Resource Library

This example explains how to use the Binomial and Bernoulli distributions.

The RiskCumul function provides a high degree of flexibility in describing the distribution of a continuous uncertain quantity. This example explains how to use it as an alternative to the RiskGeneral and RiskHistogram functions.

This example explains how to use the RiskDiscrete function which is used when you want to model an uncertain quantity with a finite -- that is, discrete -- set of possible values and corresponding probabilities. It is very general in that there can be any number of possible values, they can be any values (positive or negative, equally spaced or not), and the probabilities can be any positive values that sum to 1. This means that the distribution can have any shape: symmetric, skewed, or even multi-modal.

This example explains how to use the RiskDUniform and RiskIntUniform functions to generate equally likely integer values.

This example explains how to use the Exponential distribution.

This example explains how to use the RiskExtValue and RiskExtValueMin functions which are widely used in the Extreme Value Theory.

This example explains how to use the Gamma and Erlang distributions.

This example explains how to use the RiskGeneral and RiskHistogrm functions to to provide a high degree of flexibility in describing the distribution of a continuous uncertain quantity.

This example explains how to use the RiskGeomet function.

This example explains how to use the RiskHypergeo function.

This example explains how to use the RiskInvGauss function.

This example explains how to use the RiskJohnson function.