LR_nb_Jac: A function that returns the Jacobian of the likelihood ratio

Description Usage Arguments Value

View source: R/F_LR_nb_Jac.R

Description

A function that returns the Jacobian of the likelihood ratio

Usage

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LR_nb_Jac(
  Alpha,
  X,
  CC,
  responseFun = c("linear", "quadratic", "nonparametric", "dynamic"),
  psi,
  NB_params,
  NB_params_noLab,
  d,
  alphaK,
  k,
  centMat,
  nLambda,
  nLambda1s,
  thetaMat,
  muMarg,
  n,
  ncols,
  preFabMat,
  envGradEst,
  allowMissingness,
  naId,
  ...
)

Arguments

Alpha

a vector of length d + k*(2+(k-1)/2), the environmental gradient plus the lagrangian multipliers

X

the n-by-p count matrix

CC

a n-by-d covariate vector

responseFun

a character string indicating the type of response function

psi

a scalar, an importance parameter

NB_params

Starting values for the NB_params

NB_params_noLab

Starting values for the NB_params without label

d

an integer, the number of covariate parameters

alphaK

a matrix of environmental gradients of lower dimensions

k

an integer, the current dimension

centMat

a nLambda1s-by-d centering matrix

nLambda

an integer, number of lagrangian multipliers

nLambda1s

an integer, number of centering restrictions

thetaMat

a matrix of size n-by-p with estimated dispersion parameters

muMarg

an n-by-p offset matrix

n

an integer, the number of rows of X

ncols

a scalar, the number of columns of X

preFabMat

a prefabricated matrix

envGradEst

a character string, indicating how the environmental gradient should be fitted. 'LR' using the likelihood-ratio criterion, or 'ML' a full maximum likelihood solution

allowMissingness

A boolean, are missing values present

naId

The numeric index of the missing values in X

...

Further arguments passed on to other functions

Value

A symmetric matrix, the evaluated Jacobian


RCM documentation built on Nov. 8, 2020, 5:22 p.m.

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