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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 09 Dec 2008 10:48:15 -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/2008/Dec/09/t1228844945sjih1ikjk5wsqfd.htm/, Retrieved Fri, 17 May 2024 06:59:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31626, Retrieved Fri, 17 May 2024 06:59:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD  [Standard Deviation-Mean Plot] [SMP Investeringsg...] [2008-12-07 09:34:56] [74be16979710d4c4e7c6647856088456]
F RMP       [(Partial) Autocorrelation Function] [ACF investeringsg...] [2008-12-09 17:48:15] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RMP         [ARIMA Backward Selection] [ARIMA investering...] [2008-12-09 18:45:00] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-12-14 19:47:57 [Steven Vercammen] [reply] 
Dit heb ik correct toegepast

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.4
101.5
110.4
105.9
108.4
113.9
86.1
69.4
101.2
100.5
98.0
106.6
90.1
96.9
125.9
112.0
100.0
123.9
79.8
83.4
113.6
112.9
104.0
109.9
99.0
106.3
128.9
111.1
102.9
130.0
87.0
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137.0
91.0
90.5
122.4
123.3
124.3
120.0
118.1
119.0
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128.0
121.6
135.8
143.8
147.5
136.2
156.6
123.3
104.5
143.6

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31626&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31626&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.106834-0.80660.21163
20.0945790.71410.239054
30.1551021.1710.123236
40.0042580.03210.487233
50.2236331.68840.0484
60.2081231.57130.060825
7-0.085613-0.64640.260319
80.048780.36830.357015
90.0388410.29320.385201
100.1508411.13880.12977
110.0805460.60810.272765
12-0.110446-0.83380.203924
13-0.02029-0.15320.439397
14-0.040849-0.30840.379449
150.1125440.84970.199527
160.0377090.28470.388454
170.09930.74970.228259
18-0.097022-0.73250.233434
19-0.049532-0.3740.354911
200.0144860.10940.456648
210.1420931.07280.143945
22-0.229588-1.73330.04422
230.2017021.52280.066666
24-0.19016-1.43570.07828
25-0.041479-0.31320.377652
260.1571031.18610.120251
27-0.100801-0.7610.224888
28-0.125948-0.95090.172838
29-0.035896-0.2710.393681
30-0.149963-1.13220.131146
310.0401530.30310.38144
32-0.048298-0.36460.358364
33-0.1375-1.03810.151803
340.0556710.42030.33792
35-0.160055-1.20840.115943
36-0.071698-0.54130.295202

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.106834 & -0.8066 & 0.21163 \tabularnewline
2 & 0.094579 & 0.7141 & 0.239054 \tabularnewline
3 & 0.155102 & 1.171 & 0.123236 \tabularnewline
4 & 0.004258 & 0.0321 & 0.487233 \tabularnewline
5 & 0.223633 & 1.6884 & 0.0484 \tabularnewline
6 & 0.208123 & 1.5713 & 0.060825 \tabularnewline
7 & -0.085613 & -0.6464 & 0.260319 \tabularnewline
8 & 0.04878 & 0.3683 & 0.357015 \tabularnewline
9 & 0.038841 & 0.2932 & 0.385201 \tabularnewline
10 & 0.150841 & 1.1388 & 0.12977 \tabularnewline
11 & 0.080546 & 0.6081 & 0.272765 \tabularnewline
12 & -0.110446 & -0.8338 & 0.203924 \tabularnewline
13 & -0.02029 & -0.1532 & 0.439397 \tabularnewline
14 & -0.040849 & -0.3084 & 0.379449 \tabularnewline
15 & 0.112544 & 0.8497 & 0.199527 \tabularnewline
16 & 0.037709 & 0.2847 & 0.388454 \tabularnewline
17 & 0.0993 & 0.7497 & 0.228259 \tabularnewline
18 & -0.097022 & -0.7325 & 0.233434 \tabularnewline
19 & -0.049532 & -0.374 & 0.354911 \tabularnewline
20 & 0.014486 & 0.1094 & 0.456648 \tabularnewline
21 & 0.142093 & 1.0728 & 0.143945 \tabularnewline
22 & -0.229588 & -1.7333 & 0.04422 \tabularnewline
23 & 0.201702 & 1.5228 & 0.066666 \tabularnewline
24 & -0.19016 & -1.4357 & 0.07828 \tabularnewline
25 & -0.041479 & -0.3132 & 0.377652 \tabularnewline
26 & 0.157103 & 1.1861 & 0.120251 \tabularnewline
27 & -0.100801 & -0.761 & 0.224888 \tabularnewline
28 & -0.125948 & -0.9509 & 0.172838 \tabularnewline
29 & -0.035896 & -0.271 & 0.393681 \tabularnewline
30 & -0.149963 & -1.1322 & 0.131146 \tabularnewline
31 & 0.040153 & 0.3031 & 0.38144 \tabularnewline
32 & -0.048298 & -0.3646 & 0.358364 \tabularnewline
33 & -0.1375 & -1.0381 & 0.151803 \tabularnewline
34 & 0.055671 & 0.4203 & 0.33792 \tabularnewline
35 & -0.160055 & -1.2084 & 0.115943 \tabularnewline
36 & -0.071698 & -0.5413 & 0.295202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31626&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]-0.106834[/C][C]-0.8066[/C][C]0.21163[/C][/ROW]
[ROW][C]2[/C][C]0.094579[/C][C]0.7141[/C][C]0.239054[/C][/ROW]
[ROW][C]3[/C][C]0.155102[/C][C]1.171[/C][C]0.123236[/C][/ROW]
[ROW][C]4[/C][C]0.004258[/C][C]0.0321[/C][C]0.487233[/C][/ROW]
[ROW][C]5[/C][C]0.223633[/C][C]1.6884[/C][C]0.0484[/C][/ROW]
[ROW][C]6[/C][C]0.208123[/C][C]1.5713[/C][C]0.060825[/C][/ROW]
[ROW][C]7[/C][C]-0.085613[/C][C]-0.6464[/C][C]0.260319[/C][/ROW]
[ROW][C]8[/C][C]0.04878[/C][C]0.3683[/C][C]0.357015[/C][/ROW]
[ROW][C]9[/C][C]0.038841[/C][C]0.2932[/C][C]0.385201[/C][/ROW]
[ROW][C]10[/C][C]0.150841[/C][C]1.1388[/C][C]0.12977[/C][/ROW]
[ROW][C]11[/C][C]0.080546[/C][C]0.6081[/C][C]0.272765[/C][/ROW]
[ROW][C]12[/C][C]-0.110446[/C][C]-0.8338[/C][C]0.203924[/C][/ROW]
[ROW][C]13[/C][C]-0.02029[/C][C]-0.1532[/C][C]0.439397[/C][/ROW]
[ROW][C]14[/C][C]-0.040849[/C][C]-0.3084[/C][C]0.379449[/C][/ROW]
[ROW][C]15[/C][C]0.112544[/C][C]0.8497[/C][C]0.199527[/C][/ROW]
[ROW][C]16[/C][C]0.037709[/C][C]0.2847[/C][C]0.388454[/C][/ROW]
[ROW][C]17[/C][C]0.0993[/C][C]0.7497[/C][C]0.228259[/C][/ROW]
[ROW][C]18[/C][C]-0.097022[/C][C]-0.7325[/C][C]0.233434[/C][/ROW]
[ROW][C]19[/C][C]-0.049532[/C][C]-0.374[/C][C]0.354911[/C][/ROW]
[ROW][C]20[/C][C]0.014486[/C][C]0.1094[/C][C]0.456648[/C][/ROW]
[ROW][C]21[/C][C]0.142093[/C][C]1.0728[/C][C]0.143945[/C][/ROW]
[ROW][C]22[/C][C]-0.229588[/C][C]-1.7333[/C][C]0.04422[/C][/ROW]
[ROW][C]23[/C][C]0.201702[/C][C]1.5228[/C][C]0.066666[/C][/ROW]
[ROW][C]24[/C][C]-0.19016[/C][C]-1.4357[/C][C]0.07828[/C][/ROW]
[ROW][C]25[/C][C]-0.041479[/C][C]-0.3132[/C][C]0.377652[/C][/ROW]
[ROW][C]26[/C][C]0.157103[/C][C]1.1861[/C][C]0.120251[/C][/ROW]
[ROW][C]27[/C][C]-0.100801[/C][C]-0.761[/C][C]0.224888[/C][/ROW]
[ROW][C]28[/C][C]-0.125948[/C][C]-0.9509[/C][C]0.172838[/C][/ROW]
[ROW][C]29[/C][C]-0.035896[/C][C]-0.271[/C][C]0.393681[/C][/ROW]
[ROW][C]30[/C][C]-0.149963[/C][C]-1.1322[/C][C]0.131146[/C][/ROW]
[ROW][C]31[/C][C]0.040153[/C][C]0.3031[/C][C]0.38144[/C][/ROW]
[ROW][C]32[/C][C]-0.048298[/C][C]-0.3646[/C][C]0.358364[/C][/ROW]
[ROW][C]33[/C][C]-0.1375[/C][C]-1.0381[/C][C]0.151803[/C][/ROW]
[ROW][C]34[/C][C]0.055671[/C][C]0.4203[/C][C]0.33792[/C][/ROW]
[ROW][C]35[/C][C]-0.160055[/C][C]-1.2084[/C][C]0.115943[/C][/ROW]
[ROW][C]36[/C][C]-0.071698[/C][C]-0.5413[/C][C]0.295202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31626&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
1-0.106834-0.80660.21163
20.0945790.71410.239054
30.1551021.1710.123236
40.0042580.03210.487233
50.2236331.68840.0484
60.2081231.57130.060825
7-0.085613-0.64640.260319
80.048780.36830.357015
90.0388410.29320.385201
100.1508411.13880.12977
110.0805460.60810.272765
12-0.110446-0.83380.203924
13-0.02029-0.15320.439397
14-0.040849-0.30840.379449
150.1125440.84970.199527
160.0377090.28470.388454
170.09930.74970.228259
18-0.097022-0.73250.233434
19-0.049532-0.3740.354911
200.0144860.10940.456648
210.1420931.07280.143945
22-0.229588-1.73330.04422
230.2017021.52280.066666
24-0.19016-1.43570.07828
25-0.041479-0.31320.377652
260.1571031.18610.120251
27-0.100801-0.7610.224888
28-0.125948-0.95090.172838
29-0.035896-0.2710.393681
30-0.149963-1.13220.131146
310.0401530.30310.38144
32-0.048298-0.36460.358364
33-0.1375-1.03810.151803
340.0556710.42030.33792
35-0.160055-1.20840.115943
36-0.071698-0.54130.295202






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.106834-0.80660.21163
20.0841250.63510.263942
30.1765951.33330.093875
40.0326130.24620.403197
50.2056461.55260.063028
60.2501721.88880.032008
7-0.072673-0.54870.292687
8-0.086442-0.65260.258312
9-0.033118-0.250.401728
100.1352561.02120.155746
110.0350580.26470.396105
12-0.161175-1.21680.114339
13-0.079458-0.59990.275478
14-0.066176-0.49960.309635
150.0840830.63480.264045
160.0175520.13250.447521
170.2032941.53480.065178
180.0128370.09690.461566
19-0.117136-0.88440.19011
20-0.130146-0.98260.164983
210.1230480.9290.178406
22-0.213827-1.61440.055986
230.1801691.36020.089554
24-0.091049-0.68740.247308
25-0.064482-0.48680.314122
260.0114120.08620.465822
27-0.012091-0.09130.463792
28-0.09793-0.73940.231363
29-0.046545-0.35140.363289
30-0.047849-0.36130.359623
31-0.00892-0.06730.473272
32-0.074632-0.56350.287667
33-0.062362-0.47080.319781
340.1334911.00780.158897
350.0198470.14980.44071
36-0.176779-1.33470.093649

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.106834 & -0.8066 & 0.21163 \tabularnewline
2 & 0.084125 & 0.6351 & 0.263942 \tabularnewline
3 & 0.176595 & 1.3333 & 0.093875 \tabularnewline
4 & 0.032613 & 0.2462 & 0.403197 \tabularnewline
5 & 0.205646 & 1.5526 & 0.063028 \tabularnewline
6 & 0.250172 & 1.8888 & 0.032008 \tabularnewline
7 & -0.072673 & -0.5487 & 0.292687 \tabularnewline
8 & -0.086442 & -0.6526 & 0.258312 \tabularnewline
9 & -0.033118 & -0.25 & 0.401728 \tabularnewline
10 & 0.135256 & 1.0212 & 0.155746 \tabularnewline
11 & 0.035058 & 0.2647 & 0.396105 \tabularnewline
12 & -0.161175 & -1.2168 & 0.114339 \tabularnewline
13 & -0.079458 & -0.5999 & 0.275478 \tabularnewline
14 & -0.066176 & -0.4996 & 0.309635 \tabularnewline
15 & 0.084083 & 0.6348 & 0.264045 \tabularnewline
16 & 0.017552 & 0.1325 & 0.447521 \tabularnewline
17 & 0.203294 & 1.5348 & 0.065178 \tabularnewline
18 & 0.012837 & 0.0969 & 0.461566 \tabularnewline
19 & -0.117136 & -0.8844 & 0.19011 \tabularnewline
20 & -0.130146 & -0.9826 & 0.164983 \tabularnewline
21 & 0.123048 & 0.929 & 0.178406 \tabularnewline
22 & -0.213827 & -1.6144 & 0.055986 \tabularnewline
23 & 0.180169 & 1.3602 & 0.089554 \tabularnewline
24 & -0.091049 & -0.6874 & 0.247308 \tabularnewline
25 & -0.064482 & -0.4868 & 0.314122 \tabularnewline
26 & 0.011412 & 0.0862 & 0.465822 \tabularnewline
27 & -0.012091 & -0.0913 & 0.463792 \tabularnewline
28 & -0.09793 & -0.7394 & 0.231363 \tabularnewline
29 & -0.046545 & -0.3514 & 0.363289 \tabularnewline
30 & -0.047849 & -0.3613 & 0.359623 \tabularnewline
31 & -0.00892 & -0.0673 & 0.473272 \tabularnewline
32 & -0.074632 & -0.5635 & 0.287667 \tabularnewline
33 & -0.062362 & -0.4708 & 0.319781 \tabularnewline
34 & 0.133491 & 1.0078 & 0.158897 \tabularnewline
35 & 0.019847 & 0.1498 & 0.44071 \tabularnewline
36 & -0.176779 & -1.3347 & 0.093649 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31626&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]-0.106834[/C][C]-0.8066[/C][C]0.21163[/C][/ROW]
[ROW][C]2[/C][C]0.084125[/C][C]0.6351[/C][C]0.263942[/C][/ROW]
[ROW][C]3[/C][C]0.176595[/C][C]1.3333[/C][C]0.093875[/C][/ROW]
[ROW][C]4[/C][C]0.032613[/C][C]0.2462[/C][C]0.403197[/C][/ROW]
[ROW][C]5[/C][C]0.205646[/C][C]1.5526[/C][C]0.063028[/C][/ROW]
[ROW][C]6[/C][C]0.250172[/C][C]1.8888[/C][C]0.032008[/C][/ROW]
[ROW][C]7[/C][C]-0.072673[/C][C]-0.5487[/C][C]0.292687[/C][/ROW]
[ROW][C]8[/C][C]-0.086442[/C][C]-0.6526[/C][C]0.258312[/C][/ROW]
[ROW][C]9[/C][C]-0.033118[/C][C]-0.25[/C][C]0.401728[/C][/ROW]
[ROW][C]10[/C][C]0.135256[/C][C]1.0212[/C][C]0.155746[/C][/ROW]
[ROW][C]11[/C][C]0.035058[/C][C]0.2647[/C][C]0.396105[/C][/ROW]
[ROW][C]12[/C][C]-0.161175[/C][C]-1.2168[/C][C]0.114339[/C][/ROW]
[ROW][C]13[/C][C]-0.079458[/C][C]-0.5999[/C][C]0.275478[/C][/ROW]
[ROW][C]14[/C][C]-0.066176[/C][C]-0.4996[/C][C]0.309635[/C][/ROW]
[ROW][C]15[/C][C]0.084083[/C][C]0.6348[/C][C]0.264045[/C][/ROW]
[ROW][C]16[/C][C]0.017552[/C][C]0.1325[/C][C]0.447521[/C][/ROW]
[ROW][C]17[/C][C]0.203294[/C][C]1.5348[/C][C]0.065178[/C][/ROW]
[ROW][C]18[/C][C]0.012837[/C][C]0.0969[/C][C]0.461566[/C][/ROW]
[ROW][C]19[/C][C]-0.117136[/C][C]-0.8844[/C][C]0.19011[/C][/ROW]
[ROW][C]20[/C][C]-0.130146[/C][C]-0.9826[/C][C]0.164983[/C][/ROW]
[ROW][C]21[/C][C]0.123048[/C][C]0.929[/C][C]0.178406[/C][/ROW]
[ROW][C]22[/C][C]-0.213827[/C][C]-1.6144[/C][C]0.055986[/C][/ROW]
[ROW][C]23[/C][C]0.180169[/C][C]1.3602[/C][C]0.089554[/C][/ROW]
[ROW][C]24[/C][C]-0.091049[/C][C]-0.6874[/C][C]0.247308[/C][/ROW]
[ROW][C]25[/C][C]-0.064482[/C][C]-0.4868[/C][C]0.314122[/C][/ROW]
[ROW][C]26[/C][C]0.011412[/C][C]0.0862[/C][C]0.465822[/C][/ROW]
[ROW][C]27[/C][C]-0.012091[/C][C]-0.0913[/C][C]0.463792[/C][/ROW]
[ROW][C]28[/C][C]-0.09793[/C][C]-0.7394[/C][C]0.231363[/C][/ROW]
[ROW][C]29[/C][C]-0.046545[/C][C]-0.3514[/C][C]0.363289[/C][/ROW]
[ROW][C]30[/C][C]-0.047849[/C][C]-0.3613[/C][C]0.359623[/C][/ROW]
[ROW][C]31[/C][C]-0.00892[/C][C]-0.0673[/C][C]0.473272[/C][/ROW]
[ROW][C]32[/C][C]-0.074632[/C][C]-0.5635[/C][C]0.287667[/C][/ROW]
[ROW][C]33[/C][C]-0.062362[/C][C]-0.4708[/C][C]0.319781[/C][/ROW]
[ROW][C]34[/C][C]0.133491[/C][C]1.0078[/C][C]0.158897[/C][/ROW]
[ROW][C]35[/C][C]0.019847[/C][C]0.1498[/C][C]0.44071[/C][/ROW]
[ROW][C]36[/C][C]-0.176779[/C][C]-1.3347[/C][C]0.093649[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31626&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31626&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
1-0.106834-0.80660.21163
20.0841250.63510.263942
30.1765951.33330.093875
40.0326130.24620.403197
50.2056461.55260.063028
60.2501721.88880.032008
7-0.072673-0.54870.292687
8-0.086442-0.65260.258312
9-0.033118-0.250.401728
100.1352561.02120.155746
110.0350580.26470.396105
12-0.161175-1.21680.114339
13-0.079458-0.59990.275478
14-0.066176-0.49960.309635
150.0840830.63480.264045
160.0175520.13250.447521
170.2032941.53480.065178
180.0128370.09690.461566
19-0.117136-0.88440.19011
20-0.130146-0.98260.164983
210.1230480.9290.178406
22-0.213827-1.61440.055986
230.1801691.36020.089554
24-0.091049-0.68740.247308
25-0.064482-0.48680.314122
260.0114120.08620.465822
27-0.012091-0.09130.463792
28-0.09793-0.73940.231363
29-0.046545-0.35140.363289
30-0.047849-0.36130.359623
31-0.00892-0.06730.473272
32-0.074632-0.56350.287667
33-0.062362-0.47080.319781
340.1334911.00780.158897
350.0198470.14980.44071
36-0.176779-1.33470.093649


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')