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Gaussian Linear Models - MIT OpenCourseWare
Gaussian Linear Models Gaussian Linear Models MIT Dr. Kempthorne Spring 2016 1 MIT Gaussian Linear Models Gaussian Linear Models Linear regression : Overview Ordinary Least Squares (OLS) Distribution Theory: Normal regression Models Maximum Likelihood Estimation Generalized M Estimation Outline 1 Gaussian Linear Models Linear regression : Overview Ordinary Least Squares (OLS) Distribution Theory: Normal regression Models Maximum Likelihood Estimation Generalized M Estimation 2 MIT Gaussian Linear Models Gaussian Linear Models Linear regression : Overview Ordinary Least Squares (OLS) Distribution Theory: Normal regression Models Maximum Likelihood Estimation Generalized M Estimation General Linear model : For each case i, the conditional distribution [yi | xi ] is given by yi = yi + Ei where y i = 1xi,1 + 2xi,2 + + i,pxi,p = ( 1, 2.)
Distribution Theory: Normal Regression Models Maximum Likelihood Estimation Generalized M Estimation. Outline. 1. Gaussian Linear Models. Linear Regression: Overview Ordinary Least Squares (OLS) Distribution Theory: Normal Regression Models Maximum Likelihood Estimation Generalized M Estimation. ò. MIT 18.655 Gaussian Linear Models
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