bayesMRMApp: Shiny App for exploring the results of Bayesian multivariate...

In mansukoh/bayesMRM: Bayesian Multivariate Receptor Modeling

Description

Call Shiny to show the results of Bayesian analysis of multivariate receptor modeling in a web-based application. This object contains

• plots of the posterior means and 95% posterior intervals of parameters in an object of class bmrm.

• tables of the posterior means of parameters in an object of class bmrm.

• tables of the posterior quantiles of parameters in an object of class bmrm, for prob=(0.025, 0.05, 0.25, 0.5, 0.75, 0.95, 0.975).

• tables of convergence diagnostics of parameters in an object of class bmrm.

• 3-dimensional dynamic principal component plots of data (Y) and source profiles (rows of the estimated source composition matrix P) in an object of class bmrm. The plot can be rotated by moving the cursor.

• trace plots and ACF plots of the first 6 elements of a parameter in an object of class bmrm.

Usage

bayesMRMApp(x)

Arguments

x	an object of class bmrm, the output of the bmrm function

Examples

## Not run: 
data(Elpaso); Y=Elpaso$Y ; muP=Elpaso$muP ; q=nrow(muP)
out.Elpaso <- bmrm(Y,q,muP, nAdapt=1000,nBurnIn=5000,nIter=5000,nThin=1)
bayesMRMApp(out.Elpaso)

## End(Not run)

mansukoh/bayesMRM documentation built on March 19, 2021, 3:50 p.m.