R: Poisson lognormal model towards Principal Component Analysis

PLNPCA {PLNmodels} | R Documentation

## Poisson lognormal model towards Principal Component Analysis

### Description

Fit the PCA variants of the Poisson lognormal with a variational algorithm. Use the (g)lm syntax for model specification (covariates, offsets).

### Usage

    PLNPCA(
      formula,
      data,
      subset,
      weights,
      ranks = 1:5,
      control_init = list(),
      control_main = list()
    )

### Arguments

`formula` | an object of class "formula": a symbolic description of the model to be fitted.
`data` | an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lm is called.
`subset` | an optional vector specifying a subset of observations to be used in the fitting process.
`weights` | an optional vector of observation weights to be used in the fitting process.
`ranks` | a vector of integer containing the successive ranks (or number of axes to be considered)
`control_init` | a list for controlling the optimization at initialization. See details of function `PLN()`.
`control_main` | a list for controlling the main optimization process. See details.

### Details

The list of parameters `control_main` controls the optimization of the main process, with the following entries:

- "ftol_rel" stop when an optimization step changes the objective function by less than ftol multiplied by the absolute value of the parameter. Default is 1e-8

- "ftol_abs" stop when an optimization step changes the objective function by less than ftol multiplied by the absolute value of the parameter. Default is 0

- "xtol_rel" stop when an optimization step changes every parameters by less than xtol multiplied by the absolute value of the parameter. Default is 1e-4

- "xtol_abs" stop when an optimization step changes every parameters by less than xtol multiplied by the absolute value of the parameter. Default is 0

- "maxeval" stop when the number of iteration exceeds maxeval. Default is 10000

- "maxtime" stop when the optimization time (in seconds) exceeds maxtime. Default is -1 (no restriction)

- "algorithm" the optimization method used by NLOPT among LD type, i.e. "CCSAQ", "MMA", "LBFGS", "VAR1", "VAR2". See NLOPT documentation for further details. Default is "CCSAQ".

- "trace" integer for verbosity.

### Value

an R6 object with class `PLNPCAfamily`, which contains a collection of models with class `PLNPCAfit`

### See Also

The classes `PLNPCAfamily` and `PLNPCAfit`

### Examples

    #' ## Use future to dispatch the computations on 2 workers
    ## Not run:
    future::plan("multisession", workers = 2)

    ## End(Not run)

    data(trichoptera)
    trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
    myPCA <- PLNPCA(Abundance ~ 1 + offset(log(Offset)), data = trichoptera, ranks = 1:5)

    # Shut down parallel workers
    ## Not run:
    future::plan("sequential")

    ## End(Not run)

[Package PLNmodels version 0.11.4 Index]