5 papers
Tail asymptotics for the bivariate skew normal in the general case
Thomas Fung, Eugene Seneta
The present paper is a sequel to and generalization of Fung and Seneta (2016) whose main result gives the asymptotic behaviour as of $λ_L(u) = P(X_1 \leq F_1^{-1}(u)…
Tail asymptotics for the bivariate equi-skew Variance-Gamma distribution
Thomas Fung, Eugene Seneta
We derive the asymptotic rate of decay to zero of the tail dependence of the bivariate skew Variance Gamma (VG) distribution under the equal-skewness condition, as an explicit regu…
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…
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-…
Tail dependence convergence rate for the bivariate skew normal under the equal-skewness condition
Thomas Fung, Eugene Seneta
We derive the rate of decay of the tail dependence of the bivariate skew normal distribution under the equal-skewness condition θ1 = θ2,= θ, say. The rate of convergence depends on…