Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Parameter Estimation of SDEs with Linear Response Theory
Graph Chatbot
Related lectures (49)
Nonparametric Statistics: Bayesian Approach
Explores non-parametric statistics, Bayesian methods, and linear regression with a focus on kernel density estimation and posterior distribution.
Spectral & Parametric Estimation: Time Series
Covers spectral estimation techniques like tapering and parametric estimation, emphasizing the importance of AR models and Whittle likelihood in time series analysis.
Linear Regression: Estimation and Testing
Explores linear regression estimation, hypothesis testing, and practical applications in statistics.
Linear Regression: Estimation and Inference
Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.
NonLinear Regression
Explores non-linear regression models, likelihood estimation, model fitting, and confidence intervals.
Estimation and Forecasting in Time Series
Explores estimation, forecasting, and model comparison in time series analysis using real data examples to motivate the study.
Orthogonal/Orthonormal Bases and Polynomials
Explores orthogonal and orthonormal bases, Gram-Schmidt process, and orthogonal polynomials in physics.
Weighted Least Squares Estimation: IRLS Algorithm
Explores the IRLS algorithm for weighted least squares estimation in GLM.
Linear Regression: Concepts and Applications
Introduces linear regression concepts, from X-bands creation to slope estimator properties and tests.
Multilinear Regression: Basics and Applications
Covers the basics of multilinear regression and its application in analyzing material properties.
Linear Algebra in Data Science
Explores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.
Statistical Estimation Methods
Covers statistical estimation methods, including maximum likelihood and Bayesian estimation.
Statistical Justification of Least Squares
Explores the statistical justification of Least Squares and Generalized Linear Models.
Linear Regression and Least Squares Method
Explores linear regression and the least squares method to minimize the loss function for the best fit.
Linear Regression: Estimation and Prediction
Log in to Mediaspace to watch this video
Covers the basics of linear regression, focusing on estimation and prediction.
Digital Derivation: Evaluation and Formulas
Log in to Mediaspace to watch this video
Explores digital derivation, function evaluation, and polynomial approximations for accurate measurements and evaluations.
Regression: Simple and Multiple Linear
Log in to Mediaspace to watch this video
Covers simple and multiple linear regression, including least squares estimation and model diagnostics.
Linear Regression: Basics and Estimation
Log in to Mediaspace to watch this video
Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.
Linear Regression: Basics and Applications
Log in to Mediaspace to watch this video
Explores linear regression using the method of least squares to fit data points with the equation y = ax + b.
Basics of Linear Regression
Log in to Mediaspace to watch this video
Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Previous
Page 1 of 3
Next