Bayesian Estimation

CEO Salary Estimation Problem Consider the following problem. An investigative reporter wants to figure out how much salary makes the CEO of an investment bank X. For this he conducts interviews with some of the employees of that bank and writes down their salaries, which forms the following sample

Dose-Response Curves in R

Introduction Abstract In clinical research the dose–response relationship is often non-linear, therefore advanced fitting models are needed to capture their behavior. The talk will concentrate on fitting non-linear parametric models to the dose–response data and will explain some specificities of this problem.

Optimality of Estimators in Regular Models

Consistent Estimators In the estimation problem of a one-dimensional parameter \(\theta\) from an i.i.d. sample \[X^n=(X_1,\cdots,X_n),\ \ X_i\sim F(x,\theta),\,\theta\in\Theta\subset R\] we introduced the notion of consistency of an estimator. This means that whatever the unknown value of \(\theta\) is, this estimator is going to be close to that value in higher probability as \(n\) increases \[\hat\theta_n\approx\theta, \text{ for large } n.