On the one parameter unit-Lindley distribution and its associated regression model for proportion data

By Josmar Mazucheli, André Felipe Berdusco Menezes, Subrata Chakraborty. Journal of Applied Statistics, 2018

191 citations recorded by the source corpus.

ABSTRACT In this paper considering an appropriate transformation on the Lindley distribution, we propose the unit-Lindley distribution and investigate some of its statistical properties. An important fact associated with this new distribution is that it is possible to obtain the analytical expression for bias correction of the maximum likelihood estimator. Moreover, it belongs to the exponential family. This distribution allows us to incorporate covariates directly in the mean and consequently to quantify their influences on the average of the response variable. Finally, a practical application is presented to show that our model fits much better than the Beta regression.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/aaddf202bc40ffc0352dca28497919d1efac2914

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

Some New Facts about the Unit-Rayleigh Distribution with Applications (2020, methodology): “Among the most useful unit-distributions with various number of parameters, there are the power distribution, beta distribution, Johnson distribution by [5], Topp–Leone distribution by [6], Kumaraswamy distribution by [7], unit-gamma distribution by [8,9], unit-logistic distribution by [10], simplex”