.EMControl {phyclust} | R Documentation

## EM Control Generator

### Description

Generate an EM control (`.EMC`) controlling the options, methods, conditions and models of EM algorithms. As `.EMC`, this function generate a default template. One can either modify `.EMC` or employ this function to control EM algorithms.

### Usage

    .EMControl(exhaust.iter = 1, fixed.iter = 5,
        short.iter = 100, EM.iter = 1000,
        short.eps = 1e-2, EM.eps = 1e-6,
        cm.reltol = 1e-8, cm.maxit = 5000,
        nm.abstol.Mu.given.QA = 1e-8, nm.reltol.Mu.given.QA = 1e-8,
        nm.maxit.Mu.given.QA = 500,
        nm.abstol.QA.given.Mu = 1e-8, nm.reltol.QA.given.Mu = 1e-8,
        nm.maxit.QA.given.Mu = 5000,
        est.non.seg.site = FALSE, max.init.iter = 50,
        init.procedure = .init.procedure[1],
        init.method = .init.method[1],
        substitution.model = .substitution.model$model[1],
        edist.model = .edist.model[1], identifier = .identifier[1],
        code.type = .code.type[1], em.method = .em.method[1],
        boundary.method = .boundary.method[1], min.n.class = 1,
        se.type = FALSE, se.model = .se.model[1], se.constant = 1e-2)

### Arguments

`exhaust.iter` | number of iterations for "exhaustEM", default = 1.
`fixed.iter` | number of iterations for "RndpEM", default = 5.
`short.iter` | number of short-EM steps, default = 100.
`EM.iter` | number of long-EM steps, default = 1000.
`short.eps` | tolerance of short-EM steps, default = 1e-2.
`EM.eps` | tolerance of long-EM steps, default = 1e-6.
`cm.reltol` | relative tolerance for a CM step, default = 1e-8
`cm.maxit` | maximum number iteration for a CM step, default = 5000.
`nm.abstol.Mu.given.QA` | see ‘Details’, default = 1e-8
`nm.reltol.Mu.given.QA` | see ‘Details’, default = 1e-8
`nm.maxit.Mu.given.QA` | see ‘Details’, default = 500.
`nm.abstol.QA.given.Mu` | see ‘Details’, default = 1e-8
`nm.reltol.QA.given.Mu` | see ‘Details’, default = 1e-8
`nm.maxit.QA.given.Mu` | see ‘Details’, default = 5000.
`est.non.seg.site` | estimate non-segregation sites, default = FALSE.
`max.init.iter` | maximum number of initialization iteration, default = 50.
`init.procedure` | initialization procedure, default = "exhaustEM".
`init.method` | initialization method, default = "randomMu".
`substitution.model` | substitution model, default = "JC69".
`edist.model` | evolution distance, default = "D\_J69".
`identifier` | identifier, default = "EE".
`code.type` | code type, default = "NUCLEOTIDE".
`em.method` | EM method, default = "EM".
`boundary.method` | boundary method, default = `ADJUST`.
`min.n.class` | minimum number of sequences in a cluster, default = 1.
`se.type` | sequencing error type, default = FALSE.
`se.model` | sequencing error model, default = "CONVOLUTION".
`se.constant` | constrained constant, default = 1e-2.

### Details

`exhaust.iter`, `fixed.iter`, `short.iter`, and `short.eps` are used to control the iterations of initialization procedures and methods.

`EM.iter` and `EM.eps` are used to control the EM iterations.

`cm.reltol` and `cm.maxit` are used to control the ECM iterations.

Arguments starting with `nm.` are options for the Nelder-Mead method as in `optim`. The C codes of Nelder-Mead are modified from the R math library and the options are all followed. `abstol` and `reltol` are for absolute and relative tolerances. `Mu.given.QA` is for maximizing the profile function of mu_k given Q_k, and `QA.given.Mu` is for maximizing the profile function of Q_k given mu_k.

`est.non.seg.site` indicates whether to estimate the states of center sequences. If FALSE, the states will be fixed as the non segregating sites. Usually, there is no need to estimate.

`max.init.iter` is for certain initialization methods, e.g. `randomNJ` and `K-Medoids` need few tries to obtain an appropriate initial state.

`init.procedure` and `init.method` are for initializations.

`min.n.class` is the minimum number of sequences in a cluster to avoid bad initialization state and degenerated clusters.

`se.type`, `se.model`, and `se.constant` which are used only for sequencing error models and only for nucleotide data without labels.

### Value

This function returns a list as `.EMC`.

The sequencing error controls are stored in `se.type`, `se.model`, and `se.constant`, for sequencing error type, model, and constrained constant of errors, respectively.

### Author(s)

Wei-Chen Chen wccsnow@gmail.com

### References

Phylogenetic Clustering Website: https://snoweye.github.io/phyclust/

### See Also

`.show.option`, `.EMC`, `.boundary.method`, `.code.type`, `.edist.model`, `.em.method`, `.identifier`, `.init.method`, `.init.procedure`, `.substitution.model`, `optim`, `phyclust`, `phyclust.se`.

### Examples

    ## Not run:
    library(phyclust, quiet = TRUE)

    # The same as .EMC
    .EMControl()

    # Except code.type, all others are the same as .EMC
    .EMControl(code.type = "SNP")
    .EMControl(code.type = .code.type[2])

    ## End(Not run)

[Package phyclust version 0.1-25 Index]