gatMLE: Fitting function for Asymmetric Student-t distribution

In dan9401/skewtDist: Asymmetric Student t-Distributions

Fitting function for Asymmetric Student-t distribution

Description

Method for fitting an gat distribution to a univariate data series by Maximum Likelihood Estimation, returns an gat object.

Usage

gatMLE(
  data,
  start_pars = c(),
  fixed_pars = c(),
  solver = c("nlminb", "nloptr", "Rsolnp"),
  solver_control = list()
)

Arguments

data	a univariate data object to be fitted
start_pars	a named numeric vector of starting parameters for the optimization algorithm, not all parameters are needed
fixed_pars	a named numeric vector of parameters to be kept fixed during the optimization routine, not all parameters are needed
solver	solver used for MLE, one of 'nlminb', 'nloptr', 'Rsolnp', default is 'nlminb'
solver_control	list of control arguments passed to the solver

Details

The gatMLE function fits an gat distribution to a univariate data series by estimating the distribution parameters through Maximum Likelihood Estimation.

For details of the list of control arguments, please refer to nlminb, nloptr::nloptr, Rsolnp::solnp

Value

A gat object(S3), the components of the object are:

data	the univariate data object for the gat distribution to be fitted
solver	the solver called
solver_control	the list of control argumetns passed to the solver called
start_pars	named numeric vector of starting parameters used
fixed_pars	named numeric vector of fixed parameters used
solver_result	output of the called solver
fitted_pars	named vector of fitted arguemnts of the gat distribution
objective	the optimal log-likelihood value obtained by the solver
time_elapsed	the time elapesed for the MLE routine
message	the message of convergence status produced by the called solver
standard_errors	standard errors of the fitted parameters

References

Baker, R. D. (2016). A new asymmetric generalisation of the t-distribution. arXiv preprint arXiv:1606.05203. \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.48550/arXiv.1606.05203")}

Examples

pars <- c(0.12, 0.6, 1.5, 1.2, 2, 5)
data <- rgat(1000, pars = pars)

fit <- gatMLE(data)
fit

dan9401/skewtDist documentation built on Jan. 6, 2025, 9:14 a.m.