The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 43, No. 3 (September/septembre 2015), pp. 337-357 (21 pages) Multivariate ordinal data are modelled as a finite ...

Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...

Nonparametric regression for functional data provides a flexible statistical framework for modelling relationships between a scalar response and predictors that are inherently functional in nature.

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

Bayesian field theory denotes a nonparametric Bayesian approach for learning functions from observational data. Based on the principles of Bayesian statistics, a particular Bayesian field theory is ...