MoE-dph-method: MoE method for dph Class

In matrixdist: Statistics for Matrix Distributions

MoE method for dph Class

Description

MoE method for dph Class

Usage

## S4 method for signature 'dph'
MoE(
  x,
  formula,
  data,
  alpha_vecs = NULL,
  weight = numeric(0),
  stepsEM = 1000,
  every = 10,
  rand_init = TRUE,
  maxWts = 1000
)

Arguments

x	An object of class dph.
formula	A regression formula.
data	A data frame.
alpha_vecs	Matrix of initial probabilities.
weight	Vector of weights.
stepsEM	Number of EM steps to be performed.
every	Number of iterations between likelihood display updates.
rand_init	Random initiation in the R-step.
maxWts	Maximal number of weights in the nnet function.

Value

An object of class sph.

Examples

x <- dph(structure = "general")
n <- 100
responses <- rpois(n, 3) + 1
covariate <- data.frame(age = sample(18:65, n, replace = TRUE) / 100, income = runif(n, 0, 0.99))
f <- responses ~ age + income # regression formula
MoE(x = x, formula = f, y = responses, data = covariate, stepsEM = 20)

matrixdist documentation built on Aug. 8, 2023, 5:06 p.m.