Maximum Likelihood & Method of Moments Estimation Patrick Zheng

Source URL: gradquant.ucr.edu

Calcolo applicato alla Statistica Maximum Likelihood Problema fisico – 1/2 ●

Source URL: virgilio.mib.infn.it

Genome Informatics 11: 96–Environmental Factor Dependent Maximum Likelihood Method for Association Study Targeted to Personalized

Source URL: www.jsbi.org

Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models Author(s): Whitney K. Newey and Douglas G. Steigerwald Source: Econometrica, Vol. 65, No. 3 (May, 1997), ppPublis

Source URL: econ.ucsb.edu

NIPSBeyond maximum likelihood and density estimation: A sample-based riterion for unsupervised learning of omplex models

Source URL: www.bioinf.jku.at

Athreya, Arjun. Price, M.N., Dehal, P.S., and Arkin, A.P). “FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments.” PLoS ONE, 5(3):e9490. doi:journal.poneChou, Jed. Julia

Source URL: tandy.cs.illinois.edu

CHAPTER 5 Estimating an Examinee’s Ability 84

Source URL: echo.edres.org

• Psychometrics
• Education
• Statistics
• Evaluation
• Item response theory
• Maximum likelihood estimation
• Test score
• Likelihood function
• Attribute hierarchy method

Spectral learning of linear dynamics from generalised-linear observations with application to neural population data Lars Buesing∗ , Jakob H. Macke∗,† , Maneesh Sahani Gatsby Computational Neuroscience Unit

Source URL: www.mackelab.org

• Statistics
• Statistical theory
• Estimation theory
• Actuarial science
• Expectationmaximization algorithm
• Missing data
• Maximum likelihood estimation
• Variational Bayesian methods
• Linear regression
• Normal distribution
• Covariance
• Regression analysis

Chapter 6 Parameter Estimation Take a random variable x described by a pdf f (x): the sample space is defined to be the set of all possible values of x. The set of n independent measurements of the random variable x, {x

Source URL: ihp-lx.ethz.ch

• Statistics
• Estimation theory
• Statistical theory
• Probability distributions
• Statistical inference
• Bias of an estimator
• Maximum likelihood estimation
• Efficient estimator
• Estimator
• Uniform distribution
• Normal distribution
• Exponential distribution

Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner

Source URL: eew.caltech.edu

• Statistics
• Probability
• Maximum likelihood estimation
• Probability distributions
• Bayesian statistics
• Expectationmaximization algorithm
• Mixture model
• Normal distribution
• K-means clustering
• Likelihood function
• Data stream clustering
• Gamma distribution