distributionsrd (version 0.0.6)

combdist.mle: Combined distributions MLE

Description

Maximum Likelihood estimation for combined ( single, composite and finite mixture) truncated or complete distributions.

Usage

combdist.mle(
  x,
  dist,
  start = NULL,
  lower = NULL,
  upper = NULL,
  components = 1,
  nested = FALSE,
  steps = 1,
  lowertrunc = 0,
  uppertrunc = Inf,
  ...
)

Arguments

x

data vector

dist

character vector denoting the distribution(s).

start

named numeric vector holding the starting values for the coefficients.

lower, upper

Lower and upper bounds to the estimated coefficients, defaults to -Inf and Inf respectively.

components

number of components for a mixture distribution.

nested

logical indicating whether results should be returned in a nested list or a flat list form, defaults to FALSE.

steps

number of steps taken in stepflexmix, defaults to 1.

lowertrunc, uppertrunc

lowertrunc- and uppertrunc truncation points, defaults to 0 and Inf respectively

...

Additional arguments.

Value

Returns a named list containing a

dist

Character vector denoting the distributions, separated by an underscore

components

Nr. of combined distributions

prior

Weights assigned to the respective component distributions

coefficients

Named vector of coefficients

convergence

logical indicator of convergence

n

Length of the fitted data vector

np

Nr. of coefficients

Examples

# NOT RUN {
# }
# NOT RUN {
x <- rdoubleparetolognormal(1e3)
combdist.mle(x = x, dist = "doubleparetolognormal") # Double-Pareto Lognormal
combdist.mle(x = x, components = 2, dist = "lnorm", steps = 20) # FMM with 2 components
combdist.mle( x = x, dist = c("invpareto", "lnorm", "pareto"),
start = c(coeff1.k = 1, coeff2.meanlog = mean(log(x)), coeff2.sdlog = sd(log(x)), coeff3.k = 1),
lower = c(1e-10, -Inf, 1e-10, 1e-10), upper = c(Inf, Inf, Inf, Inf), nested = TRUE)
# composite distribution
# }
# NOT RUN {
# }