BIC: Bayesian Information Criteria for for 'VLMCX' objects that...
In VLMCX: Variable Length Markov Chain with Exogenous Covariates
BIC R Documentation
Bayesian Information Criteria for for VLMCX objects that compose Variable Length Markov Chains with Exogenous Covariates
Description
Computes the Bayesian Information Criteria for the data using the estimated parameters of the multinomial logistic regression in the VLMCX fit.
Usage
BIC(fit)
Arguments
fit
a betaVLMC object.
Value
a numeric value with the corresponding BIC.
Author(s)
Adriano Zanin Zambom <adriano.zambom@csun.edu>
Examples
set.seed(1)
n = 1000
d = 2
X = cbind(rnorm(n), rnorm(n))
p = 1/(1 + exp(0.5 + -2*X[,1] - 3.5*X[,2]))
y = c(sample(1:0,1), rbinom(n,1, p))
fit = maximum.context(y[1:n], X, max.depth = 3, n.min = 25)
draw(fit)
BIC(fit)
##[1] 696.0343
fit = VLMCX(y[1:n], X, alpha.level = 0.001, max.depth = 3, n.min = 25)
draw(fit)
BIC(fit)
##[1] 588.9432
VLMCX documentation built on May 29, 2024, 11:04 a.m.
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| BIC | R Documentation |
Bayesian Information Criteria for for VLMCX objects that compose Variable Length Markov Chains with Exogenous Covariates
Description
Computes the Bayesian Information Criteria for the data using the estimated parameters of the multinomial logistic regression in the VLMCX fit.
Usage
BIC(fit)
Arguments
fit |
a betaVLMC object. |
Value
a numeric value with the corresponding BIC.
Author(s)
Adriano Zanin Zambom <adriano.zambom@csun.edu>
Examples
set.seed(1)
n = 1000
d = 2
X = cbind(rnorm(n), rnorm(n))
p = 1/(1 + exp(0.5 + -2*X[,1] - 3.5*X[,2]))
y = c(sample(1:0,1), rbinom(n,1, p))
fit = maximum.context(y[1:n], X, max.depth = 3, n.min = 25)
draw(fit)
BIC(fit)
##[1] 696.0343
fit = VLMCX(y[1:n], X, alpha.level = 0.001, max.depth = 3, n.min = 25)
draw(fit)
BIC(fit)
##[1] 588.9432
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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