In environmental and nutritional epidemiology and in many other fields, there is increasing interest in estimating the effect of simultaneous exposure to several agents (e.g., multiple nutrients, ...
To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits ...
Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 67, No. 1 (2005), pp. 63-78 (16 pages) The literature on multivariate linear regression includes multivariate normal ...
Impact of 68Ga-PSMA-11 PET/CT on staging and management of prostate cancer patients in various clinical settings. This is an ASCO Meeting Abstract from the 2020 Genitourinary Cancers Symposium. This ...
In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...
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 ...
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 ...
Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...
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