Statistical Computing II

Catalog description

A continuation of Statistical Computing I using comprehensive and widely available tools like SAGE, SPSS, SAS and R. Advanced techniques will be covered including (but not limited to) numerical linear algebra, optimization and nonlinear equations, the EM algorithm, Laplace approximations, quadrature methods, simulation methodology, sampling, Monte Carlo and bootstrap methods.