Luc Devroye, Gábor Lugosi, Local Tail Bounds for Functions of Independent Random Variables, The Annals of Probability, Vol. 36, No. 1 (Jan., 2008), pp. 143-159 ...

Characteristic and generating functions. Vector formulation of random variables and their parameters. Mean square estimation and orthogonality principle. Criteria for estimators. Introduction to ...

P. Scheinok, The Distribution Functions of Random Variables in Arithmetic Domains Modulo a, The American Mathematical Monthly, Vol. 72, No. 2 (Feb., 1965), pp. 128-134 ...

Functions of Random Variables. Monte Carlo Simulation in R. Joint distributions and joint moments. Marginal and conditional densities. Independence, covariance and correlation. Sums of random ...

Introduction to the theories of probability and random variables, and their applications in the analysis and modelling of engineering systems. Topics include: a review of probability and random ...

You can use the RAND () function to establish probability and create a random variable with normal distribution.

Studies axioms, combinatorial analysis, independence and conditional probability, discrete and absolutely continuous distributions, expectation and distribution of functions of random variables, laws ...

The course covers the probability, distribution theory and statistical inference needed for third year courses in statistics and econometrics. Michaelmas term: Events and their probabilities. Random ...

Probability distribution functions (PDFs) describe the expected values of random variables drawn from a sample. The shape of the PDF explains how likely it is that an observed value might occur.

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model.