Discussing with a non statistician colleague, it seems that the logistic regression is not intuitive; Some basics questions like : - Why don't use the linear model? - What's logistic function? - How can we compute by hand, step by step t...

Regression is a mainstay of ecological and evolutionary data analysis. For example, a disease ecologist may use body size (e.g. a weight from a scale with measurement error) to predict infection. Classical linear regression assumes no error in covariates; they are known exactly. This is rarely the case in ecology, and ignoring error in covariates can bias regression coefficient...

Introduction The Ideal Gas Law, , is a very simple yet useful relationship that describes the behaviours of many gases pretty well in many situations. It is “Ideal” because it makes some assumptions about gas particles that make the math and the physics easy to work with; in fact, the simplicity that arises from these

As noted on paragraph 18.4.1 of the book Veterinary Epidemiologic Research, logistic regression is widely used for binary data, with the estimates reported as odds ratios (OR). If it’s appropriate for case-control studies, risk ratios (RR) are preferred for cohort studies as RR provides estimates of probabilities directly. Moreover, it is often forgotten the assumption

In the course on claims reserving techniques, I did mention the use of Poisson regression, even if incremental payments were not integers. For instance, we did consider incremental triangles > source("http://perso.univ-rennes1.fr/arthur.charpentier/bases.R") > INC=PAID > INC=PAID-PAID > INC 3209 1163 39 17 7 21 3367 1292 37 24 10 NA 3871...

Still going through the book Veterinary Epidemiologic Research and today it’s chapter 18, modelling count and rate data. I’ll have a look at Poisson and negative binomial regressions in R. We use count regression when the outcome we are measuring is a count of number of times an event occurs in an individual or group

by Joseph Rickert In a recent blog post, Revolution's Thomas Dinsmore announced stepwise regression for big data as a new feature of Revolution R Enterprise 6.2 that is scheduled for general availability later this month. Today, I would like to provide a simple example of doing stepwise regression with rxLinMod() (the RevoScaleR analog of lm()), using a 100,000 row...

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