ROBUST ESTIMATION AND HYPOTHESIS TESTING IN 2k FACTORIAL DESIGN

Hypothesis Testing and Interval Estimation

1 Topics for this Module 1. An Idealistic Special Case — When is Known. 2. Con…dence Interval Estimation (a) Taking a Stroll with Mr. Mu 3. Hypothesis Testing (a) Parameter Spaces and Sample Spaces (b) Partitioning the Parameter Space (c) Partitioning the sample space (d) Raw Score Rejection Rules (e) Error Rates i. Type I Error ii. Type II Error (f) Statistical Power i. Power vs. Precision 4. ...

A general intuitive design pattern for optimally sequencing treatment combinations in 2k factorial experiment and a simple estimation algorithm

Robust Estimation and Testing 1 A Generally Robust Approach To Hypothesis Testing in Independent and Correlated Groups Designs by

Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. These problems are vastly reduced when using a robust measure of location; incorporating bootstrap methods can result in additional benefits. This paper illustrates the use of tr...

Asymptotically Minimax Robust Hypothesis Testing

The design of asymptotically minimax robust hypothesis testing is formalized for the Bayesian and Neyman-Pearson tests of Type I and II. The uncertainty classes based on the KL-divergence, αdivergence, symmetrized α-divergence, total variation distance, as well as the band model, moment classes and p-point classes are considered. It is shown with a counterexample that minimax robust tests do no...

Matched, mismatched, and robust scatter matrix estimation and hypothesis testing in complex t-distributed data

Scatter matrix estimation and hypothesis testing are fundamental inference problems in a wide variety of signal processing applications. In this paper, we investigate and compare the matched, mismatched, and robust approaches to solve these problems in the context of the complex elliptically symmetric (CES) distributions. The matched approach is when the estimation and detection algorithms are ...