deriv2LagrangianFeatures {combi} | R Documentation |
The score function to estimate the latent variables
deriv2LagrangianFeatures(x, data, distribution, offSet, latentVars, numVar, paramEstsLower, mm, Jac, meanVarTrend, weights, compositional, indepModel, ...)
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 |
A vector of length n, the evaluation of the score functions of the latent variables