Inverse regression methods facilitate dimension-reduction analyses of high-dimensional data by extracting a small number of factors that are linear combinations of the original predictor variables.

This is a preview. Log in through your library . Abstract We propose two test statistics for use in inverse regression problems Y = Kθ + ε, where K is a given linear operator which cannot be ...

sciences. As a result of this widespread interest in identifying non-monotonic relationships in data and the well-known problems with standard parametric approaches based on quadratic regression ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Eric's career includes extensive work in both public and corporate ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...