Exact and approximate REML for heteroscedastic regression
نویسندگان
چکیده
منابع مشابه
An Efficient Algorithm for REML in Heteroscedastic Regression∗
This paper considers REML (residual or restricted maximum likelihood) estimation for heteroscedastic linear models. An explicit algorithm is given for REML-scoring which yields the REML estimates together with their standard errors and likelihood values. The algorithm includes a Levenberg-Marquardt restricted step modification which ensures that the REML-likelihood increases at each iteration. ...
متن کاملActive Heteroscedastic Regression
An active learner is given a model class Θ, a large sample of unlabeled data drawn from an underlying distribution and access to a labeling oracle that can provide a label for any of the unlabeled instances. The goal of the learner is to find a model θ ∈ Θ that fits the data to a given accuracy while making as few label queries to the oracle as possible. In this work, we consider a theoretical ...
متن کاملEfficient Quantile Regression for Heteroscedastic Models
Quantile regression provides estimates of a range of conditional quantiles. This stands in contrast to traditional regression techniques, which focus on a single conditional mean function. Lee et al. (2012) proposed efficient quantile regression by rounding the sharp corner of the loss. The main modification generally involves an asymmetric l2 adjustment of the loss function around zero. We ext...
متن کاملV-optimal designs for heteroscedastic regression
We obtain V-optimal designs, which minimize the average variance of predicted regression responses, over a finite set of possible regressors. We assume a general and possibly heterogeneous variance structure depending on the design points. The variances are either known (or at least reliably estimated) or unknown. For the former case we exhibit optimal static designs; our methods are then modif...
متن کاملSingle index quantile regression for heteroscedastic data
Quantile regression (QR) is becoming increasingly popular due to its relevance in many scientific investigations. Linear and nonlinear QR models have been studied extensively, while recent research focuses on the single index quantile regression (SIQR) model. Compared to the single index mean regression problem, the fitting and the asymptotic theory of the SIQR model are more complicated due to...
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: Statistical Modelling
سال: 2001
ISSN: 1471-082X,1477-0342
DOI: 10.1177/1471082x0100100301