A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from...

neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model. Noam Chomsky did pioneering...

statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences...

In statistics, model specification is part of the process of building a statistical model: specification consists of selecting an appropriate functional...

degree of statistical modelling. Terminology is inconsistent, but three major types can be distinguished: A generative model is a statistical model of the...

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called...

increases. Statistical models specify a set of statistical assumptions and processes that represent how the sample data are generated. Statistical models have...

social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of...

for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data...

mixed model, mixed-effects model or mixed error-component model is a statistical model containing both fixed effects and random effects. These models are...

Statistical Modelling is a bimonthly peer-reviewed scientific journal covering statistical modelling. It is published by SAGE Publications on behalf of...

of models for which substantial reduction in the complexity of the related statistical theory is possible. For the regression case, the statistical model...

In statistics, a zero-inflated model is a statistical model based on a zero-inflated probability distribution, i.e. a distribution that allows for frequent...

Principles of statistical inference. Cambridge New York: Cambridge University Press. ISBN 978-0-521-68567-2. Freedman, David A.(2005). Statistical Models: Theory...

corresponding statistical model is said to be regular; otherwise, the statistical model is said to be singular. Examples of singular statistical models include...

Ising model (or Lenz–Ising model), named after the physicists Ernst Ising and Wilhelm Lenz, is a mathematical model of ferromagnetism in statistical mechanics...

When classification is performed by a computer, statistical methods are normally used to develop the algorithm. Often, the individual observations are...

learning and more generally statistical analysis, this may be the selection of a statistical model from a set of candidate models, given data. In the simplest...

In statistics, a logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent...

thing Scientific modelling – Scientific activity that produces models Statistical model – Type of mathematical model Statistical model validation – Evaluating...

Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the parameters of the posterior distribution...

Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear...

measurements and tests occur simultaneously in one statistical estimation procedure, where all the model coefficients are calculated using all information...

pricing and portfolio management, the Fama–French three-factor model is a statistical model designed in 1992 by Eugene Fama and Kenneth French to describe...

trained statistical language models. In 2009, in most language processing tasks, statistical language models dominated over symbolic language models because...

extensions, and applications in statistical modelling; and bring together statisticians working on statistical modelling from various disciplines. The principal...

Jeremy M. G. (1989). "Robust Statistical Modeling Using the t Distribution" (PDF). Journal of the American Statistical Association. 84 (408): 881–896...

econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current...

statistic (singular) or sample statistic is any quantity computed from values in a sample which is considered for a statistical purpose. Statistical purposes...

parametric model or parametric family or finite-dimensional model is a particular class of statistical models. Specifically, a parametric model is a family...