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- Bayesian Probability: Our team has a strong grasp of Bayesian methods and can effectively apply them to analyze complex probabilistic problems. We can guide students in understanding prior and posterior probabilities, and likelihood, and updating beliefs with new evidence.
- Markov Chains: Our expertise lies in working with intricate Markov chains, calculating transition probabilities, and analyzing long-term behavior. We can help students model real-world processes using Markov chains and derive meaningful insights.
- Stochastic Processes: We excel in explaining various types of stochastic processes, including Poisson processes, Wiener processes, and renewal processes. Our assistance enables students to comprehend random processes' characteristics and make accurate predictions.
- Monte Carlo Simulation: Our service can guide students in employing Monte Carlo methods to solve problems involving uncertainty and high-dimensional integrals. We can help generate random samples and estimate probabilities for complex scenarios.
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- Brownian Motion: Our experts can explain the properties of Brownian motion, its applications in finance, physics, and biology. We can also help students simulate Brownian motion and model its behavior accurately.
- Hidden Markov Models: We specialize in working with hidden Markov models, particularly in speech recognition, bioinformatics, and natural language processing. Our guidance helps students grasp the algorithms for parameter estimation and decoding.
- Extreme Value Theory: Our service can help students comprehend extreme value distributions and estimate tail probabilities. We can also assist in applying EVT to model rare events in finance, engineering, and environmental studies.
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