Continuous-Time Markov Chains: Birth and Death Processes

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Page 3 of 3

Markov Chains: Definitions and State Probabilities

Covers the definitions and state probabilities of discrete-time Markov chains.

Stochastic Reaction Simulation: Constantin

Covers the algorithm to simulate molecule reactions using random numbers.

Statistics: Exploratory Data Analysis

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Probability and Statistics

Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.

Probability Inequalities

Explores probability inequalities, convergence types, and moment generating functions for distribution approximation.

Generalization of Martingales

Explores the generalization of Martingale Central Limit Theorem to sub- and supermartingales, discussing key properties and corollaries.

Probability and Statistics

Introduces key concepts in probability and statistics, illustrating their application through various examples and emphasizing the importance of mathematical language in understanding the universe.

Probability and Statistics: Independence and Conditional Probability

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Discrete-Time Markov Chains: Definitions

Covers the definitions and state probabilities of discrete-time Markov chains.