Jennifer S.K. Chan
Names
first:  Jennifer 
middle:  S.K. 
last:  Chan 
Research profile
author of:

Statistical inference for geometric processes with gamma distributions
by Chan, Jennifer S. K. & Lam, Yeh & Leung, Doris Y. P. 
Robust Bayesian Analysis of Loss Reserves Data Using the Generalizedt Distribution
by Jennifer Chan & Boris Choy & Udi Makov 
Statistical Exploration from SARS
by Yu, Philip L. H. & Chan, Jennifer S. K. & Fung, Wing K. 
Monte Carlo approximation through Gibbs output in generalized linear mixed models
by Chan, Jennifer S. K. & Kuk, Anthony Y. C. & Yam, Carrie H. K. 
Statistical inference for geometric processes with lognormal distribution
by Lam Yeh & So Kuen Chan 
Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output
by Chan, Jennifer S. K. & Leung, Doris Y. P. & Boris Choy, S. T. & Wan, Wai Y. 
Binary geometric process model for the modeling of longitudinal binary data with trend
by Jennifer Chan & Doris Leung 
Classification in segmented regression problems
by Chen, Cathy W. S. & Chan, Jennifer S. K. & So, Mike K. P. & Lee, Kevin K. M. 
Bayesian analysis of robust Poisson geometric process model using heavytailed distributions
by Wan, WaiYin & Chan, Jennifer SoKuen 
Stochastic volatility models with leverage and heavytailed distributions: A Bayesian approach using scale mixtures
by Wang, Joanna J. J. & Chan, Jennifer S. K. & Choy, S. T. Boris 
Bayesian approach to analysing longitudinal bivariate binary data with informative dropout
by Jennifer Chan & Wai Wan 
Bayesian analysis of loss reserving using dynamic models with generalized beta distribution
by Dong, A. X. D. & Chan, J. S. K. 
A Bayesian conditional autoregressive geometric process model for range data
by Chan, J. S. K. & Lam, C. P. Y. & Yu, P. L. H. & Choy, S. T. B. & Chen, C. W. S. 
Risk Margin Quantile Function Via Parametric and NonParametric Bayesian Quantile Regression
by Alice X. D. Dong & Jennifer S. K. Chan & Gareth W. Peters 
A Poisson geometric process approach for predicting dropout and committed firsttime blood donors
by J. S. K. Chan & W. Y. Wan & P. L. H. Yu 
Efficient modelling and forecasting with range based volatility models and its application
by Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer Sokuen & Allen, David & Ng, Kooi Huat 
Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions
by Chan, Jennifer So Kuen & Wan, Wai Yin 
Robust Bayesian Analysis of Loss Reserves Data Using the Generalizedt Distribution
by Chan, Jennifer S. K. & Boris Choy, S. T. & Makov, Udi E. 
Robust Bayesian analysis of loss reserving data using scale mixtures distributions
by S. T. Boris Choy & Jennifer S. K. Chan & Udi E. Makov 
Risk Margin Quantile Function via Parametric and NonParametric Bayesian Approaches
by Dong, Alice X. D. & Chan, Jennifer S. K. & Peters, Gareth W.