دالة الاحتماليَّة [Likelihood function]

مصطلحات ذات صلة: Bayes factor, Bayesian inference, Bayesian parameter estimation, Posterior distribution, Prior distribution **Alternative definition:** For a more statistically-informed definition, given a parametric model specified by a probability (densidity) function f(x|theta), a likelihood *for* a statistical model is defined by the same formula as the density except that the roles of the data *x* and the parameter *theta* are interchanged, and thus the likelihood can be considered a function of *theta* for fixed data *x*. Here, then, the likelihood function would describe a curve or hypersurface whose peak, if it exists, represents the combination of model parameter values that maximize the probability of drawing the sample obtained.

مراجع:

• Dienes, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference. Macmillan International Higher Education.
• Hogg, D., Bovy, J., & Lang, D. (2010). Data analysis recipes: Fitting a model to data. arXiv:1008.4686 [astro-ph.IM].
• Geyer, C. J. (2003). Maximum Likelihood in R (pp. 1–9). Open Science Framework.
• Geyer, C. J. (2007). Stat 5102 Notes: Maximum Likelihood (pp. 1–8). Open Science Framework.
• Huber, C. (2016). The Stata Blog: Introduction to Bayesian statistics, part 1: The basic concepts. In The Stata Blog. https://blog.stata.com/2016/11/01/introduction-to-bayesian-statistics-part-1-the-basic-concepts/

كتبه وراجعه: Alaa AlDoh, Dominik Kiersz, Graham Reid, Sam Parsons, Flávio Azevedo