Environmental noise is prevalent and ubiquitous, particularly that from traffic in urban areas. 1 Noise has been associated with annoyance, cardiovascular disease, and impaired cognitive performance, ...
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 ...
This is a preview. Log in through your library . Abstract Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique The authors develop a new class of distributions by introducing skewness in multivariate elliptically symmetric distributions.
The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...
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 ...
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 ...
A Slovak research team has developed a mathematical model for determining the optimum tilt angle of a solar system ranging from 0° to 90°. Their framework was tested on an experimental setup in ...
The author investigates how probabilistic classification can be used to enhance credit-scoring accuracy, offering a robust means for assessing model performance ...
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