Moment (mathematics) | Estimation methods
In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable. The method requires that a certain number of moment conditions be specified for the model. These moment conditions are functions of the model parameters and the data, such that their expectation is zero at the parameters' true values. The GMM method then minimizes a certain norm of the sample averages of the moment conditions, and can therefore be thought of as a special case of minimum-distance estimation. The GMM estimators are known to be consistent, asymptotically normal, and most efficient in the class of all estimators that do not use any extra information aside from that contained in the moment conditions. GMM were advocated by Lars Peter Hansen in 1982 as a generalization of the method of moments, introduced by Karl Pearson in 1894. However, these estimators are mathematically equivalent to those based on "orthogonality conditions" (Sargan, 1958, 1959) or "unbiased estimating equations" (Huber, 1967; Wang et al., 1997). (Wikipedia).
Generalized Coordinates & Equations of Motion | Classical Mechanics
When we consider a system of objects in classical mechanics, we can describe those objects with many different coordinate systems. Sometimes cartesian coordinates are most useful, some other times we might choose cylindrical coordinates. But there is also a way to view this system independ
From playlist Classical Mechanics
Introduction to Moments | Statics
https://goo.gl/1wkFDL for more FREE video tutorials covering Engineering Mechanics (Statics & Dynamics) The objective of this video is to clear the moment concept followed by a workout on simple moment calculation. First of all, the video gives the definition of moment stating that moment
From playlist SpoonFeedMe: Engineering Mechanics (Statics & Dynamics)
We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity promoting techniques to select the nonlinear and partial derivative
From playlist Research Abstracts from Brunton Lab
Moments of inertia example: double integrals
Free ebook http://tinyurl.com/EngMathYT How to calculate moments of inertia using double integrals. An example is presented illustrating the ideas.
From playlist Engineering Mathematics
Generalized Bisection Method for Systems of Nonlinear Equations
Generalization of the Bisection Method for solving systems of equations. This lesson explains the algorithm for a 2 dimension example based on Harvey-Stenger's approach using bisecting triangles. It includes a visualization of the method in action on an example nonlinear system. Other meth
From playlist Solving Systems of Nonlinear Equations
Newton's Method Interval of Convergence
How to find the Interval of Convergence for Newton-type methods such as Newton's Method, Secant Method, and Finite Difference Method including discussion on Damped Newton's Method and widening the convergence interval. Example code in R hosted on Github: https://github.com/osveliz/numerica
From playlist Root Finding
Finite Difference Method for finding roots of functions including an example and visual representation. Also includes discussions of Forward, Backward, and Central Finite Difference as well as overview of higher order versions of Finite Difference. Chapters 0:00 Intro 0:04 Secant Method R
From playlist Root Finding
Physics - Mechanics: Moment of Inertia (1 of 7) Parallel Axis Theorem: Example 1
Visit http://ilectureonline.com for more math and science lectures! In this video I will find the moment of inertia of 2 spheres connected by a rod rotated about the center of the rod. Next video in the moment of inertia series: http://youtu.be/swi7U6Q9pF0
From playlist PHYSICS 12 MOMENT OF INERTIA
Steffensen's Method for Systems of Nonlinear Equations
Generalized Steffensen's Method for Simultaneous Nonlinear Systems originally credited to J. F. Traub. Video shows how to solve nonlinear systems by approximating the Jacobian. Example code on GitHub https://www.github.com/osveliz/numerical-veliz Chapters 0:00 Prerequisites 0:20 Intro 0:
From playlist Solving Systems of Nonlinear Equations
Generalized maximum entropy estimation - T. Sutter - Main Conference - CEB T3 2017
Tobias Sutter (Zurich) / 11.12.2017 Title: Generalized maximum entropy estimation Abstract: We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints, possibly corrupted by noise. Based on duality
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
The Sample Complexity of Multi-Reference Alignment - Philippe Rigollet
Members' Seminar Topic: The Sample Complexity of Multi-Reference Alignment Speaker: Philippe Rigollet Affiliation: Massachusetts Institute of Technology; Visiting Professor, School of Mathematics Date: February 4, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
DDPS | Reduced order models for thermal radiative transfer problems based on moment equations & POD
In this DDPS talk from Aug. 13, 2021, Dmitriy Anistratov, a professor of nuclear engineering at North Carolina State University, presents a new group of reduced-order models (ROMs) for nonlinear thermal radiative transfer (TRT) problems. ROMs are formulated by means of the nonlinear proj
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Lecture Lorenzo Pareschi: Uncertainty quantification for kinetic equations III
The lecture was held within the of the Hausdorff Trimester Program: Kinetic Theory Abstract: In these lectures we overview some recent results in the field of uncertainty quantification for kinetic equations with random inputs. Uncertainties may be due to various reasons, like lack of kn
From playlist Summer School: Trails in kinetic theory: foundational aspects and numerical methods
The Power of Sampling by Peter W. Glynn
Infosys-ICTS Turing Lectures The Power of Sampling Speaker: Peter W. Glynn (Stanford University, USA) Date: 14 August 2019, 16:00 to 17:00 Venue: Ramanujan Lecture Hall, ICTS Bangalore Sampling-based methods arise in many statistical, computational, and engineering settings. In engine
From playlist Infosys-ICTS Turing Lectures
Joe Kileel - Method of moments in cryo-EM - IPAM at UCLA
Recorded 16 November 2022. Joe Kileel of the University of Texas at Austin presents "Method of moments in cryo-EM" at IPAM's Cryo-Electron Microscopy and Beyond Workshop. Abstract: In this talk, I will present recent advances in the theory and implementation of method of moments-based appr
From playlist 2022 Cryo-Electron Microscopy and Beyond
The subconvexity problem for L-functions – Ritabrata Munshi – ICM2018
Number Theory Invited Lecture 3.7 The subconvexity problem for L-functions Ritabrata Munshi Abstract: Estimating the size of automorphic L-functions on the critical line is a central problem in analytic number theory. An easy consequence of the standard analytic properties of the L-funct
From playlist Number Theory
On the Ising perceptron model - Nike Sun
Marston Morse Lectures Topic: On the Ising perceptron model Speaker: Nike Sun Affiliation: Massachusetts Institute of Technology Date: April 23, 2021 For more video please visit http://video.ias.edu
From playlist Mathematics
Towards a theory of non-commutative optimization...… -Rafael Oliveira
Computer Science/Discrete Mathematics Seminar I Topic: Towards a theory of non-commutative optimization: geodesic 1st and 2nd order methods for moment maps and polytopes Speaker: Rafael Oliveira Affiliation:University of Toronto Date: October 22, 2019 For more video please visit http://v
From playlist Mathematics
Method of Moment Distribution | Reinforced Concrete Design
http://goo.gl/ErP19y for more FREE video tutorials covering Concrete Structural Design This video demonstrates the theory of applied moment & fixed end moment; subsequently does an example to give a conceptual understanding of method of moment distribution (balancing act). Very first, the
From playlist SpoonFeedMe: Concrete Structures
Probability & Statistics in Finance
Mathematica 8 provides a suite of high-level functions for probability and statistics. New capabilities include the ability to compute the probability of any event or the expectation of any expression, simulate any distribution, and automatically estimate parameters or test goodness of fit
From playlist Wolfram Technology Conference 2010