Likelihood function
Likelihood Function
The Likelihood Function (pronounced: /ˈlaɪklihʊd ˈfʌŋkʃən/) is a fundamental concept in statistical inference, particularly in the field of maximum likelihood estimation.
Etymology
The term "likelihood" originates from the English language, meaning "probability" or "chance". In the context of statistics, it was first used by the English mathematician and biostatistician Ronald A. Fisher in the early 20th century.
Definition
In statistics, the likelihood function (often simply called the likelihood) measures the goodness of fit of a statistical model to a sample of data for given values of the unknown parameters. It is formed from the joint probability distribution of the sample, but viewed and used as a function of the parameters only, thus treating the random variables as fixed at the observed values.
Related Terms
- Probability Density Function: A function that describes the likelihood for a continuous random variable to take on a given value.
- Maximum Likelihood Estimation: A method of estimating the parameters of a statistical model, given observations.
- Statistical Inference: The process of using data analysis to deduce properties of an underlying probability distribution.
- Parameter Estimation: The process by which parameters of a statistical model are estimated.
See Also
External links
- Medical encyclopedia article on Likelihood function
- Wikipedia's article - Likelihood function
This WikiMD dictionary article is a stub. You can help make it a full article.
Languages: - East Asian
中文,
日本,
한국어,
South Asian
हिन्दी,
Urdu,
বাংলা,
తెలుగు,
தமிழ்,
ಕನ್ನಡ,
Southeast Asian
Indonesian,
Vietnamese,
Thai,
မြန်မာဘာသာ,
European
español,
Deutsch,
français,
русский,
português do Brasil,
Italian,
polski