Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear ...

This article ( original research paper) proposes a systematic regression-based fundamental equity valuation model that can potentially be applied in areas such as quantitative finance and machine ...

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 ...

Environmental epidemiologists often encounter time series data in the form of discrete or other nonnormal outcomes; for example, in modeling the relationship between air pollution and hospital ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus were used to construct a 12-gene ARG-based prognostic signature through LASSO and Cox regression ...

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with ...