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Modules/ado/personal/g/gausshermite2.ado

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+*! version 1  03 January 2012
+************************************************************************************************************
+* gausshermite2 : Estimate an integral of the form : f(x,y)g(x,y/mu,Sigma)dxdy where g(x,y/mu,Sigma) is the distribution function
+* of the bivariate normal distribution of mean mu and covariance matrix  Sigma by Gauss Hermite quadratures
+*
+* Version 1: 03 January 2012
+*
+*
+* Mohand Feddag, University of Nantes - France
+* Mohand-Larbi.Feddag@univ-nantes.fr *
+* News about this program : http://anaqol.free.fr
+* FreeIRT Project : http://freeirt.free.fr
+*
+* Copyright 2012 Mohand Feddag
+*
+* This program is free software; you can redistribute it and/or modify
+* it under the terms of the GNU General Public License as published by
+* the Free Software Foundation; either version 2 of the License, or
+* (at your option) any later version.
+*
+* This program is distributed in the hope that it will be useful,
+* but WITHOUT ANY WARRANTY; without even the implied warranty of
+* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+* GNU General Public License for more details.
+*
+* You should have received a copy of the GNU General Public License
+* along with this program; if not, write to the Free Software
+* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
+*
+************************************************************************************************************
+
+program define gausshermite2,rclass
+version 11
+syntax anything [, Mu(string) Sigma(string)  Nodes(integer 12) Display]
+tempfile gauss2
+qui capture save `gauss2',replace
+local save=0
+if _rc==0 {
+   qui save `gauss2',replace
+   local save=1
+}
+if "`mu'"=="" {
+   tempname mu
+   matrix `mu'=[0,0]
+}
+if "`sigma'"=="" {
+   tempname sigma
+   matrix `sigma'=[1,0\0,1]
+}
+tokenize `anything'
+
+drop _all
+qui set obs `=`nodes'*`nodes''
+tempname noeuds poids
+qui ghquadm `nodes' `noeuds' `poids' 
+
+* Cholesky transformation for the covariance matrix sigma
+ 
+matrix  C=cholesky(`sigma')
+*matrix list C
+local line=1
+qui gen x1=.
+qui gen x2=.
+qui gen poids1=.
+qui gen poids2=.
+forvalues i=1/`nodes' {
+   forvalues j=1/`nodes' {
+      qui replace x1=`noeuds'[1,`i'] *(sqrt(2)*C[1,1])+`mu'[1,1] in `line'
+       qui replace x2=`noeuds'[1,`i'] *(sqrt(2)*C[2,1])+`noeuds'[1,`j'] *(sqrt(2)*C[2,2])+`mu'[1,2] in `line'
+      qui replace poids1=`poids'[1,`i'] in `line'
+      qui replace poids2=`poids'[1,`j'] in `line'
+      local ++line
+   }
+}
+
+* Double somme du produit poids[i]*poids[j]*f(x1,x2) qui est affect<63> a la variable sum 
+ 
+qui gen f=poids1*poids2*(`1')/(_pi)
+*list x1 x2  poids1 f (sqrt(2)*_pi)
+qui su f
+local sum=r(sum)
+ return scalar int=`sum' 
+ 
+ if "`display'"!="" {
+   di in green "int_R^2 (`1')g(x1,x2/mu=`mu',Sigma=`Sigma')dx1dx2=" in yellow %12.8f `sum'
+}
+drop _all
+if `save'==1 {
+   qui use `gauss2',clear
+}
+end
+
+ 
+ 
+ 
+ 
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