*! mixlpred 1.3.0 29Mar2016 *! author arh program define mixlpred version 9.2 syntax newvarname [if] [in], [NREP(integer 50) BURN(integer 15)] if ("`e(cmd)'" != "mixlogit" & "`e(cmd)'" != "mixlogitwtp") error 301 local cmd `e(cmd)' ** Mark the prediction sample ** marksample touse, novarlist markout `touse' `e(indepvars)' `e(group)' `e(id)' ** Generate variables used to sort data ** tempvar sorder altid gen `sorder' = _n sort `touse' `e(id)' `e(group)' by `touse' `e(id)' `e(group)': gen `altid' = _n ** Drop data not in prediction sample ** preserve qui keep if `touse' ** Generate individual id ** if ("`e(id)'" != "") { tempvar nchoice pid sort `e(group)' by `e(group)': gen `nchoice' = cond(_n==_N,1,0) sort `e(id)' by `e(id)': egen `pid' = sum(`nchoice') qui duplicates report `e(id)' mata: mixl_np = st_numscalar("r(unique_value)") mata: mixl_T = st_data(., ("`pid'")) } else { qui duplicates report `e(group)' mata: mixl_np = st_numscalar("r(unique_value)") mata: mixl_T = J(st_nobs(),1,1) } ** Generate choice occacion id ** tempvar csid sort `e(group)' by `e(group)': egen `csid' = sum(1) qui duplicates report `e(group)' local nobs = r(unique_value) ** Sort data ** sort `e(id)' `e(group)' `altid' ** Set Mata matrices to be used in prediction routine ** local rhs `e(indepvars)' mata: mixl_X = st_data(., tokens(st_local("rhs"))) mata: mixl_CSID = st_data(., ("`csid'")) local totobs = _N ** Restore data ** restore tempname b matrix `b' = e(b) qui gen double `varlist' = . mata: mixl_pred("`b'", "`varlist'", "`touse'") ** Restore sort order ** sort `sorder' end version 9.2 mata: void mixl_pred(string scalar B_s, string scalar P_s, string scalar TOUSE_s) { external mixl_X external mixl_T external mixl_CSID external mixl_np np = mixl_np command = st_local("cmd") nrep = strtoreal(st_local("nrep")) totobs = strtoreal(st_local("totobs")) kfix = st_numscalar("e(kfix)") krnd = st_numscalar("e(krnd)") krln = st_numscalar("e(krln)") burn = strtoreal(st_local("burn")) corr = st_numscalar("e(corr)") user = st_numscalar("e(userdraws)") B = st_matrix(B_s)' kall = kfix + krnd if (kfix > 0) { MFIX = B[|1,1\kfix,1|] MFIX = MFIX :* J(kfix,nrep,1) } MRND = B[|(kfix+1),1\kall,1|] if (corr == 1) { ncho = st_numscalar("e(k_aux)") SRND = invvech(B[|(kall+1),1\(kall+ncho),1|]) :* lowertriangle(J(krnd,krnd,1)) } else { SRND = diag(B[|(kall+1),1\(kfix+2*krnd),1|]) } if (user == 1) external mixl_USERDRAWS P = J(totobs,1,0) i = 1 for (n=1; n<=np; n++) { if (user == 1) { ERR = invnormal(mixl_USERDRAWS[.,(1+nrep*(n-1))..(nrep*n)]) } else { ERR = invnormal(halton(nrep,krnd,(1+burn+nrep*(n-1)))') } if (kfix > 0) BETA = MFIX \ (MRND :+ (SRND*ERR)) else BETA = MRND :+ (SRND*ERR) if (krln > 0) { if ((kall-krln) > 0) { BETA = BETA[|1,1\(kall-krln),nrep|]\exp(BETA[|(kall-krln+1),1\kall,nrep|]) } else { BETA = exp(BETA) } } t = 1 nc = mixl_T[i,1] for (t=1; t<=nc; t++) { XMAT = mixl_X[|i,1\(i+mixl_CSID[i,1]-1),cols(mixl_X)|] if (command == "mixlogitwtp") { B1 = BETA[1..(rows(BETA)-1),.] \ J(1,cols(BETA),1) B2 = J(rows(XMAT),cols(BETA),1) :* BETA[rows(BETA),.] V = XMAT * B1 V = B2 :* V R = exp(V) :/ colsum(exp(V),1) } else { EV = exp(XMAT*BETA) R = EV :/ colsum(EV,1) } P[|i,1\(i+mixl_CSID[i,1]-1),1|] = mean(R',1)' i = i + mixl_CSID[i,1] } } st_store(.,P_s,TOUSE_s,P) } end exit