Probability Function Family Parameter Estimation Task
(Redirected from Probability Function Family Parameter Estimation)
A Probability Function Family Parameter Estimation Task is a function parameter estimation task for a parametric probability distribution.
- AKA: Parametric Probability Distribution Fitting.
- Context:
- It can range from being a Discrete Probability Distribution Parameter Estimation Task to being a Continuous Probability Distribution Parameter Estimation Task.
- It can be solved by a Probability Distribution Parameter Estimation System (that implements a probability distribution parameter estimation algorithm).
- See: Unknown Probability Distribution Parameter Estimation, Parametric Regression Algorithm.
References
2012
- (Levy, 2012) ⇒ Roger Levy. (2012). “Probabilistic Models in the Study of Language - Chapter 4: Parameter Estimation."
- QUOTE: … In this chapter we delve more deeply into the theory of probability density estimation, focusing on inference within parametric families of probability distributions (see discussion in Section 2.11.2). We start with some important properties of estimators, then turn to basic frequentist parameter estimation (maximum-likelihood estimation and corrections for bias), and finally basic Bayesian parameter estimation.
2000
- http://www.itl.nist.gov/div898/handbook/eda/section3/eda365.htm
- One common application of probability distributions is modeling univariate data with a specific probability distribution. This involves the following two steps:
- Determination of the "best-fitting" distribution.
- Estimation of the parameters (shape, location, and scale parameters) for that distribution.
- One common application of probability distributions is modeling univariate data with a specific probability distribution. This involves the following two steps: