dNBllrow: A score function of the NB for the row scores

View source: R/F_dNBllrow.R

dNBllrowR Documentation

A score function of the NB for the row scores

Description

A score function of the NB for the row scores

Usage

dNBllrow(
  beta,
  X,
  reg,
  thetas,
  muMarg,
  k,
  n,
  p,
  rowWeights,
  nLambda,
  rMatK,
  allowMissingness,
  naId,
  ...
)

Arguments

beta

a vector of of length n + k +1 regression parameters to optimize

X

the data matrix of dimensions nxp

reg

a 1xp regressor matrix: outer product of column scores and psis

thetas

nxp matrix with the dispersion parameters (converted to matrix for numeric reasons)

muMarg

an nxp offset matrix

k

a scalar, the dimension of the RC solution

n

a scalar, the number of samples

p

a scalar, the number of taxa

rowWeights

a vector of length n, the weights used for the restrictions

nLambda

an integer, the number of lagrangian multipliers

rMatK

the lower dimension row scores

allowMissingness

A boolean, are missing values present

naId

The numeric index of the missing values in X

...

Other arguments passed on to the jacobian

Value

A vector of length n + k +1 with evaluations of the derivative of the lagrangian


CenterForStatistics-UGent/RCM documentation built on April 24, 2023, 8:26 p.m.