Results 41 to 50 of about 1,524,562 (340)

Application of Square Msplit Estimation in Determination of Vessel Position in Coastal Shipping

open access: yesPolish Maritime Research, 2017
The main aim of this paper is to assess the possibility of using non-conventional geodetic estimation methods in maritime navigation. The research subject of this paper concerns robust determination of vessel’s position using a method of parameters ...
Zienkiewicz Marek Hubert   +1 more
doaj   +1 more source

Simple House Needs in Jember with Robust Small Area Estimation

open access: yesJurnal Ilmu Dasar, 2017
SAE (Small Area Estimation) is often used by researchers, especially statisticians to estimate parameters of a subpopulation which has a small sample size.
Frida Murtinasari   +2 more
doaj   +1 more source

Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-moments [PDF]

open access: yes, 2016
This paper discusses different classes of loss models in non-life insurance settings. It then overviews the class Tukey transform loss models that have not yet been widely considered in non-life insurance modelling, but offer opportunities to produce ...
Chen, Wilson Y.   +2 more
core   +3 more sources

Portfolio Selection With Robust Estimation [PDF]

open access: yesSSRN Electronic Journal, 2007
Mean-variance portfolios constructed using the sample mean and covariance matrix of asset returns perform poorly out of sample due to estimation error. Moreover, it is commonly accepted that estimation error in the sample mean is much larger than in the sample covariance matrix.
Victor DeMiguel, Francisco J. Nogales
openaire   +1 more source

SUM: Sequential Scene Understanding and Manipulation

open access: yes, 2017
In order to perform autonomous sequential manipulation tasks, perception in cluttered scenes remains a critical challenge for robots. In this paper, we propose a probabilistic approach for robust sequential scene estimation and manipulation - Sequential ...
Jenkins, Odest Chadwicke   +3 more
core   +1 more source

On Robust Linear Estimators

open access: yesThe Annals of Mathematical Statistics, 1969
Abstract : The problem of finding robust estimators for the location parameter of symmetric unimodal distributions has been the subject of much recent research. This paper is concerned with finding robust estimators which are linear functions of the ordered observations.
Gastwirth, Joseph L., Rubin, Herman
openaire   +3 more sources

The Robustness of Rasch Estimates [PDF]

open access: yesApplied Psychological Measurement, 1986
The small scale applicability of Rasch estimates was investigated under simulated conditions of guess ing and heterogeneity in item discrimination. The ac curacy of the Rasch estimates was evaluated by means of the correlation between the item/person parameters and their estimates, the standard deviations of the esti mates, and the difference as well ...
openaire   +3 more sources

Frequency Tracking and Parameter Estimation for Robust Quantum State-Estimation

open access: yes, 2011
In this paper we consider the problem of tracking the state of a quantum system via a continuous measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small
A. Doherty   +16 more
core   +1 more source

Robust Direction Estimation

open access: yesThe Annals of Statistics, 1992
The study of the stability of parameter estimates for directional data dates back to the late sixties and this paper is an interesting contribution to this domain. The authors consider rotationally symmetric models for directional data with axis of rotation \(\mu\) and concentration parameter \(\kappa\). The prototype is the von Mises distribution. The
He, Xuming, Simpson, Douglas G.
openaire   +2 more sources

Robust kernel density estimation [PDF]

open access: yes2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
We propose a method for nonparametric density estimation that exhibits robustness to contamination of the training sample. This method achieves robustness by combining a traditional kernel density estimator (KDE) with ideas from classical $M$-estimation.
JooSeuk Kim, Clayton D. Scott
openaire   +3 more sources

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