Power series generalized nonlinear models [Comput. Statist. Data Anal. 53 (2009) 1155–1166] can be used when the Poisson assumption of equidispersion is not valid. In these models, we consider a more ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

Fitting data with nonlinear regression -- Fitting data with linear regression -- Models -- How nonlinear regression works -- Confidence intervals of the parameters -- Comparing models -- How does a ...

Historical data and multiple nonlinear regressions allow the development of regional and national compressor station construction component cost estimation models, capable of estimating cost ...

Predictive modeling of data using modern regression and classification methods. Multiple linear regression; logistic regression; pitfalls and diagnostics; nonparametric and nonlinear regression and ...

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, ...