# mleATD: Maximum likelihood estimation (MLE) for the quantile-based... In QBAsyDist: Asymmetric Distributions and Quantile Estimation

## Description

The log-likelihood function \ell_n(μ,φ,α,ν)=\ln[L_n(μ,φ,α,ν)] and parameter estimation of θ=(μ,φ,α,ν) in the quantile-based asymmetric Student's-t distribution. by using the maximum likelihood estimation are discussed in Gijbels et al. (2019a).

## Usage

 1 mleATD(y) 

## Arguments

 y This is a vector of quantiles.

## Value

The maximum likelihood estimate of parameter θ=(μ,φ,α,ν) of the quantile-based asymmetric Student's-t distribution.

## References

Gijbels, I., Karim, R. and Verhasselt, A. (2019a). On quantile-based asymmetric family of distributions: properties and inference. International Statistical Review, https://doi.org/10.1111/insr.12324.

## Examples

 1 2 3 # Example y=rnorm(20) mleATD(y) 

QBAsyDist documentation built on Sept. 4, 2019, 1:05 a.m.