This R markdown document provide an example of how to use the uniform probability density analysis function to model site population history using dated cermic objects. For technical details of the ...

In this paper, in the light of the widely used Bayesian inference, we present a different interpretation of the BPF by expressing it as an approximation of posterior probability density functions, ...

In this paper, in the light of the widely used Bayesian inference, we present a different interpretation of the BPF by expressing it as an approximation of posterior probability density functions, ...

We propose a method for reconstructing a probability density function (pdf) from a sample of an n -dimensional probability distribution. The method works by iteratively applying some simple ...

Unlike for probability mass functions, the probability density function cannot be interpreted directly as a probability. Instead, if we visualize the graph of a pdf as a surface, then we can compute ...

The Institute of Statistical Science conducts fundamental and applied research related to statistics and probability. The Institute respects independent research of individual principal investigators, ...

Probability density function is a statistical expression defining the likelihood of a series of outcomes for a continuous variable, such as a stock or ETF return.

This will allow us to choose appropriate mathematical models to reflect various real world observances. The most common of these probability distributions is the uniform distribution. Here, all values ...