Control for coVLMC fitting — covlmc

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.

Value

a list.

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.

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")$coef
#> [[1]]
#> [1] 4.615121
#> 
#> [[2]]
#> [1] -4.60517
#> 
control <- covlmc_control(pseudo_obs = 10)
model <- covlmc(dts, dts_cov, control = control)
contexts(model, type = "data.frame", model = "coef")$coef
#> [[1]]
#> [1] 2.397895
#> 
#> [[2]]
#> [1] -2.388763
#>