A new sequential approximation method
Barry Kurt Moser,Douglas Faries +1 more
2
TL;DR: In this article, a sequential method for estimating the expected value of a random variable is proposed using a parametric model, the updating formula is based on the maximum likelihood estimators of the roots of the expectation value function.
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About: This article is published in Journal of Statistical Planning and Inference. The article was published on 30 Oct 1996. and is currently open access. The article focuses on the topics: Sequential estimation & Estimator.
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Citations
Estimation of Extreme Quantiles Based on Sensitivity Tests: A Comparative Study
TL;DR: In this article, the authors evaluate and compare the effectiveness of several sequential-design sensitivity tests in this setting through Monte Carlo simulation and show that, when the model is correctly specified, tests designed to estimate the model parameters and subsequently to estimate quantiles as a function of the model parameter provided more accurate quantile estimates than tests designed for estimating a specified quantile.
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A new sequential approximation method
Barry Kurt Moser,Douglas Faries +1 more
TL;DR: In this article, a sequential method for estimating the expected value of a random variable is proposed using a parametric model, the updating formula is based on the maximum likelihood estimators of the roots of the expectation value function.
2
References
A Stochastic Approximation Method
Herbert Robbins,Sutton Monro +1 more
TL;DR: In this article, a method for making successive experiments at levels x1, x2, ··· in such a way that xn will tend to θ in probability is presented.
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Approximation Theorems of Mathematical Statistics
Robert Serfling
- 08 Dec 1980
TL;DR: In this paper, the basic sample statistics are used for Parametric Inference, and the Asymptotic Theory in Parametric Induction (ATIP) is used to estimate the relative efficiency of given statistics.
5.7K
A Method for Obtaining and Analyzing Sensitivity Data
TL;DR: This paper provides an alternative technique based on a special system for obtaining sensitivity of dosage-mortality data that has some advantages when observations must be taken on individuals rather than groups of individuals, and it may be preferred in certain other situations.
1.2K
Least Squares Estimates in Stochastic Regression Models with Applications to Identification and Control of Dynamic Systems
Tze Leung Lai,C. Z. Wei +1 more
TL;DR: In this article, strong consistency and asymptotic normality of least squares estimates in stochastic regression models are established under certain weak assumptions on the Stochastic regressors and errors.
On a Stochastic Approximation Method
TL;DR: Asymptotic properties for the Robbins-Monro [1] procedure of stochastically solving the equation $M(x) = \alpha$ are established in detail in this article.