fitConstModel {ImpulseDE2}R Documentation

Fit a constant model to data of a gene

Description

[Model fitting function hierarchy: 4 out of 4] This quarterny fitting wrapper performs constant model fitting: This function executes numerical optimisaiton and error-handling thereof.

Usage

fitConstModel(vecCounts, scaDisp, vecSizeFactors, lsvecidxBatch, MAXIT = 1000,
  RELTOL = 10^(-8), trace = 0, REPORT = 10)

Arguments

vecCounts

(numeric vector number of samples) Read count data.

scaDisp

(scalar) Gene-wise negative binomial dispersion hyper-parameter.

vecSizeFactors

(numeric vector number of samples) Model scaling factors for each sample which take sequencing depth into account (size factors).

lsvecidxBatch

(list length number of confounding variables) List of index vectors. One vector per confounding variable. Each vector has one entry per sample with the index batch within the given confounding variable of the given sample. Batches are enumerated from 1 to number of batches.

MAXIT

(scalar) [Default 1000] Maximum number of BFGS iterations for model fitting with optim.

RELTOL

(scalar) [Default 10^(-8)] Maximum relative change in loglikelihood to reach convergence in numerical optimisation by BFGS in optim.

trace

(scalar) [Defaul 0] Reporting parameter of optim.

REPORT

(scalar) [Default 10] Reporting parameter of optim.

Value

(list) List of constant fit parameters and results.

Author(s)

David Sebastian Fischer

See Also

Called by fitConstImpulseGene to fit constant model to samples of one condition and one gene. Calls constant model cost function evalLogLikMu within optim.


[Package ImpulseDE2 version 1.10.0 Index]