estimate.expmodel: Estimate Exponential-based model 'expmodel'

In dsdp: Density Estimation with Semidefinite Programming

Estimate Exponential-based model expmodel

Description

Estimates Exponential-based model expmodel among parameter vectors, deglist, lmdlist. Then it sorts the results by AIC.

Usage

## S3 method for class 'expmodel'
estimate(
  model,
  deglist = deglist,
  lmdlist = lmdlist,
  recompute = FALSE,
  stepsize = NULL,
  verbose = FALSE,
  ...
)

Arguments

model	An object of expmodel class.
deglist	A vector of degrees of polynomials. The element should be positive integers.
lmdlist	A vector of rate parameters of Exponential-based models. The element should be larger than 0.
recompute	If TRUE, recomputes the results for better estimation and accuracy. Parameters whose accuracies had been already attained sufficiently, namely around 1.0e-6, are not included in candidates for recomputing.
stepsize	A vector in descending order whose values are between 0 and 1. If a small step size is supplied, it can attain successful estimates, but it might take more iterations.
verbose	If TRUE, it shows the detailed message of SDP solver.
...	Arguments to be passed to or from other methods.

Value

A expmodel object including the estimates. Those estimates are stored in model$result with data.frame format and model$coeffs in list format.

See Also

expmodel() summary.expmodel() plot.expmodel()

Examples

## Create an expmodel object
emodel <- expmodel(mixexpgamma$n200)
## Estimate a model with parameters
emodel <- estimate(emodel, deglist=c(4,5), lmdlist=c(0.5, 1, 2))

dsdp documentation built on Feb. 16, 2023, 8:36 p.m.