A new discrete two-parameter distribution is introduced by discretizing a generalized half-normal distribution. The model is useful for fitting overdispersed as well as underdispersed data. The failure function can be decreasing, bathtub shaped or increasing. A reparameterization of the distribution is introduced for use in a regression model based on the median. The behaviour of the maximum likelihood estimates is studied numerically, showing good performance in finite samples. Three real data set applications reveal that the new model can provide a better explanation than some other competitors
Sample quantiles for discrete distributions The classical definition of sample quantiles and their a...
In this paper, we develop two fully parametric quantile regression models, based on the power Johnso...
This article develops a two-part finite mixture quantile regression model for semi-continuous longit...
A new discrete two-parameter distribution is introduced by discretizing a generalized half-normal di...
In this paper, we propose and derive a new regression model for response variables defined on the op...
We develop quantile regression methods for discrete responses by extending Parzen’s definition of ma...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
We explore a particular fully parametric approach to quantile regression and show that this approach...
We explore a particular fully parametric approach to quantile regression and show that this approach...
Quantile regression is a class of methods voted to the modelling of conditional quantiles. In a Bay...
In this paper, we will present a new, more flexible class of distributions with a domain in the inte...
In this paper, we develop two fully parametric quantile regression models, based on the power Johnso...
Sample quantiles for discrete distributions The classical definition of sample quantiles and their a...
In this paper, we develop two fully parametric quantile regression models, based on the power Johnso...
This article develops a two-part finite mixture quantile regression model for semi-continuous longit...
A new discrete two-parameter distribution is introduced by discretizing a generalized half-normal di...
In this paper, we propose and derive a new regression model for response variables defined on the op...
We develop quantile regression methods for discrete responses by extending Parzen’s definition of ma...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
: We develop quantile regression methods for discrete responses by extending Parzen's definition of ...
We explore a particular fully parametric approach to quantile regression and show that this approach...
We explore a particular fully parametric approach to quantile regression and show that this approach...
Quantile regression is a class of methods voted to the modelling of conditional quantiles. In a Bay...
In this paper, we will present a new, more flexible class of distributions with a domain in the inte...
In this paper, we develop two fully parametric quantile regression models, based on the power Johnso...
Sample quantiles for discrete distributions The classical definition of sample quantiles and their a...
In this paper, we develop two fully parametric quantile regression models, based on the power Johnso...
This article develops a two-part finite mixture quantile regression model for semi-continuous longit...