EM.starting.point {CNVtools} | R Documentation

## Randomly assigns a starting point for the EM algorithm

### Description

This function should be invisible to most users, and is part of our the fitting routine using the EM algorithm. Our maximum likelihood procedure uses an iterative algorithm called Expectation-Maximization. This requires a starting point, chosen at random. EM.starting point randomly assigns this starting point.

### Usage

    EM.starting.point(d, trait = "binary")

### Arguments

`d` | The dataframe that needs to be initialized
`trait` | Can be either “binary” or ”eQTL”

### Value

Returns the input data frame with reasonable random starting values.

### Author(s)

Vincent Plagnol vincent.plagnol@cimr.cam.ac.uk and Chris Barnes christopher.barnes@imperial.ac.uk

### References

A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Royal Stat. Soc., vol. 39, pp. 1–38, 1977.

[Package CNVtools version 1.74.0 Index]