When Gaussian errors are inappropriate in a multivariate linear regression setting, it is often assumed that the errors are iid from a distribution that is a scale mixture of multivariate normals.
A general regression procedure for the prediction of a vector of population means in situations of nonresponse is proposed. The multivariate treatment of the prediction problem is not computationally ...
In light of the unpredictable effects of climate change and population shifts, responsible resource management will require new types of information and strategies going forward. For water utilities, ...
Associations between MDM2 SNP309 and SNP285C haplotypes and ovarian cancer risk in BRCA1 mutation carriers. A phase I trial of concurrent cetuximab (CET), cisplatin (CDDP), and radiation therapy (RT) ...
The past ten years have witnessed the development of handheld and portable tools, which has introduced new valuable analytical capabilities to quality assurance, quality control and manufacturing ...
Want to understand how multivariate linear regression really works under the hood? In this video, we build it from scratch in C++—no machine learning libraries, just raw code and linear algebra. Ideal ...
A group of scientists from Colombia’s Pontifical Bolivarian University has developed a novel temperature prediction method for PV inverters that utilizes symbolic regression (SR) based on particle ...
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