Types of data include continuous, discrete and categoric. Classifying a variable as a particular type of data is important when considering how to present the data. Data can be presented in a ...

We propose a latent variable model for mixed discrete and continuous outcomes. The model accommodates any mixture of outcomes from an exponential family and allows for arbitrary covariate effects, as ...

Data analysis is a fundamental process in any project. However, data can be lumped into different types, with categorical and continuous data seeming almost opposed at first glance. That said ...

A considerable body of literature has arisen over the past 15 years for analyzing univariate repeated measures data. However, it is rare in applied biomedical research for interest to be restricted to ...

The primal aim of this project is to establish a new field of statistics termed discrete structural statistics by integrating discrete algorithms and classical statistics. In collaboration with three ...

A random variable that can take only a certain specified set of individual possible values-for example, the positive integers 1, 2, 3, . . . For example, stock prices are discrete random variables ...

In the future, the scientists hope to further investigate how continuous-variable quantum machine learning can be extended to replicate some of the latest results involving discrete variables.

Types of data include continuous, discrete and categoric. Classifying a variable as a particular type of data is important when considering how to present the data. Data can be presented in a ...