WebA focused information criterion for quantile regression is developed, analyzed, and investigated by means of a simulation study and data analysis. Key words and phrases: Quantile regression, model selection focused information criterion. Ï. Introduction Quantile regression was introduced by Koenker and Bassett (1978) as an WebSep 5, 2012 · The tolerance discussion in Chapter 5 showed that sometimes one model is best for estimating one type of estimand, whereas another model is best for another estimand. The point of view expressed via the focussed information criterion (FIC) is that a ‘best model’ should depend on the parameter under focus, such as the mean, or the …
Focused information criterion and model averaging with
WebMar 17, 2016 · The criterion minimizes the asymptotic mean squared error of the Gaussian quasi maximum likelihood estimator of the conditional variance. We show through our simulation studies that this... WebMar 20, 2024 · Claeskens and Hjort (J Am Stat Assoc 98(464):900–916, 2003) constructed the focused information criterion (FIC) using maximum likelihood estimators to facilitate the contextual selection of probability models for independently distributed observations. We generalize these results to the case of stationary, strong mixing stochastic processes … marie roach recipe for hair removal
Focused information criterion and model averaging based …
WebFeb 1, 2003 · We develop a method which for given focus parameter estimates the precision of any submodel-based estimator. The framework is that of large-sample likelihood inference. Using an unbiased estimate... WebWe first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a … WebDec 31, 2011 · Using an unbiased estimate of limiting risk, we propose a focused information criterion for model selection. We investigate and discuss properties of the … natural kitchen yoomi 個室