Estimation of Location Parameter from Two Biased Samples

Piterbarg, Leonid I.
September 2013
Applied Mathematics;Sep2013, Vol. 4 Issue 9, p1269
Academic Journal
We consider a problem of estimating an unknown location parameter from two biased samples. The biases and scale parameters of the samples are not known as well. A class of non-linear estimators is suggested and studied based on the fuzzy set ideas. The new estimators are compared to the traditional statistical estimators by analyzing the asymptotical bias and carrying out Monte Carlo simulations.


Related Articles

  • Parameter estimation in nonlinear environmental problems. Liu, Xiaoyi; Cardiff, Michael; Kitanidis, Peter // Stochastic Environmental Research & Risk Assessment;Oct2010, Vol. 24 Issue 7, p1003 

    Popular parameter estimation methods, including least squares, maximum likelihood, and maximum a posteriori (MAP), solve an optimization problem to obtain a central value (or best estimate) followed by an approximate evaluation of the spread (or covariance matrix). A different approach is the...

  • State Estimation for Target Tracking Problems with Nonlinear Kalman Filter Algorithms. Toloei, Alireza; Niazi, Saeid // International Journal of Computer Applications;Jul2014, Vol. 98, p30 

    One the most important problems in target tracking are state estimation. This paper deals on estimation of states from noisy sensor measurements. Due to important of exact estimation in tracking problems must evader position and Line Of Sight angles estimated with least error rather than actual...

  • Fuzzy Dynamic Reliability Models of Parallel Mechanical Systems Considering Strength Degradation Path Dependence and Failure Dependence. Gao, Peng; Xie, Liyang // Mathematical Problems in Engineering;5/18/2015, Vol. 2015, p1 

    Fuzzy dynamic reliability models of mechanical parallel systems with respect to stress parameters and strength parameters are developed in this paper. Strength degradation path dependence (SDPD) and failure dependence of components in the system are two main problems to be addressed in...

  • Representativeness of a Sample in Monte Carlo Method*. Bevrani, H.; Shevtsova, I. // Journal of Mathematical Sciences;Feb2015, Vol. 205 Issue 1, p27 

    The Monte Carlo method is a quite popular method of solving mathematical problems. The theoretical basis of this method is the law of large numbers and the central limit theorem. When using this method a question often arises, whether available statistical data are enough for accurate and...

  • The Propagation of Probabilistic and Possibilistic Uncertainty in a Life Cycle Assessment: A Case Study of a Naphtha Cracking Plant in Taiwan. Liu, Kevin Fong-Rey; Si-Yu Chiu; Ming-Jui Hung; Jong-Yih Kuo // International Journal of Environmental Science & Development;Dec2013, Vol. 4 Issue 6, p652 

    The use of a life cycle assessments (LCA) is dramatically increasing, partially due to the ease of use of the commercial software. However, there is a critical doubt about the credibility of the assessment results, particularly in endpoint assessments. Each phase of a LCA involves some...

  • THE VALUATION OF REAL OPTIONS IN A HYBRID ENVIRONMENT. RĘBIASZ, Bogdan // Operations Research & Decisions;2019, Vol. 29 Issue 1, p97 

    The aim of this paper is to present the possibilities and purposefulness of the application of fuzzy set theory to the valuation of real options. Owing to temporal fluctuations in the market, some input parameters in a model of a real option cannot always be expressed in a precise sense....

  • PARAMETER ESTIMATION IN MULTIPLE LINEAR REGRESSION MODELS USING RANKED SET SAMPLING. Özdemir, Yaprak Arzu; Esin, A. Alptekin // Communications Series A1 Mathematics & Statistics;2007, Vol. 56 Issue 1, p7 

    In statistical surveys, if the measurements of sampling units according to the variable under consideration is expensive in all sense, and if it is possible to rank sampling units according to the same variable by means of a method which is not expensive at all, in those cases, Ranked Set...

  • Auxiliary mixture sampling for parameter-driven models of time series of counts with applications to state space modelling. FrüHwirth-Schnatter, Sylvia; Wagner, Helga // Biometrika;Dec2006, Vol. 93 Issue 4, p827 

    We consider parameter-driven models of time series of counts, where the observations are assumed to arise from a Poisson distribution with a mean changing over time according to a latent process. Estimation of these models is carried out within a Bayesian framework using data augmentation and...

  • Isochronal sampling in non-Boltzmann Monte Carlo methods. Abreu, Charlles R. A. // Journal of Chemical Physics;10/21/2009, Vol. 131 Issue 15, p154113 

    Non-Boltzmann sampling (NBS) methods are usually able to overcome ergodicity issues which conventional Monte Carlo methods often undergo. In short, NBS methods are meant to broaden the sampling range of some suitable order parameter (e.g., energy). For many years, a standard for their...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics