Thomas W. Yee

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Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalized linear and additive model (VGLM/VGAM) framework. Additionally, there are natural extensions, such as reduced-rank VGLMs for dimension reduction, and allowing covariates that have values specific to each(More)
One of the most popular methods for quantile regression is the LMS method of Cole and Green. The method naturally falls within a penalized likelihood framework, and consequently allows for considerable flexible because all three parameters may be modelled by cubic smoothing splines. The model is also very understandable: for a given value of the covariate,(More)
For several decades now, ecologists have sought to determine the shape of species' response curves and how they are distributed along unknown underlying gradients, environmental latent variables, or ordination axes. Its determination has important implications for both continuum theory and community analysis because many theories and models in community(More)
Species' presence/absence at two time points is a very common form of ecological data. It is the simplest type of longitudinal study and has fundamental applications in ecological succession, environmental monitoring, and climate change scenarios. Despite its widespread commonality the use of statistical regression to analyse such data has been wanting. We(More)
It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture–recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and(More)
data= Data frame with the formula variables. subset= Vector of logicals. na.action= What to do with missing values. "" causes an error, "na.omit" deletes rows. Can be assigned a user-defined function. Extractor functions class() The object’s class. coef() Regression coefficients (the βk in (1) but enumerated in a different order). Coef() Regression(More)
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