R: One M-Step of phyclust

phyclust.m.step {phyclust} | R Documentation

## One M-Step of phyclust

### Description

This is a single M-step of `phyclust`, usually following or followed by the other E-step.

### Usage

    phyclust.m.step(X, ret.phyclust = NULL, K = NULL,
        pi = NULL, kappa = NULL, Tt = NULL, Z.normalized = NULL,
        substitution.model = NULL, identifier = NULL, code.type = NULL,
        label = NULL)

### Arguments

`X` | nid/sid matrix with N rows/sequences and L columns/sites.
`ret.phyclust` | an object with the class `phyclust`.
`K` | number of clusters.
`pi` | equilibrium probabilities, each row sums to 1.
`kappa` | transition and transversion bias.
`Tt` | total evolution time, t.
`Z.normalized` | posterior probabilities obtained from an E-step.
`substitution.model` | substitution model.
`identifier` | identifier.
`code.type` | code type.
`label` | label of sequences for semi-supervised clustering.

### Details

`X` should be a numerical matrix containing sequence data that can be transfered by `code2nid` or `code2sid`.

Either input `ret.phyclust` or all other arguments for this function. `ret.phyclust` can be obtained either from an EM iteration of `phyclust` or from a E step of `phyclust.e.step`.

If `label` is inputted, the label information will be used the M-step and `Z.normalized` will be replaced, even the `ret.phyclust` is the result of unsupervised clustering.

### Value

This function returns an object with class `phyclust`.

### Author(s)

Wei-Chen Chen wccsnow@gmail.com

### References

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

### See Also

`phyclust`, `phyclust.em.step`, `phyclust.e.step`.

### Examples

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

    set.seed(1234)
    EMC.1 <- .EMC
    EMC.1$short.iter <- 1
    EMC.1$EM.iter <- 1

    # Test with phyclust.
    X <- seq.data.toy$org
    ret.1 <- phyclust(X, 2, EMC = EMC.1)

    # Test with an em step.
    ret.em <- phyclust.em.step(X, ret.1)

    # Test with an E- and M-step.
    ret.1$Z.normalized <- phyclust.e.step(X, ret.phyclust = ret.1)
    ret.m <- phyclust.m.step(X, ret.phyclust = ret.1)

    # Test with 2 em steps.
    set.seed(1234)
    EMC.2 <- EMC.1
    EMC.2$EM.iter <- 2
    ret.2 <- phyclust(X, 2, EMC = EMC.2)

    # Check logL.
    phyclust.logL(X, ret.1)
    phyclust.logL(X, ret.em)
    phyclust.logL(X, ret.m)
    phyclust.logL(X, ret.2)

    # For semi-supervised.
    semi.label <- rep(0, nrow(X))
    semi.label[1:3] <- 1
    ret.m.1 <- phyclust.m.step(X, ret.phyclust = ret.1, label = semi.label)

    ## End(Not run)

[Package phyclust version 0.1-30 Index]