A study to compare different methods of estimation was conducted. The goal was to provide an estimate for the number of petal colors existing in the field by using a random sample of Lycoris longituba flowers taken from the field. Three methods of estimation were used to estimate the actual number of the colors in the field. Using the variance analysis, the maximum number of colors was obtained...

First, we demonstrate how the Contraction Lemma for Rademacher averages can be used to obtain tight performance guarantees for learning methods [3]. In particular, we derive risk bounds for a greedy mixture density estimation procedure. We prove that, unlike what is suggested in the literature, the number of terms in the mixture is not a bias-variance trade-off for the performance. Our upper bo...

We introduce a simple, efficient method that improves stochastic policies for Markov decision processes. The computational complexity is the same as that of the value estimation problem. We prove that when the value estimation error is small, this method gives an improvement in performance that increases with certain variance properties of the initial policy and transition dynamics. Performance...

Background and objectives: Risk-adjusted Bernoulli control chart is one of the main tools for monitoring multistage healthcare processes to achieve higher performance and effectiveness in healthcare settings. Using parameter estimates can lead to significantly deteriorate chart performance. However, so far, the effect of estimation error on this chart in which healthcare ...

This paper accurately quantifies the way in which noise induced estimation errors are dependent on model structure, underlying system frequency response, measurement noise and input excitation. This exposes several new principles. In particular, it is shown here that when employing Output–Error model structures in a prediction-error framework, then the ensuing estimate variability in the freque...

The paper computes the reliability of estimates of image motion parameters. The use of such measures of reliability to weight motion estimates improves significantly the performance of motion analysis tasks such as the recovery of 3D structure [1, 2]. The paper relates both the estimation error variance and the stability of the estimation algorithm with the spatial gradient of the image brightn...

Motivated by the need to smooth and to summarize multiple simultaneous time series arising from networks of environmental monitors, we propose a hierarchical wavelet model for which estimation of hyperparameters can be performed by marginal maximum likelihood. The result is an empirical Bayes thresholding procedure whose results improve on those of wavethresh in terms of mean square error. We a...

[1] The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence of the error propagation into hydrological simulation. First, the error associated with the satellite-based precipitation estimates is assumed as a nonlinear function of rainfall space-...

The present paper proposes a testimation procedure using a preliminary test of significance for the estimation of the error variance for three-way layout to be used for testing a main effect in the random effects model. The risk properties of this testimation procedure have been studied under asymmetric loss function and it is observed through numerical computations that the estimator for error...

This paper addresses the problem of selecting the optimum training sequence for channel estimation in communication systems over time-dispersive channels. By processing in the frequency domain, a new explicit form of search criterion is found, the gain loss factor (GLF), which minimizes the variance of the estimation error and is easy to compute. Theoretical upper and lower bounds on the GLF ar...