131.14520.127981
140.0139770.11780.453291
15-0.068143-0.57420.28383
16-0.098925-0.83360.203664
170.1144270.96420.169114
18-0.129741-1.09320.138997
190.0335630.28280.389075
20-0.090594-0.76340.223889
21-0.062878-0.52980.298944
22-0.164197-1.38350.085416
230.0936610.78920.216311
24-0.103644-0.87330.192716
25-0.045355-0.38220.35174
26-0.002027-0.01710.49321
27-0.02755-0.23210.408547
28-0.060179-0.50710.306836
29-0.167316-1.40980.081478
30-0.073965-0.62320.267562
31-0.020603-0.17360.431335
32-0.085153-0.71750.237707
330.0231720.19520.422877
34-0.060175-0.5070.306848
35-0.115711-0.9750.166436
36-0.006862-0.05780.477026

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.149529 & 1.26 & 0.105906 \tabularnewline
2 & 0.089336 & 0.7528 & 0.227043 \tabularnewline
3 & -0.132692 & -1.1181 & 0.13365 \tabularnewline
4 & -0.154538 & -1.3022 & 0.098534 \tabularnewline
5 & -0.108104 & -0.9109 & 0.182714 \tabularnewline
6 & 0.043108 & 0.3632 & 0.358756 \tabularnewline
7 & -0.034552 & -0.2911 & 0.385896 \tabularnewline
8 & -0.152155 & -1.2821 & 0.101992 \tabularnewline
9 & -0.092912 & -0.7829 & 0.218148 \tabularnewline
10 & 0.078494 & 0.6614 & 0.255246 \tabularnewline
11 & -0.147325 & -1.2414 & 0.109275 \tabularnewline
12 & -0.080087 & -0.6748 & 0.25099 \tabularnewline
13 & 0.135913 & 1.1452 & 0.127981 \tabularnewline
14 & 0.013977 & 0.1178 & 0.453291 \tabularnewline
15 & -0.068143 & -0.5742 & 0.28383 \tabularnewline
16 & -0.098925 & -0.8336 & 0.203664 \tabularnewline
17 & 0.114427 & 0.9642 & 0.169114 \tabularnewline
18 & -0.129741 & -1.0932 & 0.138997 \tabularnewline
19 & 0.033563 & 0.2828 & 0.389075 \tabularnewline
20 & -0.090594 & -0.7634 & 0.223889 \tabularnewline
21 & -0.062878 & -0.5298 & 0.298944 \tabularnewline
22 & -0.164197 & -1.3835 & 0.085416 \tabularnewline
23 & 0.093661 & 0.7892 & 0.216311 \tabularnewline
24 & -0.103644 & -0.8733 & 0.192716 \tabularnewline
25 & -0.045355 & -0.3822 & 0.35174 \tabularnewline
26 & -0.002027 & -0.0171 & 0.49321 \tabularnewline
27 & -0.02755 & -0.2321 & 0.408547 \tabularnewline
28 & -0.060179 & -0.5071 & 0.306836 \tabularnewline
29 & -0.167316 & -1.4098 & 0.081478 \tabularnewline
30 & -0.073965 & -0.6232 & 0.267562 \tabularnewline
31 & -0.020603 & -0.1736 & 0.431335 \tabularnewline
32 & -0.085153 & -0.7175 & 0.237707 \tabularnewline
33 & 0.023172 & 0.1952 & 0.422877 \tabularnewline
34 & -0.060175 & -0.507 & 0.306848 \tabularnewline
35 & -0.115711 & -0.975 & 0.166436 \tabularnewline
36 & -0.006862 & -0.0578 & 0.477026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105830&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]0.149529[/C][C]1.26[/C][C]0.105906[/C][/ROW]
[ROW][C]2[/C][C]0.089336[/C][C]0.7528[/C][C]0.227043[/C][/ROW]
[ROW][C]3[/C][C]-0.132692[/C][C]-1.1181[/C][C]0.13365[/C][/ROW]
[ROW][C]4[/C][C]-0.154538[/C][C]-1.3022[/C][C]0.098534[/C][/ROW]
[ROW][C]5[/C][C]-0.108104[/C][C]-0.9109[/C][C]0.182714[/C][/ROW]
[ROW][C]6[/C][C]0.043108[/C][C]0.3632[/C][C]0.358756[/C][/ROW]
[ROW][C]7[/C][C]-0.034552[/C][C]-0.2911[/C][C]0.385896[/C][/ROW]
[ROW][C]8[/C][C]-0.152155[/C][C]-1.2821[/C][C]0.101992[/C][/ROW]
[ROW][C]9[/C][C]-0.092912[/C][C]-0.7829[/C][C]0.218148[/C][/ROW]
[ROW][C]10[/C][C]0.078494[/C][C]0.6614[/C][C]0.255246[/C][/ROW]
[ROW][C]11[/C][C]-0.147325[/C][C]-1.2414[/C][C]0.109275[/C][/ROW]
[ROW][C]12[/C][C]-0.080087[/C][C]-0.6748[/C][C]0.25099[/C][/ROW]
[ROW][C]13[/C][C]0.135913[/C][C]1.1452[/C][C]0.127981[/C][/ROW]
[ROW][C]14[/C][C]0.013977[/C][C]0.1178[/C][C]0.453291[/C][/ROW]
[ROW][C]15[/C][C]-0.068143[/C][C]-0.5742[/C][C]0.28383[/C][/ROW]
[ROW][C]16[/C][C]-0.098925[/C][C]-0.8336[/C][C]0.203664[/C][/ROW]
[ROW][C]17[/C][C]0.114427[/C][C]0.9642[/C][C]0.169114[/C][/ROW]
[ROW][C]18[/C][C]-0.129741[/C][C]-1.0932[/C][C]0.138997[/C][/ROW]
[ROW][C]19[/C][C]0.033563[/C][C]0.2828[/C][C]0.389075[/C][/ROW]
[ROW][C]20[/C][C]-0.090594[/C][C]-0.7634[/C][C]0.223889[/C][/ROW]
[ROW][C]21[/C][C]-0.062878[/C][C]-0.5298[/C][C]0.298944[/C][/ROW]
[ROW][C]22[/C][C]-0.164197[/C][C]-1.3835[/C][C]0.085416[/C][/ROW]
[ROW][C]23[/C][C]0.093661[/C][C]0.7892[/C][C]0.216311[/C][/ROW]
[ROW][C]24[/C][C]-0.103644[/C][C]-0.8733[/C][C]0.192716[/C][/ROW]
[ROW][C]25[/C][C]-0.045355[/C][C]-0.3822[/C][C]0.35174[/C][/ROW]
[ROW][C]26[/C][C]-0.002027[/C][C]-0.0171[/C][C]0.49321[/C][/ROW]
[ROW][C]27[/C][C]-0.02755[/C][C]-0.2321[/C][C]0.408547[/C][/ROW]
[ROW][C]28[/C][C]-0.060179[/C][C]-0.5071[/C][C]0.306836[/C][/ROW]
[ROW][C]29[/C][C]-0.167316[/C][C]-1.4098[/C][C]0.081478[/C][/ROW]
[ROW][C]30[/C][C]-0.073965[/C][C]-0.6232[/C][C]0.267562[/C][/ROW]
[ROW][C]31[/C][C]-0.020603[/C][C]-0.1736[/C][C]0.431335[/C][/ROW]
[ROW][C]32[/C][C]-0.085153[/C][C]-0.7175[/C][C]0.237707[/C][/ROW]
[ROW][C]33[/C][C]0.023172[/C][C]0.1952[/C][C]0.422877[/C][/ROW]
[ROW][C]34[/C][C]-0.060175[/C][C]-0.507[/C][C]0.306848[/C][/ROW]
[ROW][C]35[/C][C]-0.115711[/C][C]-0.975[/C][C]0.166436[/C][/ROW]
[ROW][C]36[/C][C]-0.006862[/C][C]-0.0578[/C][C]0.477026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105830&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105830&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
10.1495291.260.105906
20.0893360.75280.227043
3-0.132692-1.11810.13365
4-0.154538-1.30220.098534
5-0.108104-0.91090.182714
60.0431080.36320.358756
7-0.034552-0.29110.385896
8-0.152155-1.28210.101992
9-0.092912-0.78290.218148
100.0784940.66140.255246
11-0.147325-1.24140.109275
12-0.080087-0.67480.25099
130.1359131.14520.127981
140.0139770.11780.453291
15-0.068143-0.57420.28383
16-0.098925-0.83360.203664
170.1144270.96420.169114
18-0.129741-1.09320.138997
190.0335630.28280.389075
20-0.090594-0.76340.223889
21-0.062878-0.52980.298944
22-0.164197-1.38350.085416
230.0936610.78920.216311
24-0.103644-0.87330.192716
25-0.045355-0.38220.35174
26-0.002027-0.01710.49321
27-0.02755-0.23210.408547
28-0.060179-0.50710.306836
29-0.167316-1.40980.081478
30-0.073965-0.62320.267562
31-0.020603-0.17360.431335
32-0.085153-0.71750.237707
330.0231720.19520.422877
34-0.060175-0.5070.306848
35-0.115711-0.9750.166436
36-0.006862-0.05780.477026


Figures (Output of Computation)

Input Parameters & R Code

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