Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm
Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm
Authors
Gomez, Hector J.
Gallardo, Diego, I
Santoro, Karol, I
Gallardo, Diego, I
Santoro, Karol, I
Profesor GuĆa
Authors
Date
Datos de publicaciĆ³n:
10.3390/sym13112164
SYMMETRY-BASEL,Vol.13,2021
SYMMETRY-BASEL,Vol.13,2021
Tipo de recurso
Article
Keywords
Materia geogrƔfica
Collections
Abstract
In this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.