Developing a Model

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Related lectures (31)

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Maximum Likelihood: Inference and Model Comparison

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

Introduction to Behavior Modeling: Simple Example

Introduces behavior modeling through a simple example, focusing on choice modeling components and the analysis of the electric car market.

Maximum Likelihood Inference

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

Traffic flow modeling: Developing and testing traffic models

Covers the fundamentals of traffic flow modeling, including model classification and testing techniques.

Maximum Likelihood Theory & Applications

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Hidden Markov Models (HMM): Theory

Covers Hidden Markov Models (HMM) for modeling time series data and decoding using the Viterbi Algorithm.

Design Discussions, Documentation

Explores design discussions and documentation in software development, emphasizing scientific programming and code documentation tools like Doxygen and Sphinx.

Developing a Model: Simple Example

Presents a simple example of developing a model with a focus on variables and causal relationships.

Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

AdEx: Adaptive exponential integrate-and-fire

Covers the AdEx model, firing patterns, adaptation, and parameter estimation.