dpmixsim (version 0.0-9)

postdataseg: Data segmentation

Description

postdataseg performs data segmentation based on labelled cluster estimates.

Usage

postdataseg(x, z, ngrid, dbg=FALSE)

Arguments

x

full-sized scaled image data prepared by premask

z

cluster labels produced by postdpmixciz

ngrid

dimension of the grid used in estimation

dbg

logical variable to show debugging output (default = FALSE)

Value

cx

vector of image cluster values

Details

Once the distributions of the indicator variables \(z_i\) are calculated we can separate the components of the mixture. Individual components are selected according to the most probable \(z_i\) value in a given region of the distributional space, leading to a partition of this space into regions. Intensity threshold values are associated with the partition of the distributional space to drive the image segmentation. In brief, the partition of the distributional space induced by the \(z\) values is used to segment the data space. From a computational point of view, the use of these two separate spaces enables us to optimize the MCMC implementation.

See Also

dpmixsim, readsliceimg, premask, postdpmixciz

Examples

# NOT RUN {
## see Example 2 in dpmixsim.
# }