What would be the optimal (bayesian?) solution for fitting a model f(x) to data h, given the following assumptions: h is a vector with N elements h has gaussian noise with known covariance $\sigma_h ...
I realize the methodology pursued by the Frequentist and Bayesian camps generally differ. However, one method of estimation that they do share is optimization of a certain function: Frequentists ...
I need to implement a program that will classify records into 2 categories (true/false) based on some training data, and I was wondering at which algorithm/methodology I should be looking at. There ...
I am trying to state a prior distribution for a Bayesian meta-analysis. I have the following information about a random variable: Two observations: 3.0, 3.6 a scientist who studies the variable ...