NBjacobianRow {RCM} | R Documentation

## A jacobian function of the NB for the row scores

### Description

A jacobian function of the NB for the row scores

### Usage

    NBjacobianRow(
      beta,
      X,
      reg,
      thetas,
      muMarg,
      k,
      n,
      p,
      rowWeights,
      nLambda,
      rMatK,
      preFabMat,
      Jac,
      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
`preFabMat` | a prefab matrix, (1+X/thetas)
`Jac` | an empty Jacobian matrix
`allowMissingness` | A boolean, are missing values present
`naId` | The numeric index of the missing values in X

### Value

a symmetric jacobian matrix of size n+k + 1

[Package RCM version 1.6.0 Index]