deriv2LagrangianFeatures {combi} | R Documentation

## The score function to estimate the latent variables

### Description

The score function to estimate the latent variables

### Usage

    deriv2LagrangianFeatures(x, data, distribution, offSet, latentVars, numVar,
      paramEstsLower, mm, Jac, meanVarTrend, weights, compositional,
      indepModel, ...)

### Arguments

`x` | parameter estimates
`data` | A list of data matrices
`distribution, compositional, meanVarTrend, offSet, numVar` | Characteristics of the view
`latentVars` | A vector of latent variables
`paramEstsLower` | lower dimension estimates
`mm` | the current dimension
`Jac` | a prefab jacobian
`weights` | The normalization weights
`indepModel` | the independence model
`...` | Additional arguments passed on to the score and jacobian functions

### Value

A vector of length n, the evaluation of the score functions of the latent variables

[Package combi version 0.99.15 Index]