covlmc_control {mixvlmc} | R Documentation |
Control for coVLMC fitting
Description
This function creates a list with parameters used to fine tune the coVLMC fitting algorithm.
Usage
covlmc_control(pseudo_obs = 1)
Arguments
pseudo_obs |
number of fake observations of each state to add to the observed ones. |
Details
pseudo_obs
is used to regularize the probability estimations when a
context is only observed followed by always the same state. Transition
probabilities are computed after adding pseudo_obs
pseudo observations
of each of the states (including the observed one). This corresponds to a
Bayesian posterior mean estimation with a Dirichlet prior.
Value
a list.
Examples
dts <- rep(c(0, 1), 100)
dts_cov <- data.frame(y = rep(0, length(dts)))
default_model <- covlmc(dts, dts_cov)
contexts(default_model, type = "data.frame", model = "coef")$coef
control <- covlmc_control(pseudo_obs = 10)
model <- covlmc(dts, dts_cov, control = control)
contexts(model, type = "data.frame", model = "coef")$coef
[Package mixvlmc version 0.2.1 Index]