Rhonda Van Dyke, Ph.D., Cincinnati Children's Hospital
November 17, 2009 @ 3:30 pm - 4:30 pmLocation: BRB - 251
Biostatistics
TITLE: Mixtures of Self-Modeling Regressions
A shape invariant model for functions f_1,… f_n specifies that each
individual function f_i can be related to a common shape function g
through the relation f_i(x)=a_i g(c_i x + d_i)+b_i. We consider a
mixture model that allows multiple shape functions g_1,…,g_K, where
each f_i is a shape invariant transformation of one of those g_k. We
derive an MCMC algorithm for fitting the model using Bayesian Adaptive
Regression Splines (BARS) and discuss some of the computational
difficulties that arise. The method is illustrated using synaptic
transmission data, where the groups of functions may indicate
different active zones in a synapse.
