mapfit.point: MAP fitting with point data

In mapfit: PH/MAP Parameter Estimation

MAP fitting with point data

Description

Estimates MAP parameters from point data.

Usage

mapfit.point(map, x, intervals, ...)

Arguments

map	An object for MAP. The estimation algorithm is selected depending on this class.
x	A vector for point data.
intervals	A vector for intervals.
...	Further options for fitting methods.

Value

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

model	an object for estimated PH class.
llf	a value of the maximum log-likelihood.
df	a value of degrees of freedom of the model.
aic	a value of Akaike information criterion.
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 used for fitting.
call	the matched call.

Examples

## load trace data
data(BCpAug89)
BCpAug89s <- head(BCpAug89, 50)

## MAP fitting for general MAP
(result1 <- mapfit.point(map=map(2), x=cumsum(BCpAug89s)))

## MAP fitting for MMPP
(result2 <- mapfit.point(map=mmpp(2), x=cumsum(BCpAug89s)))

## MAP fitting for ER-HMM
(result3 <- mapfit.point(map=erhmm(3), x=cumsum(BCpAug89s)))

## marginal moments for estimated MAP
map.mmoment(k=3, map=result1$model)
map.mmoment(k=3, map=result2$model)
map.mmoment(k=3, map=result3$model)

## joint moments for estimated MAP
map.jmoment(lag=1, map=result1$model)
map.jmoment(lag=1, map=result2$model)
map.jmoment(lag=1, map=result3$model)

## lag-k correlation
map.acf(map=result1$model)
map.acf(map=result2$model)
map.acf(map=result3$model)

mapfit documentation built on Nov. 22, 2022, 5:05 p.m.