These functions are called by EmSkew.contours,EmSkew.filter and EmSkew.flow to plot the contours of (skew) mixture density after fitting to the data.
conplot(x, y, pro, mu, sigma, dof, delta, distr, grid = 300,
nrand = 6000, levels = seq(5, 95, by = 20), col = "white")
conplot2(x, y, pro, mu, sigma, dof, delta, distr, grid = 300,
nrand = 6000, levels = seq(5, 95, by = 20))
conplot3(x, y, pro, mu, sigma, dof, delta, modpts,distr, grid =300,
nrand = 10000, levels = seq(5, 95, by = 20))
mypanel2(x,y,...)
mypanel3(x,y,...)
mypanel4(x,y,...)
panel.density(x, col=1,...)A vector of observations on variable x.
A vector of observations on variable y.
A vector of mixing proportions in the (skew) mixture model.
A matrix with each column corresponding to the mean or location vector of one mixture component.
An array of covariance matrices for each component of the mixture distribution.
A vector of degrees of freedom when "distr"ibution is "mvt" or "mst".
A matrix with each column as skew parameter vector of one component when "distr"ibution is "msn" or "mst".
A three letter string indicating component distribution, "mvn"=normal distribution, "mvt"=t-distribution,"msn"=skew normal distribution, "mst"=skew t-ditribution.
The mode points.
An integer for the number of grid points in one direction.
A large integer for the number of random numbers being drawn.
A vector of contour percentage levels for the plots. It should be in the range of 0 to 100.
The colour of contour lines.
other
In most case, users do not call this function directly, instead they call the function emmix.flow.