The General Linear Model (GLM) is a statistical framework that generalizes multiple linear regression to include various types of linear relationships between a dependent variable and one or more ...

In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

What is a Generalized Linear Model? A traditional linear model is of the form where y i is the response variable for the i th observation. The quantity x i is a column vector of covariates, or ...

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

Course TopicsOrdinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be discrete (e.g ...

The convolutional neural network is also able to recover the true model variables (kernels) used to generate the probability of spiking in the output neuron. Based on the convolutional neural network ...