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Expectation-maximization_algorithm

Expectation-maximization algorithm From Sterwiki In statistical computing, an expectation-maximization (EM) algorithm is an algorithm for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an expectation (E) step, which computes the expected value of the latent variables, and a maximization (M) step, whic... : Expectation-maximization_algorithm

Estimator

Estimator From Wikipedia, the free encyclopedia. In statistics, an estimator is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. Many different estimators are possible for an... : Estimator

Claude_Duplain

Claude Duplain From Sterwiki Claude Duplain (born January 10, 1954) is a Canadian politician. He was elected as a member of the Liberal Party of Canada during the 37th Parliament. Claude Duplain has been president of Construction du Grand Portneuf, a general construction company, since 1996. He is deeply involved in the economic develo... : Claude_Duplain

Mode_choice

Mode choice From Sterwiki Mode choice analysis is the third step in the conventional four-step transportation planning model, following trip generation and trip distribution but before route assignment. Trip distribution's zonal interchange analysis yields a set of origin destination tables which tells where the trips will be made, mode choice analysis allo... : Mode_choice

Mean_squared_error

Mean squared error From Sterwiki In statistics the mean squared error of an estimator T of an unobservable parameter θ is operatorname{MSE}(T)=operatorname{E}((T- heta)^2), i.e., it is the expected value of the square of the 'error'. The 'error' is the amount by which the estimator differs from the quantity to be estimated. ... : Mean_squared_error
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