Count regression models maintain a steadfast presence in modern applied statistics as
highlighted by their usage in diverse areas like biometry, ecology, and insurance. However …

The prequel to this review provided an extensive treatment of classic zero‐inflated count
regression models where a univariate discrete distribution is used for the count regression …

In the era of big data, researchers interested in developing statistical models are challenged
with how to achieve parsimony. Usually, some sort of dimension reduction strategy is …

Decision tree ensembles are widely used and competitive learning models. Despite their
success, popular toolkits for learning tree ensembles have limited modeling capabilities. For …

Grouped and right-censored (GRC) counts are widely used in criminology, demography,
epidemiology, marketing, sociology, psychology and other related disciplines to study …

While excess zeros are often thought to cause data over-dispersion (ie when the variance
exceeds the mean), this implication is not absolute. One should instead consider a flexible …

Social mixing is one of the key objectives of the housing policy in OECD countries. The Low-
Income Housing Tax Credit (LIHTC) program, the largest affordable housing construction …

The analysis of traffic accident data is crucial to address numerous concerns, such as
understanding contributing factors in an accident's chain-of-events, identifying hotspots, and …

When the observed proportion of zeros in a data set consisting of binary outcome data is
larger than expected under a regular logistic regression model, it is frequently suggested to …

Multivariate areal data are common in many disciplines. When fitting spatial regressions for
such data, one needs to account for dependence (both among and within areal units) to …