Sufficient statistic - PDFSEARCH.IO - Document Search Engine

Sufficient statistic
Results: 125

#	Item
21	c8k, :51 CHAPTER 8 Add to Reading List Source URL: omega.albany.edu Language: English - Date: 2005-09-22 15:53:38 Fisher information Sufficient statistic Likelihood principle Likelihood function Maximum likelihood Completeness Estimation theory Statistics Statistical theory
22	Statistics 200 Computer Lab Section #3 The aim of this exercise is to construct a minimum variance unbiased estimate for the proportion π of a Normal population that is above a given value c on the basis of an observed Add to Reading List Source URL: statweb.stanford.edu Language: English - Date: 2001-09-20 14:45:48 Bias Bias of an estimator Variance Sufficient statistic Beta distribution Minimum-variance unbiased estimator Normal distribution Symbol Statistics Statistical theory Probability theory
23	Statistics 580 The EM Algorithm Introduction The EM algorithm is a very general iterative algorithm for parameter estimation by maximum likelihood when some of the random variables involved are not observed i.e., conside Add to Reading List Source URL: www.cse.cuhk.edu.hk Language: English M-estimators Expectation–maximization algorithm Missing data Maximum likelihood Sufficient statistic Statistics Estimation theory Statistical theory
24	Lecture 39: The method of moments The method of moments is the oldest method of deriving point estimators. It almost always produces some asymptotically unbiased estimators, although they may not be the best estimators. Add to Reading List Source URL: www.stat.wisc.edu Language: English - Date: 2008-09-02 18:49:43 Statistical inference Consistent estimator Completeness Bias of an estimator Sufficient statistic Law of large numbers Estimator Minimum-variance unbiased estimator Maximum likelihood Statistics Estimation theory Statistical theory
25	Chapter 1 Heuristics The official dogma on parametric estimation is: Good estimators converge to the right thing and have limiting normal distributions; moreover, the variance of the limiting distribution can’t be sma Add to Reading List Source URL: www.stat.yale.edu Language: English - Date: 2010-09-07 00:00:23 Consistent estimator Maximum likelihood Fisher information Fisher consistency Loss function Estimator Sufficient statistic Delta method M-estimator Statistics Estimation theory Statistical theory
26	On the Generalization of the Likelihood Function and the Likelihood Principle Jan F. Bjornstad Journal of the American Statistical Association, Vol. 91, NoJun., 1996), ppStable URL: http://links.jstor. Add to Reading List Source URL: www.phil.vt.edu Language: English - Date: 2011-03-10 19:45:58 Bayesian statistics M-estimators Regression analysis Likelihood principle Sufficient statistic Maximum likelihood Empirical Bayes method Likelihood function Covariance Statistics Estimation theory Statistical theory
27	Learning Continuous Time Bayesian Networks Uri Nodelman Stanford University Add to Reading List Source URL: robotics.stanford.edu Language: English - Date: 2005-05-18 16:00:10 Markov models Bayesian network Networks Markov chain Conjugate prior Gamma distribution Exponential family Bayesian inference Sufficient statistic Statistics Bayesian statistics Statistical theory
28	Exponential Families Classification and Novelty Detection S.V.N. “Vishy” Vishwanathan http://web.rsise.anu.edu.au/~vishy National ICT Australia Add to Reading List Source URL: www.stat.purdue.edu Language: English - Date: 2009-08-21 20:27:32 Mathematical analysis Exponentials M-estimators Maximum likelihood Exponential family Sufficient statistic Likelihood function Exponential function Laplace distribution Statistics Estimation theory Statistical theory
29	Bayesian Nonparametrics Foundations and Applications Notes to Stat 718 (SpringJayaram Sethuraman E-mail: Modified on April 22, 2008 Add to Reading List Source URL: www.nps.edu Language: English - Date: 2013-09-23 21:16:43 Sufficient statistic Normal distribution Symbol Statistics Statistical theory Gamma distribution
30	Expectation Maximization and Complex Duration Distributions for Continuous Time Bayesian Networks Uri Nodelman Stanford University Add to Reading List Source URL: robotics.stanford.edu Language: English - Date: 2005-06-05 21:42:42 Exponentials Statistical theory Bayesian statistics Expectation–maximization algorithm Hidden Markov model Bayesian network Exponential family Maximum likelihood Sufficient statistic Statistics Markov models Estimation theory

UPDATE