EXTRA MATH Lec 6B: Maximum likelihood estimation for the binomial model
Forelæsning med Per B. Brockhoff. Kapitler:
From playlist DTU: Introduction to Statistics | CosmoLearning.org
Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of
From playlist COVARIANCE AND VARIANCE
EstimatingRegressionCoeff.8.MLE
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Estimating Regression Coefficients
Probability is not Likelihood. Find out why!!!
NOTE: This video was originally made as a follow up to an overview of Maximum Likelihood https://youtu.be/XepXtl9YKwc . That video provides context that gives this video more meaning. Here's one of those tricky little things, Probability vs. Likelihood. In common conversation we use these
From playlist StatQuest
Semantic models for higher-order Bayesian inference - Sam Staton, University of Oxford
In this talk I will discuss probabilistic programming as a method of Bayesian modelling and inference, with a focus on fully featured probabilistic programming languages with higher order functions, soft constraints, and continuous distributions. These languages are pushing the limits of e
From playlist Logic and learning workshop
Jean-Marc Bardet : Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of...
Abstract : We prove the consistency and asymptotic normality of the Laplacian Quasi-Maximum Likelihood Estimator (QMLE) for a general class of causal time series including ARMA, AR(∞), GARCH, ARCH(∞), ARMA-GARCH, APARCH, ARMA-APARCH,..., processes. We notably exhibit the advantages (moment
From playlist Probability and Statistics
Covariance Definition and Example
What is covariance? How do I find it? Step by step example of a solved covariance problem for a sample, along with an explanation of what the results mean and how it compares to correlation. 00:00 Overview 03:01 Positive, Negative, Zero Correlation 03:19 Covariance for a Sample Example
From playlist Correlation
Statistics: Ch 9 Hypothesis Testing (4 of 35) What is the "Alternative Hypothesis"?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 The null hypothesis (H0) is a statement about the population, the product, the design, of the capability or property of a population,
From playlist STATISTICS CH 9 HYPOTHESIS TESTING
Gravitational astronomy (Lecture 5) by B S Sathyaprakash
DATES Monday 25 Jul, 2016 - Friday 05 Aug, 2016 VENUE Madhava Lecture Hall, ICTS Bangalore APPLY Over the last three years ICTS has been organizing successful summer/winter schools on various topics of gravitational-wave (GW) physics and astronomy. Each school from this series aimed at foc
From playlist Summer School on Gravitational-Wave Astronomy
Sylvia Biscoveanu - Source characterization of individual compact binary coalescences - IPAM at UCLA
Recorded 20 September 2021. Sylvia Biscoveanu of the Massachusetts Institute of Technology presents "Source characterization of individual compact binary coalescences using Bayesian inference" at IPAM's Mathematical and Computational Challenges in the Era of Gravitational Wave Astronomy Tu
From playlist Tutorials: Math & Computational Challenges in the Era of Gravitational Wave Astronomy
Juan Calderon-Bustillo - Challenge of characterising high-mass compact mergers: the case of GW190521
Recorded 18 November 2021. Juan Calderon-Bustillo of the University of Santiago de Compostela presents "The challenge of characterising high-mass compact mergers: the case of GW190521" at IPAM's Workshop III: Source inference and parameter estimation in Gravitational Wave Astronomy. Abstra
From playlist Workshop: Source inference and parameter estimation in Gravitational Wave Astronomy
Intro to non normal distributions. Several examples including exponential and Weibull.
From playlist Probability Distributions
R - Grammar Analysis with Logistic Regression
Lecturer: Dr. Erin M. Buchanan Summer 2019 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class. This video continues with co-relations by using distinctive collexeme analysis to determine the likelihood of collocates (combinations of words). N
From playlist Human Language (ANLY 540)
Boris Beranger - Composite likelihood and logistic regression models for aggregated data
Dr Boris Beranger (UNSW Sydney) presents “Composite likelihood and logistic regression models for aggregated data”, 14 August 2020. This seminar was organised by the University of Technology Sydney.
From playlist Statistics Across Campuses
Matt Moores - The Annealed Leap-Point MCMC Sampler (ALPS) for multi-modal posterior distributions
Dr Matt Moores (University of Wollongong) presents, "The Annealed Leap-Point MCMC Sampler (ALPS) for multi-modal posterior distributions", 10 June 2022.
From playlist Statistics Across Campuses
Order, Entropy, Information, and Compression (Lecture 1) by Dov Levine
PROGRAM ENTROPY, INFORMATION AND ORDER IN SOFT MATTER ORGANIZERS: Bulbul Chakraborty, Pinaki Chaudhuri, Chandan Dasgupta, Marjolein Dijkstra, Smarajit Karmakar, Vijaykumar Krishnamurthy, Jorge Kurchan, Madan Rao, Srikanth Sastry and Francesco Sciortino DATE: 27 August 2018 to 02 Novemb
From playlist Entropy, Information and Order in Soft Matter
Causal Inference is a set of tools used to scientifically prove cause and effect, very commonly used in economics and medicine. This series will go over the basics that any data scientist should understand about causal inference - and point them to the tools they would need to perform it.
From playlist Causal Inference - The Science of Cause and Effect