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Negative Binomial Varying Coefficient Partially Linear Models
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 Title & Authors
Negative Binomial Varying Coefficient Partially Linear Models
Kim, Young-Ju;
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We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.
Negative binomial;penalized likelihood;semiparametric;smoothing parameter;smoothing spline;varying coefficients;
 Cited by
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