Applying Generalized Linear Models

By J. Lindsey. 2000

367 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3fa34d1a96e32bedfee2a62995e4bc4ead74b87e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Malay Ghosh
2. A. Lecerf
3. A. Klimley
4. Joseph C. Heublein
5. M. Moser
6. J. T. Kelly
7. A. I. Khuri
8. D. Welch

In Statistics and Probability

1. Malay Ghosh
2. A. Lecerf
3. A. Klimley
4. Mark Berman
5. Andrew Hardegen
6. Rohan Shah
7. Joseph C. Heublein
8. M. Moser

Citations in the corpus

• Marine Migration of North American Green Sturgeon (2008, methodology): “—To answer the question of whether green sturgeon tagged and released in different geographic locations (Rogue, Klamath, and Columbia rivers; San Pablo and Willapa bays; and Grays Harbor) are subsequently distributed differently, we used a generalized linear model with binomial error structure and l”
• Design Issues for Generalized Linear Models: A Review (2006, background): “In addition,them orerecentbooksby Lind- sey (1997),M cCulloch and Searle (2001),Dobson (2002)and M yers,M ontgom ery and Vining (2002) provideadded insightsinto theapplication and use- fulnessofG LM s.”
• Kinetic modeling on drug release from controlled drug delivery systems. (2010, neutral): “Linear or first order regression model (50-52).”
• Spatial logistic regression and change-of-support in Poisson point processes (2010, background): “Approximation of a stochastic process by a generalized linear model is now commonplace in applied statistics [55, 56, 57].”
• Multivariate Statistical Modelling Based on Generalized Linear Models (2003, background): “Could students avoid buying a text devoted solely to univariate GLMs, such as the seminal text of McCullagh and Nelder (1989) or the primer by Lindsey (1997)?”
• A study on the effects of unbalanced data when fitting logistic regression models in ecology (2018, background): “In a GLM, three compartments must be specified (Lindsey, 1997; Schabenberger and Pierce, 2002): a random component, a systematic component, and a link function.”
• Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application (2013, background): “Generalized linear models (GLMs) are a large class of statistical models for relating responses to linear combinations of predictor variables, including many commonly encountered types of dependent variables and error structures as special cases (Lindsey 1997).”
• Diversity and functions of leaf‐decaying fungi in human‐altered streams (2008, positive): “For each pair of sites, we assessed differences in leaf breakdown rates between control and impact sites, and between coarse and fine mesh bags using separate generalized linear models based on a normal distribution (Lindsey, 1997).”