Logistic model of a COVLMC context

This function returns a representation of the logistic model associated to a COVLMC context from its node in the associated context tree.

Usage

model(node, type = c("coef", "full"))

Arguments

node: A ctx_node_covlmc object as returned by find_sequence() or contexts.covlmc()
type: specifies the model information to return, either the coefficients only (type="coef" default case) or the full model object (type="full")

Value

if node is a context, the coefficients of the logistic model (as a vector or a matrix depending on the size of the state space) or a logistic model as a R object. If node is not a context, NULL.

Details

Full model extraction is only possible if the COVLMC model what not fully trimmed (see trim.covlmc()). Notice that find_sequence.covlmc() can produce node that are not context: in this case this function return NULL.

Examples

pc <- powerconsumption[powerconsumption$week == 5, ]
dts <- cut(pc$active_power, breaks = c(0, quantile(pc$active_power, probs = c(0.5, 1))))
dts_cov <- data.frame(day_night = (pc$hour >= 7 & pc$hour <= 17))
m_cov <- covlmc(dts, dts_cov, min_size = 10)
vals <- states(m_cov)
node <- find_sequence(m_cov, c(vals[1], vals[1]))
node
#> Context [T]: (0,1.34], (0,1.34] 
#>  followed by (0,1.34] (433), (1.34,7.54] (32)
model(node)
#>     (Intercept) day_night_1TRUE day_night_2TRUE 
#>       -2.759353        2.784578       -2.524973 
model(node, type = "full")
#> 
#> Call:  stats::glm(formula = target ~ ., family = stats::binomial(), 
#>     data = mm, control = stats::glm.control(maxit = options()[["mixvlmc.maxit"]]), 
#>     model = FALSE, x = FALSE, y = FALSE)
#> 
#> Coefficients:
#>     (Intercept)  day_night_1TRUE  day_night_2TRUE  
#>          -2.759            2.785           -2.525  
#> 
#> Degrees of Freedom: 464 Total (i.e. Null);  462 Residual
#> Null Deviance:	    233 
#> Residual Deviance: 226.4 	AIC: 232.4