Shrinkage estimation of non-negative mean vector with unknown covariance under balance loss

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices

In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is nonparametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the prior information on the population covariancematrix. Analytical results on the improvement of the propos...

متن کامل

Estimation under unknown correlation: covariance intersection revisited

This paper addresses the problem of obtaining a consistent estimate (or upper bound) of the covariance matrix when combining two quantities with unknown correlation. The combination is defined linearly with two gains. When the gains are chosen a priori, a family of consistent estimates is presented in the paper. The member in this family having minimal trace is said to be “family-optimal”. When...

متن کامل

Shrinkage Preliminary Test Estimation under a Precautionary Loss Function with Applications on Records and Censored Ddata

Shrinkage preliminary test estimation in exponential distribution under a precautionary loss function is considered. The minimum risk-unbiased estimator is derived and some shrinkage preliminary test estimators are proposed. We apply our results on censored data and records. The relative efficiencies of proposed estimators with respect to the minimum ‎risk-unbiased‎&...

متن کامل

Non-linear shrinkage estimation of large-scale structure covariance

In many astrophysical settings, covariance matrices of large data sets have to be determined empirically from a finite number of mock realizations. The resulting noise degrades inference and precludes it completely if there are fewer realizations than data points. This work applies a recently proposed non-linear shrinkage estimator of covariance to a realistic example from large-scale structure...

متن کامل

Heteroskedasticity-Autocorrelation Robust Covariance Estimation Under Non-stationary Covariance Processes

The need to estimate variance-covariance matrix in a time series regression arises often in economic applications involving macroeconomic or finance data. In this paper, we study the behavior of two most popular covariance matrix estimators, namely the Kiefer, Vogelsang and Bunzel kernel estimator without truncation (Kiefer, Vogelsang and Bunzel 2000, KVB thereafter) and standard consistent ker...

متن کامل

ذخیره 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: Journal of Inequalities and Applications

سال: 2018

ISSN: 1029-242X

DOI: 10.1186/s13660-018-1919-0