mapfit (version 1.0.0)

phfit.density: PH fitting with density function

Description

Estimates PH parameters from density function.

Usage

phfit.density(
  ph,
  f,
  deformula = deformula.zeroinf,
  weight.zero = 1e-12,
  weight.reltol = 1e-08,
  start.divisions = 8,
  max.iter = 12,
  ...
)

Value

Returns a list with components, which is an object of S3 class phfit.result;

model

an object for estimated PH class.

llf

a value of the maximum log-likelihood (a negative value of the cross entropy).

df

a value of degrees of freedom of the model.

KL

a value of Kullback-Leibler divergence.

iter

the number of iterations.

convergence

a logical value for the convergence of estimation algorithm.

ctime

computation time (user time).

data

an object for data class

aerror

a value of absolute error for llf at the last step of algorithm.

rerror

a value of relative error for llf at the last step of algorithm.

options

a list of options.

call

the matched call.

Arguments

ph

An object of R6 class. The estimation algorithm is selected depending on this class.

f

A function object for a density function.

deformula

An object for formulas of numerical integration. It is not necessary to change it when the density function is defined on the positive domain [0,infinity).

weight.zero

A absolute value which is regarded as zero in numerical integration.

weight.reltol

A value for precision of numerical integration.

start.divisions

A value for starting value of divisions in deformula.

max.iter

A value for the maximum number of iterations to increase divisions in deformula.

...

Options for EM steps, which is also used to send the arguments to density function.

Examples

####################
##### truncated density
####################

## PH fitting for general PH
(result1 <- phfit.density(ph=ph(2), f=dnorm, mean=3, sd=1))

## PH fitting for CF1
(result2 <- phfit.density(ph=cf1(2), f=dnorm, mean=3, sd=1))

## PH fitting for hyper Erlang
(result3 <- phfit.density(ph=herlang(3), f=dnorm, mean=3, sd=1))

## mean
ph.mean(result1$model)
ph.mean(result2$model)
ph.mean(result3$model)

## variance
ph.var(result1$model)
ph.var(result2$model)
ph.var(result3$model)

## up to 5 moments 
ph.moment(5, result1$model)
ph.moment(5, result2$model)
ph.moment(5, result3$model)