search for: dpdensity

Hi all, in the function DPdensity( ) example -- ?DPdensity --, we can extract the density estimate by: # Extracting the density estimate cbind(fit1.1$x1,fit1.1$dens) cbind(fit1.2$x1,fit1.2$dens) How is density calculated? I can imagine it is a mixture of normal densities, but where is the information about the density stored?...

...0,0,2),ncol=3)) prior<-list(a0=1,b0=1/5,nu1=4,nu2=4,s2=s2, m2=m2,psiinv2=psiinv2,tau1=0.01,tau2=0.01) state <- NULL # MCMC parameters nburn<-1000 nsave<-5000 nskip<-10 ndisplay<-1000 mcmc <- list(nburn=nburn,nsave=nsave,nskip=nskip,ndisplay=ndisplay) # Fit the model fit3<-DPdensity(y=rnormm,mcmc=mcmc, prior=prior, state=state,status=TRUE,na.action=na.omit) All is fine untill I bacame... MCMC scan 1000 of 5000 (CPU time: 32.125 s) MCMC scan 2000 of 5000 (CPU time: 61.797 s) MCMC scan 3000 of 5000 (CPU time: 91.281 s) MCMC scan 4000 of 5000 (CPU time: 120.750 s) MCMC scan 50...

...al package for Bayesian nonparametric and semi-parametric data analysis. So far, the package includes models based on Dirichlet processes, Dirichlet process mixtures of normals, Polya trees, and Random Bernstein polynomials. A list of current functions is given next: 1) Density estimation: DPdensity (using DPM of normals), PTdensity (using Mixtures of Polya Trees), and BDPdensity (using Bernstein-Dirichlet prior). The first two functions allow uni- and multi-variate analysis. 2) Nonparametric random effects distributions in mixed effects models: 2.1) DPlmm and DPMlmm, using a DP/MD...

...al package for Bayesian nonparametric and semi-parametric data analysis. So far, the package includes models based on Dirichlet processes, Dirichlet process mixtures of normals, Polya trees, and Random Bernstein polynomials. A list of current functions is given next: 1) Density estimation: DPdensity (using DPM of normals), PTdensity (using Mixtures of Polya Trees), and BDPdensity (using Bernstein-Dirichlet prior). The first two functions allow uni- and multi-variate analysis. 2) Nonparametric random effects distributions in mixed effects models: 2.1) DPlmm and DPMlmm, using a DP/MD...