Dunn, Peter K. <br/><br/>
Generalized linear models with examples in R / 
Peter K. Dunn, Gordon K. Smyth. 
 - New York :  Springer,  2018. 
 - xx, 562 p. :  24 cm. 
 - Springer texts in statistics, .
 - Springer texts in statistics. .
<br/><br/>Includes bibliographical references and index. 
<br/><br/>Statistical models -- Linear regression models -- Linear regression models: diagnostics and model-building -- Beyond linear regression: the method of maximum likelihood -- Generalized linear models: structure -- Generalized linear models: estimation -- Generalized linear models: inference -- Generalized linear models: diagnostics -- Models for proportions: binomial GLMs -- Models for counts: Poisson and negative binomial GLMs -- Positive continuous data: gamma and inverse Gaussian GLMs -- Tweedie GLMs -- Extra problems. 
<br/><br/><label>ISBN: </label>9781441901170 (hbk.) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Linear models (Statistics)<br/>R (Computer program language)<br/>Mathematical statistics.
<br/><br/><label>Dewey Class. No.: </label>519.535 DUN