Abstract
This lecture overviews Parameter estimation that has many applications in Statistics and Pattern Recognition. It covers the following topics in detail: Data analysis needs: Probabilistic data modeling, Estimation of pdf parameters (Location and dispersion parameters). Maximum Likelihood Parameter Estimation (ML Estimation for Gaussian Distributions, ML Estimation for Laplacian Distributions, Robustness of arithmetic mean and median). Maximum a Posteriori Probability Estimation.
Pdf of unknown location and various data samples.
Maximum a Posteriori Probability Estimation.
Parameter-Estimation-v2.3.1-Summary