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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 computationWed, 25 Nov 2009 12:35:50 -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/25/t1259177779mrptr9vauhvawje.htm/, Retrieved Tue, 07 May 2024 07:15:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59585, Retrieved Tue, 07 May 2024 07:15:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
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]
-   PD          [(Partial) Autocorrelation Function] [WS 8.3] [2009-11-25 19:35:50] [51118f1042b56b16d340924f16263174] [Current]
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Dataseries X:
1076.7
1035.9
1037
1154
1237.2
996.6
1238.2
1153.4
1268.1
1156
1144.5
1232.9
1055.2
1109.7
1079.8
1126.3
1196.8
1130.4
1183.6
1200.9
1426.6
1080.4
1325.4
1230
1125.9
1174.5
1151.9
1439.3
1344.3
1319.1
1257.6
1249.1
1397.1
1348
1548.2
1377.6
1402.9
1167.6
1392.9
1547
1420
1266.4
1280.8
1128.6
1449.5
1511.7
1548.3
1652
1650.5
1370.8
1653.3
1474.3
1418.8
1554.1
1156.6
1223.4
1337.5
1098.9
1037.6
1202.5




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=59585&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=59585&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59585&T=0

As an alternative you can also use a 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
1-0.503687-3.45310.000592
20.0933180.63980.262719
30.2063011.41430.081928
4-0.343322-2.35370.011411
50.1618571.10960.1364
60.0540610.37060.356291
7-0.053216-0.36480.358437
8-0.018951-0.12990.448593
90.1258660.86290.19629
10-0.278467-1.90910.031185
110.2532341.73610.044551
12-0.109577-0.75120.228132
13-0.128226-0.87910.191917
140.2103471.44210.077957
15-0.11479-0.7870.217629
160.0116460.07980.468353
170.1132030.77610.220794
18-0.141737-0.97170.168087
190.0207370.14220.443778
200.1328670.91090.1835
21-0.092575-0.63470.264364
220.052210.35790.360999
230.0378230.25930.398267
24-0.209055-1.43320.079209
250.0957050.65610.257473
260.0557490.38220.352019
27-0.095457-0.65440.258015
280.1697031.16340.125265
29-0.135119-0.92630.179504
30-0.010589-0.07260.471219
310.077310.530.2993
32-0.186911-1.28140.10317
330.1834991.2580.107301
34-0.083863-0.57490.284038
35-0.051321-0.35180.363266
360.1236080.84740.20053

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.503687 & -3.4531 & 0.000592 \tabularnewline
2 & 0.093318 & 0.6398 & 0.262719 \tabularnewline
3 & 0.206301 & 1.4143 & 0.081928 \tabularnewline
4 & -0.343322 & -2.3537 & 0.011411 \tabularnewline
5 & 0.161857 & 1.1096 & 0.1364 \tabularnewline
6 & 0.054061 & 0.3706 & 0.356291 \tabularnewline
7 & -0.053216 & -0.3648 & 0.358437 \tabularnewline
8 & -0.018951 & -0.1299 & 0.448593 \tabularnewline
9 & 0.125866 & 0.8629 & 0.19629 \tabularnewline
10 & -0.278467 & -1.9091 & 0.031185 \tabularnewline
11 & 0.253234 & 1.7361 & 0.044551 \tabularnewline
12 & -0.109577 & -0.7512 & 0.228132 \tabularnewline
13 & -0.128226 & -0.8791 & 0.191917 \tabularnewline
14 & 0.210347 & 1.4421 & 0.077957 \tabularnewline
15 & -0.11479 & -0.787 & 0.217629 \tabularnewline
16 & 0.011646 & 0.0798 & 0.468353 \tabularnewline
17 & 0.113203 & 0.7761 & 0.220794 \tabularnewline
18 & -0.141737 & -0.9717 & 0.168087 \tabularnewline
19 & 0.020737 & 0.1422 & 0.443778 \tabularnewline
20 & 0.132867 & 0.9109 & 0.1835 \tabularnewline
21 & -0.092575 & -0.6347 & 0.264364 \tabularnewline
22 & 0.05221 & 0.3579 & 0.360999 \tabularnewline
23 & 0.037823 & 0.2593 & 0.398267 \tabularnewline
24 & -0.209055 & -1.4332 & 0.079209 \tabularnewline
25 & 0.095705 & 0.6561 & 0.257473 \tabularnewline
26 & 0.055749 & 0.3822 & 0.352019 \tabularnewline
27 & -0.095457 & -0.6544 & 0.258015 \tabularnewline
28 & 0.169703 & 1.1634 & 0.125265 \tabularnewline
29 & -0.135119 & -0.9263 & 0.179504 \tabularnewline
30 & -0.010589 & -0.0726 & 0.471219 \tabularnewline
31 & 0.07731 & 0.53 & 0.2993 \tabularnewline
32 & -0.186911 & -1.2814 & 0.10317 \tabularnewline
33 & 0.183499 & 1.258 & 0.107301 \tabularnewline
34 & -0.083863 & -0.5749 & 0.284038 \tabularnewline
35 & -0.051321 & -0.3518 & 0.363266 \tabularnewline
36 & 0.123608 & 0.8474 & 0.20053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59585&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]-0.503687[/C][C]-3.4531[/C][C]0.000592[/C][/ROW]
[ROW][C]2[/C][C]0.093318[/C][C]0.6398[/C][C]0.262719[/C][/ROW]
[ROW][C]3[/C][C]0.206301[/C][C]1.4143[/C][C]0.081928[/C][/ROW]
[ROW][C]4[/C][C]-0.343322[/C][C]-2.3537[/C][C]0.011411[/C][/ROW]
[ROW][C]5[/C][C]0.161857[/C][C]1.1096[/C][C]0.1364[/C][/ROW]
[ROW][C]6[/C][C]0.054061[/C][C]0.3706[/C][C]0.356291[/C][/ROW]
[ROW][C]7[/C][C]-0.053216[/C][C]-0.3648[/C][C]0.358437[/C][/ROW]
[ROW][C]8[/C][C]-0.018951[/C][C]-0.1299[/C][C]0.448593[/C][/ROW]
[ROW][C]9[/C][C]0.125866[/C][C]0.8629[/C][C]0.19629[/C][/ROW]
[ROW][C]10[/C][C]-0.278467[/C][C]-1.9091[/C][C]0.031185[/C][/ROW]
[ROW][C]11[/C][C]0.253234[/C][C]1.7361[/C][C]0.044551[/C][/ROW]
[ROW][C]12[/C][C]-0.109577[/C][C]-0.7512[/C][C]0.228132[/C][/ROW]
[ROW][C]13[/C][C]-0.128226[/C][C]-0.8791[/C][C]0.191917[/C][/ROW]
[ROW][C]14[/C][C]0.210347[/C][C]1.4421[/C][C]0.077957[/C][/ROW]
[ROW][C]15[/C][C]-0.11479[/C][C]-0.787[/C][C]0.217629[/C][/ROW]
[ROW][C]16[/C][C]0.011646[/C][C]0.0798[/C][C]0.468353[/C][/ROW]
[ROW][C]17[/C][C]0.113203[/C][C]0.7761[/C][C]0.220794[/C][/ROW]
[ROW][C]18[/C][C]-0.141737[/C][C]-0.9717[/C][C]0.168087[/C][/ROW]
[ROW][C]19[/C][C]0.020737[/C][C]0.1422[/C][C]0.443778[/C][/ROW]
[ROW][C]20[/C][C]0.132867[/C][C]0.9109[/C][C]0.1835[/C][/ROW]
[ROW][C]21[/C][C]-0.092575[/C][C]-0.6347[/C][C]0.264364[/C][/ROW]
[ROW][C]22[/C][C]0.05221[/C][C]0.3579[/C][C]0.360999[/C][/ROW]
[ROW][C]23[/C][C]0.037823[/C][C]0.2593[/C][C]0.398267[/C][/ROW]
[ROW][C]24[/C][C]-0.209055[/C][C]-1.4332[/C][C]0.079209[/C][/ROW]
[ROW][C]25[/C][C]0.095705[/C][C]0.6561[/C][C]0.257473[/C][/ROW]
[ROW][C]26[/C][C]0.055749[/C][C]0.3822[/C][C]0.352019[/C][/ROW]
[ROW][C]27[/C][C]-0.095457[/C][C]-0.6544[/C][C]0.258015[/C][/ROW]
[ROW][C]28[/C][C]0.169703[/C][C]1.1634[/C][C]0.125265[/C][/ROW]
[ROW][C]29[/C][C]-0.135119[/C][C]-0.9263[/C][C]0.179504[/C][/ROW]
[ROW][C]30[/C][C]-0.010589[/C][C]-0.0726[/C][C]0.471219[/C][/ROW]
[ROW][C]31[/C][C]0.07731[/C][C]0.53[/C][C]0.2993[/C][/ROW]
[ROW][C]32[/C][C]-0.186911[/C][C]-1.2814[/C][C]0.10317[/C][/ROW]
[ROW][C]33[/C][C]0.183499[/C][C]1.258[/C][C]0.107301[/C][/ROW]
[ROW][C]34[/C][C]-0.083863[/C][C]-0.5749[/C][C]0.284038[/C][/ROW]
[ROW][C]35[/C][C]-0.051321[/C][C]-0.3518[/C][C]0.363266[/C][/ROW]
[ROW][C]36[/C][C]0.123608[/C][C]0.8474[/C][C]0.20053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59585&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59585&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.503687-3.45310.000592
20.0933180.63980.262719
30.2063011.41430.081928
4-0.343322-2.35370.011411
50.1618571.10960.1364
60.0540610.37060.356291
7-0.053216-0.36480.358437
8-0.018951-0.12990.448593
90.1258660.86290.19629
10-0.278467-1.90910.031185
110.2532341.73610.044551
12-0.109577-0.75120.228132
13-0.128226-0.87910.191917
140.2103471.44210.077957
15-0.11479-0.7870.217629
160.0116460.07980.468353
170.1132030.77610.220794
18-0.141737-0.97170.168087
190.0207370.14220.443778
200.1328670.91090.1835
21-0.092575-0.63470.264364
220.052210.35790.360999
230.0378230.25930.398267
24-0.209055-1.43320.079209
250.0957050.65610.257473
260.0557490.38220.352019
27-0.095457-0.65440.258015
280.1697031.16340.125265
29-0.135119-0.92630.179504
30-0.010589-0.07260.471219
310.077310.530.2993
32-0.186911-1.28140.10317
330.1834991.2580.107301
34-0.083863-0.57490.284038
35-0.051321-0.35180.363266
360.1236080.84740.20053







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.503687-3.45310.000592
2-0.214904-1.47330.073668
30.2179741.49440.070883
4-0.161274-1.10560.137255
5-0.141766-0.97190.168038
60.0687130.47110.319885
70.1772631.21530.11517
8-0.100421-0.68850.247276
90.0476520.32670.372679
10-0.196857-1.34960.091807
110.1098980.75340.227476
12-0.021135-0.14490.442708
13-0.154813-1.06130.146978
14-0.084175-0.57710.283323
150.1539791.05560.148268
160.0491940.33730.368712
170.0322740.22130.412926
18-0.122369-0.83890.202881
190.023010.15780.437664
200.1377950.94470.174828
210.1592071.09150.140315
22-0.101867-0.69840.244196
23-0.05637-0.38650.350452
24-0.131326-0.90030.186268
25-0.046179-0.31660.376478
260.0294520.20190.420429
270.053540.36710.357614
280.0504010.34550.365617
29-0.028766-0.19720.422258
30-0.006746-0.04620.481654
310.0456260.31280.377909
32-0.202741-1.38990.08555
330.0498080.34150.367137
34-0.033913-0.23250.408582
35-0.047906-0.32840.372023
36-0.037388-0.25630.399411

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.503687 & -3.4531 & 0.000592 \tabularnewline
2 & -0.214904 & -1.4733 & 0.073668 \tabularnewline
3 & 0.217974 & 1.4944 & 0.070883 \tabularnewline
4 & -0.161274 & -1.1056 & 0.137255 \tabularnewline
5 & -0.141766 & -0.9719 & 0.168038 \tabularnewline
6 & 0.068713 & 0.4711 & 0.319885 \tabularnewline
7 & 0.177263 & 1.2153 & 0.11517 \tabularnewline
8 & -0.100421 & -0.6885 & 0.247276 \tabularnewline
9 & 0.047652 & 0.3267 & 0.372679 \tabularnewline
10 & -0.196857 & -1.3496 & 0.091807 \tabularnewline
11 & 0.109898 & 0.7534 & 0.227476 \tabularnewline
12 & -0.021135 & -0.1449 & 0.442708 \tabularnewline
13 & -0.154813 & -1.0613 & 0.146978 \tabularnewline
14 & -0.084175 & -0.5771 & 0.283323 \tabularnewline
15 & 0.153979 & 1.0556 & 0.148268 \tabularnewline
16 & 0.049194 & 0.3373 & 0.368712 \tabularnewline
17 & 0.032274 & 0.2213 & 0.412926 \tabularnewline
18 & -0.122369 & -0.8389 & 0.202881 \tabularnewline
19 & 0.02301 & 0.1578 & 0.437664 \tabularnewline
20 & 0.137795 & 0.9447 & 0.174828 \tabularnewline
21 & 0.159207 & 1.0915 & 0.140315 \tabularnewline
22 & -0.101867 & -0.6984 & 0.244196 \tabularnewline
23 & -0.05637 & -0.3865 & 0.350452 \tabularnewline
24 & -0.131326 & -0.9003 & 0.186268 \tabularnewline
25 & -0.046179 & -0.3166 & 0.376478 \tabularnewline
26 & 0.029452 & 0.2019 & 0.420429 \tabularnewline
27 & 0.05354 & 0.3671 & 0.357614 \tabularnewline
28 & 0.050401 & 0.3455 & 0.365617 \tabularnewline
29 & -0.028766 & -0.1972 & 0.422258 \tabularnewline
30 & -0.006746 & -0.0462 & 0.481654 \tabularnewline
31 & 0.045626 & 0.3128 & 0.377909 \tabularnewline
32 & -0.202741 & -1.3899 & 0.08555 \tabularnewline
33 & 0.049808 & 0.3415 & 0.367137 \tabularnewline
34 & -0.033913 & -0.2325 & 0.408582 \tabularnewline
35 & -0.047906 & -0.3284 & 0.372023 \tabularnewline
36 & -0.037388 & -0.2563 & 0.399411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59585&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]-0.503687[/C][C]-3.4531[/C][C]0.000592[/C][/ROW]
[ROW][C]2[/C][C]-0.214904[/C][C]-1.4733[/C][C]0.073668[/C][/ROW]
[ROW][C]3[/C][C]0.217974[/C][C]1.4944[/C][C]0.070883[/C][/ROW]
[ROW][C]4[/C][C]-0.161274[/C][C]-1.1056[/C][C]0.137255[/C][/ROW]
[ROW][C]5[/C][C]-0.141766[/C][C]-0.9719[/C][C]0.168038[/C][/ROW]
[ROW][C]6[/C][C]0.068713[/C][C]0.4711[/C][C]0.319885[/C][/ROW]
[ROW][C]7[/C][C]0.177263[/C][C]1.2153[/C][C]0.11517[/C][/ROW]
[ROW][C]8[/C][C]-0.100421[/C][C]-0.6885[/C][C]0.247276[/C][/ROW]
[ROW][C]9[/C][C]0.047652[/C][C]0.3267[/C][C]0.372679[/C][/ROW]
[ROW][C]10[/C][C]-0.196857[/C][C]-1.3496[/C][C]0.091807[/C][/ROW]
[ROW][C]11[/C][C]0.109898[/C][C]0.7534[/C][C]0.227476[/C][/ROW]
[ROW][C]12[/C][C]-0.021135[/C][C]-0.1449[/C][C]0.442708[/C][/ROW]
[ROW][C]13[/C][C]-0.154813[/C][C]-1.0613[/C][C]0.146978[/C][/ROW]
[ROW][C]14[/C][C]-0.084175[/C][C]-0.5771[/C][C]0.283323[/C][/ROW]
[ROW][C]15[/C][C]0.153979[/C][C]1.0556[/C][C]0.148268[/C][/ROW]
[ROW][C]16[/C][C]0.049194[/C][C]0.3373[/C][C]0.368712[/C][/ROW]
[ROW][C]17[/C][C]0.032274[/C][C]0.2213[/C][C]0.412926[/C][/ROW]
[ROW][C]18[/C][C]-0.122369[/C][C]-0.8389[/C][C]0.202881[/C][/ROW]
[ROW][C]19[/C][C]0.02301[/C][C]0.1578[/C][C]0.437664[/C][/ROW]
[ROW][C]20[/C][C]0.137795[/C][C]0.9447[/C][C]0.174828[/C][/ROW]
[ROW][C]21[/C][C]0.159207[/C][C]1.0915[/C][C]0.140315[/C][/ROW]
[ROW][C]22[/C][C]-0.101867[/C][C]-0.6984[/C][C]0.244196[/C][/ROW]
[ROW][C]23[/C][C]-0.05637[/C][C]-0.3865[/C][C]0.350452[/C][/ROW]
[ROW][C]24[/C][C]-0.131326[/C][C]-0.9003[/C][C]0.186268[/C][/ROW]
[ROW][C]25[/C][C]-0.046179[/C][C]-0.3166[/C][C]0.376478[/C][/ROW]
[ROW][C]26[/C][C]0.029452[/C][C]0.2019[/C][C]0.420429[/C][/ROW]
[ROW][C]27[/C][C]0.05354[/C][C]0.3671[/C][C]0.357614[/C][/ROW]
[ROW][C]28[/C][C]0.050401[/C][C]0.3455[/C][C]0.365617[/C][/ROW]
[ROW][C]29[/C][C]-0.028766[/C][C]-0.1972[/C][C]0.422258[/C][/ROW]
[ROW][C]30[/C][C]-0.006746[/C][C]-0.0462[/C][C]0.481654[/C][/ROW]
[ROW][C]31[/C][C]0.045626[/C][C]0.3128[/C][C]0.377909[/C][/ROW]
[ROW][C]32[/C][C]-0.202741[/C][C]-1.3899[/C][C]0.08555[/C][/ROW]
[ROW][C]33[/C][C]0.049808[/C][C]0.3415[/C][C]0.367137[/C][/ROW]
[ROW][C]34[/C][C]-0.033913[/C][C]-0.2325[/C][C]0.408582[/C][/ROW]
[ROW][C]35[/C][C]-0.047906[/C][C]-0.3284[/C][C]0.372023[/C][/ROW]
[ROW][C]36[/C][C]-0.037388[/C][C]-0.2563[/C][C]0.399411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59585&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59585&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.503687-3.45310.000592
2-0.214904-1.47330.073668
30.2179741.49440.070883
4-0.161274-1.10560.137255
5-0.141766-0.97190.168038
60.0687130.47110.319885
70.1772631.21530.11517
8-0.100421-0.68850.247276
90.0476520.32670.372679
10-0.196857-1.34960.091807
110.1098980.75340.227476
12-0.021135-0.14490.442708
13-0.154813-1.06130.146978
14-0.084175-0.57710.283323
150.1539791.05560.148268
160.0491940.33730.368712
170.0322740.22130.412926
18-0.122369-0.83890.202881
190.023010.15780.437664
200.1377950.94470.174828
210.1592071.09150.140315
22-0.101867-0.69840.244196
23-0.05637-0.38650.350452
24-0.131326-0.90030.186268
25-0.046179-0.31660.376478
260.0294520.20190.420429
270.053540.36710.357614
280.0504010.34550.365617
29-0.028766-0.19720.422258
30-0.006746-0.04620.481654
310.0456260.31280.377909
32-0.202741-1.38990.08555
330.0498080.34150.367137
34-0.033913-0.23250.408582
35-0.047906-0.32840.372023
36-0.037388-0.25630.399411



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')