bin: Binning the Raw Data
In mixR: Finite Mixture Modeling for Raw and Binned Data

Description Usage Arguments Details Value See Also Examples

This function creates a binned data set from the raw data

1	bin(x, brks)

`x`	a numeric vector of raw data
`brks`	a numeric vector in increasing order, representing the bin values within each of which we want to calculate the frequency of the data

Given a numeric vector, the function bin creates a binned data set with bin values provided by brks. Fitting mixture models with a large data set may be slow, especially when we want to fit non-normal mixture models. Binning the data with a relatively small bin width speeds up the computation of EM algorithm while at the same time keeps the precision of the estimation result.

The function bin returns a matrix with three columns, representing the value of the left bin, the value of the right bin and the number of observations in x that falls in each bin.

reinstate

set.seed(99)
x <- rmixnormal(200, c(0.5, 0.5), c(2, 5), c(1, 1))
data <- bin(x, seq(-2, 10, 0.1))
fit1 <- mixfit(x, ncomp = 2)
fit2 <- mixfit(data, ncomp = 2)