The function DBH() defines the Discrete Burr Hatke distribution, one-parameter discrete distribution, for a gamlss.family object to be used in GAMLSS fitting using the function gamlss().
DBH(mu.link ="logit")
Arguments
mu.link: defines the mu.link, with "logit" link as the default for the mu parameter. Other links are "probit" and "cloglog"'(complementary log-log)
Returns
Returns a gamlss.family object which can be used to fit a Discrete Burr-Hatke distribution in the gamlss() function.
Details
The Discrete Burr-Hatke distribution with parameters μ has a support 0, 1, 2, ... and density given by
f(x∣μ)=(x+11−x+2μ)μx
The pmf is log-convex for all values of 0<μ<1, where f(x;μ)f(x+1;μ)
is an increasing function in x for all values of the parameter μ.
Note: in this implementation we changed the original parameters λ for μ, we did it to implement this distribution within gamlss framework.
Examples
# Example 1# Generating some random values with# known muy <- rDBH(n=1000, mu=0.74)library(gamlss)mod1 <- gamlss(y~1, family=DBH, control=gamlss.control(n.cyc=500, trace=FALSE))# Extracting the fitted values for mu# using the inverse logit functioninv_logit <-function(x) exp(x)/(1+exp(x))inv_logit(coef(mod1, parameter="mu"))# Example 2# Generating random values under some model# A function to simulate a data set with Y ~ DBHgendat <-function(n){ x1 <- runif(n) mu <- inv_logit(-3+5* x1) y <- rDBH(n=n, mu=mu) data.frame(y=y, x1=x1)}datos <- gendat(n=150)mod2 <-NULLmod2 <- gamlss(y~x1, family=DBH, data=datos, control=gamlss.control(n.cyc=500, trace=FALSE))summary(mod2)# Example 3# number of carious teeth among the four deciduous molars.# Taken from EL-MORSHEDY (2020) page 74364.y <- rep(0:4, times=c(64,17,10,6,3))mod3 <- gamlss(y~1, family=DBH, control=gamlss.control(n.cyc=500, trace=FALSE))# Extracting the fitted values for mu# using the inverse link functioninv_logit <-function(x)1/(1+ exp(-x))inv_logit(coef(mod3, what="mu"))