Statistical inference for geometric processes with gamma distributions. - Jennifer So-Kuen Chan; Yeh Lam; Doris Y. P. Leung (Comput. Stat. Data Anal., 2004)

Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output. - Jennifer So-Kuen Chan; Doris Y. P. Leung; S. T. Boris Choy; Wai-Yin Wan (Comput. Stat. Data Anal., 2009)

Binary geometric process model for the modeling of longitudinal binary data with trend. - Jennifer S. K. Chan; Doris Y. P. Leung (Comput. Stat., 2010)

Classification in segmented regression problems. - Cathy W. S. Chen; Jennifer So-Kuen Chan; Mike K. P. So; Kevin K. M. Lee (Comput. Stat. Data Anal., 2011)

Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions. - Wai-Yin Wan; Jennifer So-Kuen Chan (Comput. Stat. Data Anal., 2011)

Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures. - Joanna J. J. Wang; Jennifer So-Kuen Chan; S. T. Boris Choy (Comput. Stat. Data Anal., 2011)

Bayesian approach to analysing longitudinal bivariate binary data with informative dropout. - Jennifer So-Kuen Chan; Wai-Yin Wan (Comput. Stat., 2011)

A comparison of estimators for regression models with change points. - Cathy W. S. Chen; Jennifer So-Kuen Chan; Richard Gerlach; William Y. L. Hsieh (Stat. Comput., 2011)

A Bayesian conditional autoregressive geometric process model for range data. - Jennifer So-Kuen Chan; Connie P. Y. Lam; Philip L. H. Yu; S. T. Boris Choy; Cathy W. S. Chen (Comput. Stat. Data Anal., 2012)

An Innovative Financial Time Series Model: The Geometric Process Model. - Jennifer So-Kuen Chan; Connie P. Y. Lam; S. T. Boris Choy (TES, 2014)

Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions. - Jennifer So-Kuen Chan; Wai-Yin Wan (J. Multivar. Anal., 2014)

Autoregressive Conditional Duration Model with an Extended Weibull Error Distribution. - Rasika P. Yatigammana; S. T. Boris Choy; Jennifer So-Kuen Chan (Causal Inference in Econometrics, 2016)

Non-stationary neural network for stock return prediction. - Steven Y. K. Wong; Jennifer S. K. Chan; Lamiae Azizi; Richard Y. D. Xu (CoRR, 2020)

Supervised Temporal Autoencoder for Stock Return Time-series Forecasting. - Steven Y. K. Wong; Jennifer S. K. Chan; Lamiae Azizi; Richard Y. D. Xu (COMPSAC, 2021)

Time-varying neural network for stock return prediction. - Steven Y. K. Wong; Jennifer S. K. Chan; Lamiae Azizi; Richard Y. D. Xu (Intell. Syst. Account. Finance Manag., 2022)

Stochastic modelling of volatility and inter-relationships in the Australian electricity markets. - Joanna J. J. Wang; Jennifer S. K. Chan (Commun. Stat. Simul. Comput., 2023)

Temporal mixture density networks for enhanced investment modeling. - Fong Lam; Jennifer So-Kuen Chan (Expert Syst. Appl., 2025)

Quantifying neural network uncertainty under volatility clustering. - Steven Y. K. Wong; Jennifer S. K. Chan; Lamiae Azizi (Neurocomputing, 2025)