Stochastic processes - Data processing.

Probability and random processes : = using MATLAB with applications to continuous and discrete time systems / by: (Language materials, printed)

The analysis of stochastic processes using GLIM / by: (Language materials, printed)

Stochastic simulation in physics / by: (Language materials, printed)

Simulation and inference for stochastic processes with YUIMA = a comprehensive R framework for SDEs and other stochastic processes / by: (Electronic resources)

Introduction to stochastic processes using R by: (Electronic resources)

Randomized algorithms / by: (Language materials, printed)

Monte Carlo method.

Quantitative Economics.

Probability Theory and Stochastic Processes.

Stochastic Processes.

Physics- Mathematical models.

GLIM.

Linear models (Statistics)- Data processing.

Stochastic processes- Mathematical models.

Algorithms.

R (Computer program language)

Applied Probability.

Probabilities- Data processing.

Probability Theory.

MATLAB.

Stochastic processes- Data processing.

Simulation methods.

Markov Process.

Physics- Data processing.

Stochastic processes.

Statistics.

Statistics and Computing/Statistics Programs.

Probability and Statistics in Computer Science.