Likelihood-based Imprecise Regression
نویسندگان
چکیده
منابع مشابه
An Exact Algorithm for Likelihood-Based Imprecise Regression in the Case of Simple Linear Regression with Interval Data
Likelihood-based Imprecise Regression (LIR) is a recently introduced approach to regression with imprecise data. Here we consider a robust regression method derived from the general LIR approach and we establish an exact algorithm to determine the set-valued result of the LIR analysis in the special case of simple linear regression with interval data.
متن کاملRobust regression with imprecise data
We consider the problem of regression analysis with imprecise data. By imprecise data we mean imprecise observations of precise quantities in the form of sets of values. In this paper, we explore a recently introduced likelihood-based approach to regression with such data. The approach is very general, since it covers all kinds of imprecise data (i.e. not only intervals) and it is not restricte...
متن کاملEmpirical likelihood based testing for regression
Abstract: Consider a random vector (X, Y ) and let m(x) = E(Y |X = x). We are interested in testing H0 : m ∈ MΘ,G = {γ(·, θ, g) : θ ∈ Θ, g ∈ G} for some known function γ, some compact set Θ ⊂ IR and some function set G of real valued functions. Specific examples of this general hypothesis include testing for a parametric regression model, a generalized linear model, a partial linear model, a si...
متن کاملEmpirical Likelihood Based Rank Regression Inference
Communications in Statistics Simulation and Computation Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713597237 Empirical Likelihood Based Rank Regression Inference Ellen E. Bishop a; Yichuan Zhao b a Research Triangle Institute, International, Atlanta, Georgia, USA b Department of Mathematics and Statistics...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2012
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2012.06.010