The large sample theory for these estimators is developed. Furthermore results of Monte Carlo studies and an example of real data analysis are provided for the feasible generalized median estimator.

This model provides an extension of a covariate-adjusted regression approach to the case of a generalized linear model. We demonstrate that this contamination model leads to a semiparametric ...

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of-fit analyses. Census tracts. Fire ...

Linear regression models are used for binary classification that can then be generalized to multiclass classification and normally perform very well.

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...