Update in the example of aodml

R/aodml.R

@@ -76,7 +76,7 @@ aodml <- function(formula, data, family = c("bb", "nb"),
     a <- (k - 1) * mu
     b <- (k - 1) * (1 - mu)
     if (log)
-      lbeta(a + m, b + n - m) - lbeta(a, b) + lchoose(n, m)
+      suppressWarnings(lbeta(a + m, b + n - m) - lbeta(a, b) + lchoose(n, m))
   }
 
   m.logL <- function(theta) {
@@ -98,7 +98,7 @@ aodml <- function(formula, data, family = c("bb", "nb"),
       l <- dbetabin(m = m, n = n, mu = mu, k = k, log = TRUE)
 
     if (fam == "nb")
-      l <- dnbinom(x = y, mu = mu, size = k, log = TRUE)
+      suppressWarnings(l <- dnbinom(x = y, mu = mu, size = k, log = TRUE))
 
     -sum(l)
 

man/aodml.Rd

@@ -203,7 +203,9 @@ The full parameter vector returned by \code{aodml}, say \code{param}, is equal t
 #------ Beta-binomial model
 
 data(orob2)
+
 fm1 <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb")
+names(fm1)
 
 # summaries
 fm1
@@ -255,15 +257,15 @@ fm$varparam
 
 # model with 2 phi coefficients, with the first set as constant ~ "0"
 fm <- aodml(formula = cbind(m, n - m) ~ seed * root, data = orob2,
-  family = "bb", phi.formula = ~ seed, fixpar = list(5, 1e-15))
+  family = "bb", phi.formula = ~ seed, fixpar = list(5, 1e-8))
 fm$param
 fm$varparam
 
 # model with 2 phi coefficients, with the first set as constant ~ "0",
 # and the mu intercept (1rst coef of vector b) set as as constant "-0.5"
 fm <- aodml(formula = cbind(m, n - m) ~ seed * root, data = orob2,
             family = "bb", phi.formula = ~ seed,
-            fixpar = list(c(1, 5), c(-0.5, 1e-15)))
+            fixpar = list(c(1, 5), c(-0.5, 1e-8)))
 fm$param
 fm$varparam