The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance.

Hoerl and Kennard introduced a class of biased estimators (ridge estimators) for the parameters in an ill-conditioned linear model. In this paper the ridge estimators are viewed as a subclass of the ...

We study linear smoothers and their use in building nonparametric regression models. In the first part of this paper we examine certain aspects of linear smoothers for scatterplots; examples of these ...

DTSA 5013 Generalized Linear Models and Nonparametric Regression DTSA 5013 Generalized Linear Models and Nonparametric Regression Specialization: Statistical Modeling for Data Science Applications ...

This is the equivalent of linear algebra—performing matrix multiplication. However, AI models are often used to find intricate patterns in data where the output is not always proportional to the ...

This unit builds on the basic ideas of linear models introduced in Probability and Statistics 1 (MATH 11340), and Linear Models (MATH 35110), and extends them to deal with more general specifications.

A Temple University environmental engineer has outlined new mathematical procedures, or techniques, to produce analytical solutions of the complex, non-linear equations of water flow in soils ...