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
Mixture models: latent classes
Graph Chatbot
Related lectures (41)
Mixture Models: Simulation-based Estimation
Explores mixture models, including discrete and continuous mixtures, and their application in capturing taste heterogeneity in populations.
Mixture models: taste heterogeneity
MOOC: Selected Topics on Discrete Choice
Explores mixture models in discrete choice and random parameters estimation results.
Regression: Linear Models
Introduces linear regression, generalized linear models, and mixed-effect models for regression analysis.
Variational Inference and Neural Networks
Covers variational inference and neural networks for classification tasks.
Maximum Likelihood: Inference and Model Comparison
Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.
Mixture models: alternative specific variance
MOOC: Selected Topics on Discrete Choice
Explores alternative specific variance in mixture models and discusses identification issues and model comparisons using 500 draws.
Debiased Whittle Likelihood: Time Series and Spatial Data
Explores the Debiased Whittle likelihood for time series and spatial data, focusing on fitting spectral density to the periodogram for better predictions and parameter estimation.
Personalized Menu Optimization
Explores Bayesian methods in choice modeling for personalized menu optimization and individual choice prediction.
Optimisation in Energy Systems
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
Law of Large Numbers, Statistics
Covers the Law of Large Numbers in Statistics and methods for deriving estimators and maximum likelihood.
Estimation Methods
Covers various methods for estimating model parameters, such as method of moments and maximum likelihood estimation.
Estimation Methods in Probability and Statistics
Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.
Latent Space Models: Inference and Applications
Log in to Mediaspace to watch this video
Explores latent space models, network representations, spectral decompositions, and parameter estimation methods.
Linear Mixed Model
Log in to Mediaspace to watch this video
Covers the linear mixed model, including fixed and random effects, estimation, and inference techniques.
Maximum Likelihood Theory & Applications
Log in to Mediaspace to watch this video
Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.
Modeling Neurobiological Signals: Spikes & Firing Rate
Log in to Mediaspace to watch this video
Explores modeling neurobiological signals, focusing on spikes, firing rate, multiple state neurons, and parameter estimation.
Topic Models: Understanding Latent Structures
Log in to Mediaspace to watch this video
Explores topic models, Gaussian mixture models, Latent Dirichlet Allocation, and variational inference in understanding latent structures within data.
Gaussian Mixture Models & Noisy Signals
Log in to Mediaspace to watch this video
Explores Gaussian mixture models and denoising noisy signals using a probabilistic approach.
Statistical Analysis: Data Exploration and Inference
Log in to Mediaspace to watch this video
Covers statistical analysis, emphasizing data exploration and inference to quantify uncertainty and draw conclusions.
Estimation and Analysis of Deviance
Log in to Mediaspace to watch this video
Covers estimation of unknown parameters, analyzing model fit, bird prey response, and model diagnostics.
Previous
Page 1 of 3
Next
