respFunScoreMat {RCM} | R Documentation

## Derivative of the Lagrangian of the parametric response function

### Description

Derivative of the Lagrangian of the parametric response function

### Usage

    respFunScoreMat(
      betas,
      X,
      reg,
      thetaMat,
      muMarg,
      psi,
      p,
      v,
      allowMissingness,
      naId,
      ...
    )

### Arguments

`betas` | a vector of length (deg+1)*(p+1) with regression parameters with deg the degree of the response function and the lagrangian multipliers
`X` | the nxp data matrix
`reg` | a matrix of regressors with the dimension nx(deg+1)
`thetaMat` | The n-by-p matrix with dispersion parameters
`muMarg` | offset matrix of size nxp
`psi` | a scalar, the importance parameter
`p` | an integer, the number of taxa
`v` | an integer, one plus the degree of the response function
`allowMissingness` | A boolean, are missing values present
`naId` | The numeric index of the missing values in X
`...` | further arguments passed on to the jacobian The parameters are restricted to be normalized, i.e. all squared intercepts, first order and second order parameters sum to 1

### Value

The evaluation of the score functions, a vector of length (p+1)* (deg+1)

[Package RCM version 1.6.0 Index]