Probability Distribution Estimation Task
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A Probability Distribution Estimation Task is a parameter estimation task that fits the shape parameters of a probability function family.
- AKA: Estimating a Probability Distribution.
- Context:
- It can be solved by a Probability Distribution Estimation System (that implements a probability distribution estimation algorithm).
- It can range from being a Discrete Probability Distribution Estimation Task to being a Continuous Probability Distribution Estimation Task.
- It can range from being a Parametric Probability Distribution Estimation Task to being a Nonparametric Probability Distribution Estimation Task.
- It can range from being a Joint Probability Distribution Estimation Task to being a Conditional Probability Distribution Estimation Task.
- Example(s):
- “Given Binomial process <math)B(n,p)</math> to [math]\displaystyle{ n }[/math] observations X (with [math]\displaystyle{ s }[/math] success observations) for slot machine Y. What is the maximum likelihood of [math]\displaystyle{ p }[/math]? for the beta-binomial distribution [math]\displaystyle{ B(n,p,s) }[/math]?"
- See: Probability Density Estimation Task, Discrete Probability Function Fitting.