# Stochastic Modeling and Bayesian Inference

Assignment help is an online tutoring site which caters to all the needs and requirements of the students by providing guidance of professional tutors in various fields. One such subject is statistics in which the students can seek assistance of our expert tutors. In statistics the students can get help in various sub-disciplines like introduction to stochastic processes. A stochastic process is the counterpart to a deterministic process. Instead of dealing with only one possible reality of how the process might evolve under time (as is the case, for example, for solutions of an ordinary differential equation, in a stochastic or random process there is some indeterminacy in its future evolution described by probability distributions. This means that even if the initial condition (or starting point) is known, there are many possibilities the process might go to, but some paths may be more probable and others less so.

This subject includes study of topics like Markov chains, branching processes, Poisson processes, birth and death processes, Brownian motion, martingales, introduction to stochastic integrals, and their applications. Other topics which are a part of the course are Brownian motion, Martingales, Central limit theorems and Stein's method, Poisson random measures, Approximations (Delta method, Edgeworth, etc.), Inequalities, Elements of Stochastic integrals. Stochastic processes and their applications in biological, chemical and financial modeling are studied. Bayesian inference about stochastic models based on the Monte Carlo sampling approach is also considered.

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