Here we offer a whole host of modeling techniques that EpiX Analytics has applied in real world problems in a wide variety of fields from insurance to banking, epidemiology to engineering, human health to utilities, oil, gas and diamond exploration to railways management, etc.

This section also includes other resources such as past webinars and worked examples of real-life models published by our team.

A great pleasure of risk modeling is to find out that techniques used in one field are just right for a problem in another. We'd like to encourage you to browse through these models for ideas you might find useful in your work.

- A continuous variable with a long tail distribution
- A discrete variable with a long tail distribution
- The number of successes in a certain number of trials
- The number of events in a specific period
- The number of failures until a certain number of successes have been achieved
- Uncertainty about a probability, fraction or prevalence
- Modeling an extreme value for a variable
- Calculating the area under a curve or volume under a surface
- Creating a custom distribution of the lifetime of a device
- The state of individuals sampled from a large or infinite population
- The state of individuals sampled from a small population
- Distance to the nearest neighbor when individuals are randomly distributed over an area or space
- Modeling a risk event
- Multivariate trials
- Stress and strength
- Time until an event occurs, or the lifetime of a device
- The probability of an event
- Uncertainty about the rate at which things occur in time or space
- The distribution of particles in a volume when the volume is portioned out
- Sampling from a liquid containing suspended particles
- Lifetime of a device of several components
- Percent operating time of a machine with breakdowns and repairs
- Times of arrivals and wait times in a queuing system
- Predicting results of a random survey, and uncertainty about results
- Comparing uncertain properties of two or more individuals
- Uncertainty about a population statistic
- Uncertainty about a population size
- Rare event risks