Estimates the marginal parameter modes using kernel density estimation

Description

Estimates the marginal parameter modes using kernel density estimation

Usage

posterior.mode(x, adjust=0.1, ...)

Arguments

Value

modes of the kernel density estimates

Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

See Also

density

Examples

v<-rIW(as.matrix(1),10, n=1000)
hist(v)
abline(v=posterior.mode(mcmc(v)), col="red")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(MCMCglmm)
Loading required package: Matrix
Loading required package: coda
Loading required package: ape
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MCMCglmm/posterior.mode.Rd_%03d_medium.png", width=480, height=480)
> ### Name: posterior.mode
> ### Title: Estimates the marginal parameter modes using kernel density
> ###   estimation
> ### Aliases: posterior.mode
> ### Keywords: distribution
> 
> ### ** Examples
> 
> v<-rIW(as.matrix(1),10, n=1000)
> hist(v)
> abline(v=posterior.mode(mcmc(v)), col="red")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>