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182 lines
4.7 KiB
Plaintext
182 lines
4.7 KiB
Plaintext
9 months ago
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*! version 2 15jan2013
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************************************************************************************************************
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* gausshermite : Estimate an integral of the form |f(x)g(x/mu,sigma)dx or f(x,y)g(x,y/mu,Sigma)dxdy where g(x/mu,sigma) is the distribution function
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* of the gaussian distribution of mean mu and variance sigma^2 and g(x,y/mu,Sigma) is the distribution function
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* of the bivariate normal distribution of mean mu and covariance matrix Sigma by Gauss Hermite quadratures
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*
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* Version 1 : May 5, 2005 (Jean-Benoit Hardouin)
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* Version 1.1: June 14, 2012 /*name option*/ (Jean-Benoit Hardouin)
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* Version 2: January 15, 2013 /*bivariate normal distribution*/ (Jean-Benoit Hardouin, Mohand-Larbi Feddag, Myriam Blanchin)
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*
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* Jean-Benoit Hardouin, jean-benoit.hardouin@univ-nantes.fr
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* EA 4275 "Biostatistics, Pharmacoepidemiology and Subjectives Measures in Health"
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* Faculty of Pharmaceutical Sciences - University of Nantes - France
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* http://www.sphere-nantes.org
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*
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* News about this program : http://anaqol.free.fr
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* FreeIRT Project : http://freeirt.free.fr
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*
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* Copyright 2005, 2013 Jean-Benoit Hardouin, Mohand-Larbi Feddag, Myriam Blanchin
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*
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************************************************************************************************************
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program define gausshermite,rclass
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version 7
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syntax anything [, Sigma(real -1) Var(string) MU(string) Nodes(integer 12) Display Name(string)]
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tempfile gauss
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qui capture save `gauss',replace
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local save=0
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if _rc==0 {
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qui save `gauss',replace
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local save=1
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}
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tokenize `anything'
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drop _all
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tempname mean variance C
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qui set obs `=`nodes'*`nodes''
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if "`name'"=="" {
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if `sigma'!=-1{
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if "`var'"==""{
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local name x
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local nb=1
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}
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else{
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di in red "{p}Please fill in the {hi:name} option{p_end}"
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error 198
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exit
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}
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}
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else{
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if "`var'"!=""{
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local name1 x1
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local name2 x2
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local nb=2
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}
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else{
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di in red "{p}Please fill in the {hi:name} option{p_end}"
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error 198
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exit
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}
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}
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}
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else {
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local nb=wordcount("`name'")
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if `nb'==2{
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local name1=word("`name'",1)
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local name2=word("`name'",2)
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}
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}
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if `nb'==2{
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capture confirm matrix `var'
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if !_rc{
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if colsof(`var')==2 & rowsof(`var')==2{
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matrix `C'=cholesky(`var')
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}
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else{
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di in red "{p}The covariance matrix in the {hi:var} option should be a 2x2 matrix for a bivariate distribution{p_end}"
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error 198
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exit
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}
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}
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else{
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matrix `variance'=(1,0\0,1)
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matrix `C'=cholesky(`variance')
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}
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}
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else{
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if `sigma'==-1{
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local sig=1
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}
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else{
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local sig=`sigma'
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}
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}
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capture confirm matrix `mu'
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if !_rc{
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if colsof(`mu')==1 & rowsof(`mu')==1{
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local `mean'=`mu'[1,1]
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}
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else{
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matrix `mean'=`mu'
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}
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}
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else{
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if "`mu'"==""{
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if `nb'==1{
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local `mean'=0
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}
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else{
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matrix `mean'=(0,0)
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}
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}
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else{
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local `mean'=`mu'
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}
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}
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tempname noeuds poids
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qui ghquadm `nodes' `noeuds' `poids'
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if `nb'==1{
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qui gen `name'=.
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qui gen poids=.
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forvalues i=1/`nodes' {
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qui replace `name'=`noeuds'[1,`i'] in `i'
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qui replace poids=`poids'[1,`i'] in `i'
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}
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qui replace `name'=`name'*(sqrt(2)*`sig')+``mean''
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qui gen f=poids/sqrt(_pi)*(`1')
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*list `name' poids f in 1/5
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}
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else{
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forvalues i=1/`nb'{
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qui gen `name`i''=.
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qui gen poids`i'=.
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}
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local line=1
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forvalues i=1/`nodes' {
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forvalues j=1/`nodes' {
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qui replace `name1'=`noeuds'[1,`i'] *(sqrt(2)*`C'[1,1])+`mean'[1,1] in `line'
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qui replace `name2'=`noeuds'[1,`i'] *(sqrt(2)*`C'[2,1])+`noeuds'[1,`j'] *(sqrt(2)*`C'[2,2])+`mean'[1,2] in `line'
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qui replace poids1=`poids'[1,`i'] in `line'
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qui replace poids2=`poids'[1,`j'] in `line'
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local ++line
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}
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}
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qui gen f=poids1*poids2*(`1')/(_pi)
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*list `name1' `name2' poids1 poids2 f in 10/20
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}
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qui su f
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return scalar int=r(sum)
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if "`display'"!="" {
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di in green "int_R (`1')g(`name'/sigma=`sig')d`name'=" in yellow %12.8f `r(sum)'
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}
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drop _all
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if `save'==1 {
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qui use `gauss',clear
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}
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end
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