MoE,dph-method | R Documentation |
MoE method for dph Class
## S4 method for signature 'dph'
MoE(
x,
formula,
data,
alpha_vecs = NULL,
weight = numeric(0),
stepsEM = 1000,
every = 10,
rand_init = TRUE,
maxWts = 1000
)
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. |
An object of class sph.
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)
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