Alex Smola et al.A tutorial on support vector regression.Statistics and Computing,2004 In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of curr
Our book is about using Stata for estimating and interpreting regression models with categorical outcomes. The book is divided into two parts. Part I contains general information that applies to all of the regression models that are considered in de
This book examines the application of basic statistical methods: primarily analysis of variance and regression but with some discussion of count data. It is directed primarily towards Masters degree students in statistics studying analysis of varian
In statistics, regression analysis consists of techniques for modeling the relationship between a dependent variable (also called response variable) and one or more independent variables (also known as explanatory variables or predictors).
Regression is the study of the conditional distribution Y |x of the response Y given the p × 1 vector of nontrivial predictors x. In a 1D regression model, Y is conditionally independent of x given a single linear combination α + βTx of the predicto
Logistic regression is a useful tool for analyzing data that includes categorical response variables, such as tree survival, presence or absence of a species in quadrats, and presence of disease or damage to seedlings
