Continuous Variable: can take on any value between two specified values. Obtained by measuring. Covariance: a measure of the direction of the linear relationship between two variables. Discrete ...

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, martingales, concentration inequalities, branching ...

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, Chernoff bounds and large deviations, martingales, ...

Description: Basic set theory, elementary probability theory, discrete probability models, finite Markov chains. Applications to problems in the management and social sciences.

We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given default. We formulate the model in a discrete time frame, apply ...

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical ...

This paper develops an algorithm to calculate the Brownian multivariate normal probability subject to any preset error tolerance criteria. The algorithm is founded ...