R: Create the Control Parameters for the EM Computation of...

haplo.em.control {haplo.stats} | R Documentation

## Create the Control Parameters for the EM Computation of Haplotype Probabilities, with Progressive Insertion of Loci

### Description

Create a list of parameters that control the EM algorithm for estimating haplotype frequencies, based on progressive insertion of loci. Non-default parameters for the EM algorithm can be set as parameters passed to haplo.em.control.

### Usage

    haplo.em.control(loci.insert.order=NULL, insert.batch.size = 6,
                                 min.posterior = 1e-09, tol = 1e-05,
                                 max.iter=5000, random.start=0, n.try = 10,
                                 iseed=NULL, max.haps.limit=2e6, verbose=0)

### Arguments

`loci.insert.order` | Numeric vector with specific order to insert the loci. If this value is NULL, the insert order will be in sequential order (1, 2, ..., No. Loci).
`insert.batch.size` | Number of loci to be inserted in a single batch.
`min.posterior` | Minimum posterior probability of a haplotype pair, conditional on observed marker genotypes. Posteriors below this minimum value will have their pair of haplotypes "trimmed" off the list of possible pairs. If all markers in low LD, we recommend using the default. If markers have at least moderate LD, can increase this value to use less memory.
`tol` | If the change in log-likelihood value between EM steps is less than the tolerance (tol), it has converged.
`max.iter` | Maximum number of iterations allowed for the EM algorithm before it stops and prints an error. If the error is printed, double max.iter.
`random.start` | If random.start = 0, then the inititial starting values of the posteriors for the first EM attempt will be based on assuming equal posterior probabilities (conditional on genotypes). If random.start = 1, then the initial starting values of the first EM attempt will be based on assuming a uniform distribution for the initial posterior probabilities.
`n.try` | Number of times to try to maximize the lnlike by the EM algorithm. The first try uses, as initial starting values for the posteriors, either equal values or uniform random variables, as determined by random.start. All subsequent tries will use random uniform values as initial starting values for the posterior probabilities.
`iseed` | An integer or a saved copy of .Random.seed. This allows simulations to be reproduced by using the same initial seed.
`max.haps.limit` | Maximum number of haplotypes for the input genotypes. It is used as the amount of memory to allocate in C for the progressive-insertion E-M steps. Within haplo.em, the first step is to try to allocate the sum of the result of geno.count.pairs(), if that exceeds max.haps.limit, start by allocating max.haps.limit. If that is exceeded in the progressive-insertions steps, the C function doubles the memory until it can no longer request more.
`verbose` | Logical, if TRUE, print procedural messages to the screen. If FALSE, do not print any messages.

### Details

The default is to use n.try = 10. If this takes too much time, it may be worthwhile to decrease n.try. Other tips for computing haplotype frequencies for a large number of loci, particularly if some have many alleles, is to decrease the batch size (insert.batch.size), increase the memory (max.haps.limit), and increase the probability of trimming off rare haplotypes at each insertion step (min.posterior).

### Value

A list of the parameters passed to the function.

### See Also

`haplo.em`, `haplo.score`

### Examples

    # This is how it is used within haplo.score
    #    > score.gauss <- haplo.score(resp, geno, trait.type="gaussian",
    #    >           em.control=haplo.em.control(insert.batch.size = 2, n.try=1))

[Package haplo.stats version 1.7.9 Index]