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hisemi (version 1.1-0)

logistic.enp: Fit a logistic curve to the raw effective number of parameters over log smoothing parameter

Description

Fit a logistic curve to the raw effective number of parameters over log smoothing parameter

Usage

logistic.enp(log.spar, enps, maximum, minimum = 2, eps = 1e-08)

Arguments

log.spar

A numeric vector of log smoothing parameters

enps

A numeric vector of raw effective number of parameters

maximum

A numeric scalar of upper bound of the effective number of parameters

minimum

A numeric scalar of lower bound of the effective enumber of parameters

eps

A small numeric scalar of error of tolerence

Value

A numeric vector of fitted effective number of parameters, with attributes

log.spar

log of smoothing parameter

rate

rate parameter of the logistic curve

mdis

the center parameter of the logistic curve

pow

the exponent parameter of the logistic curve

fit

a nonlinear least squared fit object

goodenp.idx

Indices of enps whose values are reasonably estimated

mode

The model of enps from a isotonic fit

Details

The purpose is of this function is to reduce some estimation variability of effective number of parameters. The function heuristically fit a smooth logistic curve to the raw effective number of parameters.

See Also

nls