Statistical theory and modeling

This subclass comprises research and experimental development in statistical theory and modeling.

Parent Category

C

Chen, Jiahua

Department of Statistics, Faculty of Science

Faculty (G+PS eligible/member)

empirical likelihood; finite mixture model; sample survey; asymptotic theory; imputation; Empirical likelihood, Finite mixture model, Sample survey, Asymptotic theory, imputation

K

Kroc, Edward

Department of Educational & Counselling Psychology, and Special Education, Faculty of Education

Faculty (G+PS eligible/member)

measurement; Measurement error; Statistics; urban ecology; Seabirds; Gulls; Quantitative ecology; Measurement, Measurement error, Statistics, Urban ecology, Seabirds, Gulls, Quantitative ecology

L

Lam, Tzeng Yih

Department of Forest Resources Management, Faculty of Forestry

Faculty (G+PS eligible/member)

Bayesian Filtering; Forest Inventory; Growth and Yield; Sampling Theory; silviculture; Timber; Tree Measurement; Bayesian Filtering, Forest Inventory, Growth and Yield, Sampling Theory, Silviculture, Timber, Tree Measurement

M

McDonald, Daniel

Department of Statistics, Faculty of Science

Faculty (G+PS eligible/member)

Methods and models for epidemiological forecasting; Estimation and quantification of prediction risk; Evaluating the predictive abilities of complex dependent data; Application of statistical learning techniques to time series prediction problems; Investigations of cross-validation and the bootstrap for risk estimation; Methods and models for epidemiological forecasting, Estimation and quantification of prediction risk, Evaluating the predictive abilities of complex dependent data, Application of statistical learning techniques to time series prediction problems, Investigations of cross-validation and the bootstrap for risk estimation

P

Pleiss, Geoffrey

Department of Statistics, Faculty of Science

Faculty (G+PS eligible/member)

Machine Learning; neural networks; Gaussian processes; Bayesian optimization; reliable deep learning; machine learning, neural networks, Gaussian processes, Bayesian optimization, reliable deep learning

R

Robeva, Elina

Department of Mathematics, Faculty of Science

Faculty (G+PS eligible/member)

Algebraic statistics; Graphical Models; Tensor decomposition; Causality; Applied algebraic geometry; Shape-constrained density estimation; Tensor networks; Algebraic statistics, Graphical models, Tensor decomposition, Causality, Applied algebraic geometry, Shape-constrained density estimation, Tensor networks

Z

Zumbo, Bruno

Department of Educational & Counselling Psychology, and Special Education, Faculty of Education

Faculty (G+PS eligible/member)

Psychometrics and Test Theory; Mathematical sciences of measurement; Latent Variable and Mixed Models, Item Response Theory, Factor Analysis; Validity Theory and Validation; Multivariate Analysis; Psychometrics and Test Theory; Mathematical sciences of measurement, Latent Variable and Mixed Models, Item Response Theory, Factor Analysis, Validity Theory and Validation, Multivariate Analysis

French Name

Théorie et modélisation statistiques

French Description

Cette sous-classe comprend la recherche et le développement expérimental en théorie statistique et modélisation.