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70 lines
1.8 KiB
Plaintext
70 lines
1.8 KiB
Plaintext
9 months ago
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*! Log likelihood for cfa1: linear form; v.2.1
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program define cfa1_lf
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args lnf $CFA1theta
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* $CFA1theta contains all the names needed:
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* $CFA1theta == l_1 ... l_q v_1 ... v_q m_1 ... m_q phi
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gettoken lnf allthenames : 0
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tempvar lnl
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qui g double `lnl' = .
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nobreak mata: CFA1_NormalLKHDr( "`allthenames'", "$CFA1vars", "`lnl'")
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qui replace `lnf' = `lnl'
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end
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*! NormalLKHDr: normal likelihood with normal deviates in variables
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*! v.2.1 Stas Kolenikov skolenik@gmail.com
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cap mata: mata drop CFA1_NormalLKHDr()
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mata:
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void CFA1_NormalLKHDr(
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string parnames, // the parameter names
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string varnames, // the variables
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string loglkhd // where the stuff is to be returned
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) {
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// declarations
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real matrix data, lnl, parms // views of the data
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real matrix lambda, means, vars, phi // parameters
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real matrix Sigma, WorkSigma, InvWorkSigma, SS // the covariance matrices and temp matrix
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real scalar p, n // dimension, no. obs
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// get the data in
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st_view(data=., ., tokens(varnames) )
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st_view(lnl=., ., tokens(loglkhd) )
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st_view(parms=., 1, tokens(parnames) )
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n=rows(data)
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p=cols(data)
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// get the parameters in
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lambda= parms[1,1..p]
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vars = parms[1,p+1..2*p]
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means = parms[1,2*p+1..3*p]
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phi = parms[1,3*p+1]
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Sigma = lambda'*lambda*phi + diag(vars)
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SS = cholesky(Sigma)
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InvWorkSigma = solvelower(SS,I(rows(SS)))
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InvWorkSigma = solveupper(SS',InvWorkSigma)
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ldetWS = 2*ln(dettriangular(SS))
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for( i=1; i<=n; i++ ) {
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lnl[i,1] = -.5*(data[i,.]-means)*InvWorkSigma*(data[i,.]-means)' - .5*ldetWS - .5*p*ln(2*pi())
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}
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}
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end
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exit
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History:
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v.2.0 March 10, 2006 -- re-written for Stata 9 and Mata
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v.2.1 March 10, 2006 -- everything is moved to Mata
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