The zero-adjusted log-symmetric quantile regression model applied to
extramarital affairs data
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abstract
In this work, we propose a zero-adjusted log-symmetric quantile regression
model. Initially, we introduce zero-adjusted log-symmetric distributions, which
allow for the accommodation of zeros. The estimation of the parameters is
approached by the maximum likelihood method and a Monte Carlo simulation is
performed to evaluate the estimates. Finally, we illustrate the proposed
methodology with the use of a real extramarital affairs data set.
