[R] SEM : Warning : Could not compute QR decomposition of Hessian

Wed Aug 25 20:26:18 CEST 2010

Dear Anne,

I started to diagram your model but stopped when I noticed some problems:
(1) Some variables, such as pays_alti, are clearly endogenous, since they
have arrows pointing to them, yet are declared as fixed exogenous variables;
that clearly doesn't make sense. (2) You've placed conflicting constraints
on factor loadings and the variances of latent variables, for example
setting both the path from the factor type_paysage to the indicator
pays_alti and the variance of type_paysage to 1; again, that doesn't make
sense.

Do you have a path diagram for the model that you're trying to fit? It would
in particular be helpful to have a diagram of the structural part of the
model.

Regards,
 John

--------------------------------
John Fox
Senator William McMaster 
  Professor of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
> Behalf Of Anne Mimet
> Sent: August-25-10 10:27 AM
> To: r-help at r-project.org
> Subject: [R] SEM : Warning : Could not compute QR decomposition of Hessian
> 
> Hi useRs,
> 
> I'm trying for the first time to use a sem. The model finally runs,
> but gives a warning saying :
> "In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names
> = vars,  :   Could not compute QR decomposition of Hessian.
> Optimization probably did not converge. "
> 
> I found in R-help some posts on this warning, but my attemps to modify
> the code didn't change the warning message (i tried to give an error
> of 1 to the latente variables). I can't figure what the problem is.
> Here is the code :
> 
> 
> tab<-read.table("F:/Mes documents/stats/sem/donnees_corr.txt",
> header=T, sep="",na.strings = "NA")
> 
> tab[,46]<-as.factor(tab[,46])
> tab[,24]<-as.factor(tab[,24])
> tab[,40]<-as.factor(tab[,40])
> 
> fct_cor<-hetcor(tab, ML=T)
> cor_tab<- fct_cor$correlations
> 
> moment_tab<-read.moments(diag=F, names=c('c1','c2', 'c3','c4','c5',
> 'c6','c7', 'c8', 'c9',  'ind_plando', 'long_sup15', 'long_inf15',
> 'pente', 'est', 'sud','ouest', 'nord' ,'reg_hydriq', 'prof_sol',
> 'pierro', 'efferv', 'struct','drainage','texture', 'route1_pond',
> 'route2_pond',
> 'pourcactif', 'tx_chomage', 'pourcagric', 'pourc_jeunes', 'pop99',
> 'rev_imp_foyer','eq_CONC', 'eq_sante', 'eq_edu', 'sold_nat',
> 'sold_mig', 'tps_dom_emp','TXEMPLOI','ORIECO','dist_paris','axe1',
> 'axe2', 'axe3', 'dist_protect','urbanisation','pays_incli','pays_alti'))
> # after comes the moment matrix (triangular)
> 
> ram_tab<-specify.model()
> type_paysage->pays_alti,NA,1
> type_paysage->pays_incli, pays2, NA
> pedo->reg_hydriq, NA, 1
> pedo->prof_sol, ped8, NA
> pedo->pierro, ped9, NA
> pedo->efferv, ped10, NA
> pedo->struct, ped11, NA
> pedo->drainage, ped12, NA
> pedo->texture, ped13, NA
> adj_99->c1, NA,1
> adj_99->c2, adj2,NA
> adj_99->c3, adj3,NA
> adj_99->c4, adj4,NA
> adj_99->c5, adj5,NA
> adj_99->c6, adj6,NA
> adj_99->c7, adj7,NA
> adj_99->c8, adj8,NA
> adj_99->c9, adj9,NA
> etat_hexa->axe1, NA, 1
> etat_hexa->axe2, et2, NA
> etat_hexa->axe3, et3, NA
> socioBV->sold_mig, BV1, NA
> socioBV->sold_nat, BV2, NA
> socioBV->TXEMPLOI, BV3, NA
> socioBV->ORIECO, BV4, NA
> socioBV->tps_dom_emp, NA, 1
> eqBV->eq_CONC, NA, 1
> eqBV->eq_sante, eq2, NA
> eqBV->eq_edu, eq3, NA
> socio_com->pourcactif , NA, 1
> socio_com->tx_chomage, com2, NA
> socio_com->pourcagric, com3, NA
> socio_com->pourc_jeunes, com4, NA
> socio_com->pop99, com5, NA
> socio_com->rev_imp_foyer, com7, NA
> access_hexa->route1_pond, NA, 1
> access_hexa->route2_pond, acc2, NA
> hydro->ind_plando, NA, 1
> hydro->long_sup15, eau2, NA
> hydro->long_inf15, eau3, NA
> topog->pente, NA, 1
> topog->est, top2, NA
> topog->sud, top3, NA
> topog->nord, top4, NA
> topog->ouest, top5, NA
> dist_protect-> urbanisation, cor1,NA
> dist_protect-> adj_99, cor2, NA
> dist_protect-> etat_hexa, cor3, NA
> topog-> urbanisation, cor4, NA
> topog-> adj_99, cor5, NA
> topog-> etat_hexa, cor6, NA
> topog-> access_hexa, cor7, NA
> topog<->hydro, cor8, NA
> topog<->pedo, cor9, NA
> pedo-> urbanisation, cor10, NA
> pedo-> adj_99, cor11, NA
> pedo-> etat_hexa, cor12, NA
> pedo<->hydro, cor1, NA
> hydro-> urbanisation, cor13, NA
> hydro-> adj_99, cor14, NA
> hydro-> etat_hexa, cor15, NA
> access_hexa-> urbanisation, cor16, NA
> access_hexa-> etat_hexa, cor17, NA
> socio_com-> etat_hexa, cor18, NA
> socio_com-> adj_99, cor19, NA
> socio_com-> urbanisation, cor20, NA
> dist_paris-> socio_com, cor21, NA
> dist_paris-> access_hexa, cor22, NA
> dist_paris-> adj_99, cor23, NA
> dist_paris-> etat_hexa, cor24, NA
> dist_paris-> urbanisation, cor25, NA
> dist_paris-> socioBV, cor26, NA
> socioBV-> eqBV, cor27, NA
> socioBV-> urbanisation, cor28, NA
> socioBV-> adj_99, cor29, NA
> socioBV-> etat_hexa, cor30, NA
> eqBV-> etat_hexa, cor31, NA
> eqBV-> adj_99, cor32, NA
> eqBV-> urbanisation, cor33, NA
> etat_hexa-> urbanisation, cor34, NA
> etat_hexa<-> adj_99, cor35, NA
> adj_99-> urbanisation, cor36, NA
> type_paysage-> urbanisation, cor37, NA
> type_paysage-> adj_99, cor38, NA
> type_paysage-> etat_hexa, cor39, NA
> dist_paris<->dist_paris, auto1, NA
> dist_protect<->dist_protect, auto2, NA
> c1 <-> c1, auto4, NA
> c2 <-> c2 , auto5, NA
> c3 <->  c3 , auto6, NA
> c4 <->  c4 , auto7, NA
> c5 <->  c5 , auto8, NA
> c6 <->  c6 , auto9, NA
> c7 <->  c7 , auto10, NA
> c8 <-> c8 , auto11, NA
> c9 <-> c9 , auto12, NA
> ind_plando <->  ind_plando, auto13, NA
> long_sup15 <-> long_sup15 , auto14, NA
> long_inf15 <->  long_inf15  , auto15, NA
> pente <-> pente , auto16, NA
> est<->  est , auto17, NA
> sud <->  sud , auto18, NA
> ouest<-> ouest , auto19, NA
> nord <->  nord , auto20, NA
> reg_hydriq <-> reg_hydriq , auto21, NA
> prof_sol<-> prof_sol , auto22, NA
> pierro <-> pierro , auto23, NA
> efferv <->  efferv , auto24, NA
> struct <-> struct , auto25, NA
> drainage <-> drainage, auto26, NA
> texture <->  texture , auto27, NA
> route1_pond  <->route1_pond  , auto30, NA
> route2_pond <-> route2_pond , auto31, NA
> pourcactif  <->  pourcactif , auto32, NA
> tx_chomage <->  tx_chomage, auto33, NA
> pourcagric <-> pourcagric , auto34, NA
> pourc_jeunes<-> pourc_jeunes  , auto36, NA
> pop99<-> pop99  , auto36, NA
> rev_imp_foyer <->   rev_imp_foyer , auto38, NA
> eq_CONC <-> eq_CONC, auto39, NA
> eq_sante <->eq_sante , auto40, NA
> eq_edu<->eq_edu   , auto41, NA
> sold_nat<->  sold_nat , auto42, NA
> sold_mig  <->  sold_mig  , auto43, NA
> tps_dom_emp  <->  tps_dom_emp , auto44, NA
> TXEMPLOI  <-> TXEMPLOI  , auto45, NA
> ORIECO  <-> ORIECO  , auto46, NA
> axe1  <->  axe1 , auto47, NA
> axe2  <->  axe2 , auto48, NA
> axe3  <-> axe3 , auto49, NA
> pays_incli<->pays_incli, auto70, NA
> pays_alti<->pays_alti, auto71, NA
> urbanisation<->  urbanisation , auto50, NA
> type_paysage <-> type_paysage ,  NA,1
> adj_99  <-> adj_99 , NA  ,1
> socioBV  <-> socioBV ,  NA,1
> eqBV  <-> eqBV  , NA ,1
> socio_com  <-> socio_com  , NA,1
> access_hexa <-> access_hexa , NA,1
> hydro  <-> hydro ,  NA ,1
> topog <->  topog ,  NA ,1
> pedo  <->  pedo  ,  NA ,1
> eqBV  <->  eqBV ,  NA ,1
> etat_hexa<->etat_hexa,  NA ,1
> 
> sem_dyn<-sem(ram_tab, moment_tab, N=1176, raw=T,
> fixed.x=c("pays_alti","reg_hydriq", "c1","axe1", "tps_dom_emp",
> "pourcactif",
> "route1_pond","ind_plando","pente"), par.size="ones")
> 
> 
> Any help would be greatly appreciate.
> 
> Thank you,
> 
> Anne
> 
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