Probabilistic modeling

Probabilistic modeling

Log-t distribution

The log-t distribution models the uncertainty about positive-valued quantities that follow a log-normal distribution with unknown mean and standard deviation.
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Probabilistic modeling

Normal-gamma distribution

The Normal-gamma distribution serves as conjugate prior for a Normal distribution with unknown mean and standard deviation. As parameters for the prior, the prior mean and variance can be used, along with the number of associated (pseudo-)observations.
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Probabilistic modeling

Poisson process: post-processing

Use our web app to quantify the uncertainty about the rate of a Poisson process based on observing a specific number of event occurrences within a given time.
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Probabilistic modeling

What is a Poisson process?

A Poisson process is used to model the occurrence of independent random events along a continuous axis. It is a very important stochastic process in probabilistic modeling.
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