R package for statistical inference using partially observed Markov processes

An R Package for Monte Carlo Option Pricing Algorithm for Jump Diffusion Models with Correlational Companies

Tools for Stochastic Simulation using diffusion models (R).

Stochastic epidemiological branching simulation

An R package for the stochastic simulation of processes with any marginal distribution and correlation structure

📈 📉 📈 📈 📉 Multisignal GMWM estimation and model selection for IMU

This repository is dedicated to engineering students at The national Higher School of Mathematics (NHSM) who are specialising in finance and economics for actuarial sciences. It contains R and Python code on various aspects of stochastic processes and their applications.

Code written as a part of MTH371 Stochastic Processes and its Applications taught my Dr. Monika Arora at IIIT Delhi in Monsoon 2018

R package to work with Markov Chain Steady-State probability vector.

Fast R implementation of Gillespie's Stochastic Simulation Algorithm

R scripts for implementing different stochastic methods

This repository contains the assignments of course Stochastic Processes and Applications (MTH371) of IIIT Delhi, taught by Dr. Monika Arora in the Monsoon Semester 2021.

R code for simulating basic queueing systems, including customer arrivals, service times, and waiting times.

A measure of the variability of linear trends in a time-series observation, as a function of windowing length

R code for finding realizations (samples) of Stochastic Processes

Employed Monte Carlo simulation to model beetle population dynamics within a closed ecosystem experiencing seasonal changes driven by fluctuations in food availability and habitat.

Monte-Carlo Simulations and Analysis of Stochastic Differential Equations

A stokhazesthai (stochastic) process, also called a random process, is one in which outcomes are uncertain (MAT 455, ISU).

tibble friendly, cleverly impure functions to simulate stochastic processes

Functional Data Analysis (clustering)