17 citations · 49 across the 11 of their papers we have counts for
11 papers
Encoding large information structures in linear algebra and statistical models
David Banh, Alan Huang
Large information sizes in samples and features can be encoded to speed up the learning of statistical models based on linear algebra and remove unwanted signals. Encoding informat…
On arbitrarily underdispersed Conway-Maxwell-Poisson distributions
Alan Huang
We show that the Conway--Maxwell--Poisson distribution can be arbitrarily underdispersed when parametrized via its mean. More precisely, if the mean is an integer then the limi…
Consistent second-order discrete kernel smoothing using dispersed Conway-Maxwell-Poisson kernels
Alan Huang, Lucas Sippel, Thomas Fung
The histogram estimator of a discrete probability mass function often exhibits undesirable properties related to zero probability estimation both within the observed range of count…
Bayesian generalized linear model for over and under dispersed counts
Alan Huang, Andy Sang Il Kim
Bayesian models that can handle both over and under dispersed counts are rare in the literature, perhaps because full probability distributions for dispersed counts are rather diff…
Are profile likelihoods likelihoods? No, but sometimes they can be
Alan Huang, Andy Sangil Kim
We offer our two cents to the ongoing discussion on whether profile likelihoods are "true" likelihood functions, by showing that the profile likelihood function can in fact be iden…
Profile likelihood ratio tests for parameter inferences in generalized single-index models
Nanxi Zhang, Alan Huang
A profile likelihood ratio test is proposed for inferences on the index coefficients in generalized single-index models. Key features include its simplicity in implementation, inva…
Orthogonality of the mean and error distribution in generalized linear models
Alan Huang, Paul J. Rathouz
We show that the mean-model parameter is always orthogonal to the error distribution in generalized linear models. Thus, the maximum likelihood estimator of the mean-model paramete…
Mean-parametrized Conway-Maxwell-Poisson regression models for dispersed counts
Alan Huang
Conway-Maxwell-Poisson (CMP) distributions are flexible generalizations of the Poisson distribution for modelling overdispersed or underdispersed counts. The main hindrance to thei…
Semiparametric generalized linear models for time-series data
Thomas Fung, Alan Huang
Time-series data in population health and epidemiology often involve non-Gaussian responses. In this note, we propose a semiparametric generalized linear models framework for time-…
Doubly-nonparametric generalized additive models
Alan Huang, Nanxi Zhang
The popular generalized additive model framework is extended to allow both the mean curves and the response distribution to be nonparametric. The approach is demonstrated to be a f…
On generalized estimating equations for vector regression
Alan Huang
Generalized estimating equations (GEE; Liang & Zeger 1986) for general vector regression settings are examined. When the response vectors are of mixed type (e.g. continuous-binary…