Barankin Vector Locally Best Unbiased Estimates

نویسنده

  • Bruno Cernuschi-Frías
چکیده

The Barankin bound is generalized to the vector case in the mean square error sense. Necessary and sufficient conditions are obtained to achieve the lower bound. To obtain the result, a simple finite dimensional real vector valued generalization of the Riesz representation theorem for Hilbert spaces is given. The bound has the form of a linear matrix inequality where the covariances of any unbiased estimator, if these exist, are lower bounded by matrices depending only on the parametrized probability distributions.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Barankin Bounds on Parameter Estimation Accuracy Applied to Communications and Radar Problems

The Schwartz Inequality is used to derive the Barankin lower bounds on the covariance matrix of unbiased estimates of a vector parameter, The bound is applied to communications and radar problems in which the unknown parameter is imbedded in a signal of known form and observed in the presence of additive white Gaussian noise. Within this context it is shown that the Barankin bound reduces to th...

متن کامل

Ben–gurion University of the Negev Faculty of Engineering Sciences

In this thesis, the problem of minimum-variance unbiased (MVU) parameter estimation in low signal-to-noise ratios (SNRs) or few number of samples was studied. Performance lower bounds are commonly used in statistical signal processing for system design and analysis. In most practical problems there exists a threshold SNR below which the performance of the estimators, such as the maximum likelih...

متن کامل

Comparison of approaches for estimating reliability of individual regression predictions

The paper compares different approaches to estimate the reliability of individual predictions in regression. We compare the sensitivity-based reliability estimates developed in our previous work with four approaches found in the literature: variance of bagged models, local cross-validation, density estimation, and local modeling. By combining pairs of individual estimates, we compose a combined...

متن کامل

Matroid Regression

We propose an algebraic combinatorial method for solving large sparse linear systems of equations locally that is, a method which can compute single evaluations of the signal without computing the whole signal. The method scales only in the sparsity of the system and not in its size, and allows to provide error estimates for any solution method. At the heart of our approach is the so-called reg...

متن کامل

Time Series Regression Models with Locally Stationary Disturbance

Time series linear regression model with the stationary residuals has been studied in many fields, and well established. However, the stationary assumption on the residuals seems to be restrictive. Therefore, we extend the model to the case when the residuals are locally stationary. The best linear unbiased estimator (BLUE) of coefficient vector contains the residual covariance matrix which is ...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1706.10062  شماره 

صفحات  -

تاریخ انتشار 2017