This article explains how to create and use Gaussian process regression (GPR) models. Compared to other regression techniques, GPR is especially useful when there is limited training data. There are ...

In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

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 regression model, ...

Figure 3: Regression flow after separating the common set up phase reused by all tests, yielding a 20% saving on regression time Using a simulator’s automation for this methodology, you should be able ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

A crucial step in the model-building process is the selection of a good model among many possible candidates. Taking into account the effect of estimated regressors, we develop an ...

Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

There are many different techniques available to create a regression model. Some common techniques, listed from less complex to more complex, are: linear regression, linear lasso regression, linear ...