em.twocomp.m3 {bimixt} R Documentation

## em.twocomp.m3

### Description

Expectation maximization (EM) algorithm for estimating two-component Gaussian mixtures with different mixture proportions for cases and controls (two component unconstrained model). This is used as an internal method and is called from `bc.twocomp`.

### Usage

```em.twocomp.m3(x.all, case.indicator, max.iters = 1000, errtol = 1e-09,

control.comp = 1, start.vals=NULL)
```

### Arguments

 `x.all` vector of cases and controls `case.indicator` a vector of equal length to x.all with 1's in the case positions and 0's in the control positions `max.iters` the maximum number of iterations to run `errtol` Error tolerance level. Approximates convergence of the maximum log likelihood value. `control.comp` indicator of which component contains the controls (1 or 2) `start.vals` starting values for the EM algorithm. If `NA`, the starting values are estimated from the data.

### Value

 `max.loglike` the maximum log likelihood value for the algorithm `mu` estimated means for each component `sig` estimated standard deviations for each component `pi.cs` estimated proportion of cases in each component `pi.ctrl` estimated proportion of controls in each component `n.iters` the number of iterations the algorithm took to converge `control.comp` indicator of which component contains the controls (1 or 2)

### Author(s)

Michelle Winerip, Garrick Wallstrom, Joshua LaBaer

### References

Dempster, Arthur P., Nan M. Laird, and Donald B. Rubin. "Maximum likelihood from incomplete data via the EM algorithm." Journal of the royal statistical society. Series B (methodological) (1977): 1-38.

`bc.binorm` `bc.twocomp` `bc.fourcomp` `em.twocomp.m1` `em.twocomp.m2`