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Comparing Interval-Valued Estimations with Point-Valued Estimations
2016In the last decade, numerous proposals have been made to deal with imprecision in estimation problems. Those approaches, many of which involve dealing with interval-valued outputs, deal with the subtle difference between uncertainty and imprecision.
Hugo Saulnier +2 more
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Estimating Loan‐to‐Value Distributions
Real Estate Economics, 2015We estimate a model of house prices, combined loan‐to‐value ratios (CLTVs) and trade and foreclosure behavior. House prices are only observed for traded properties and trades are endogenous, creating sample‐selection problems for existing approaches to estimating CLTVs.
Korteweg, Arthur, Sørensen, Morten
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2005
KNNimpute is a fast, robust, and accurate method of estimating missing values for microarray data. Both KNNimpute and SVDimpute methods far surpass the currently accepted solutions (filling missing values with zeros or row average) by taking advantage of the structure of microarray data to estimate missing expression values.
Olga G. Troyanskaya +2 more
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KNNimpute is a fast, robust, and accurate method of estimating missing values for microarray data. Both KNNimpute and SVDimpute methods far surpass the currently accepted solutions (filling missing values with zeros or row average) by taking advantage of the structure of microarray data to estimate missing expression values.
Olga G. Troyanskaya +2 more
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2021
In the statistical viewpoint, any unknown parameter can be considered as a random variable. This means that an unknown response (the missing answer) is a random variable that may take different values from the relevant range.
Nezameddin Faghih +2 more
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In the statistical viewpoint, any unknown parameter can be considered as a random variable. This means that an unknown response (the missing answer) is a random variable that may take different values from the relevant range.
Nezameddin Faghih +2 more
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2002
Mobile code languages facilitate the transmission of code between remote sites in a system. A piece of code which is generated at one site can be transmitted for execution at another site which exhibits characteristics different from its place of origin. This poses implementation challenges for mobile code languages.
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Mobile code languages facilitate the transmission of code between remote sites in a system. A piece of code which is generated at one site can be transmitted for execution at another site which exhibits characteristics different from its place of origin. This poses implementation challenges for mobile code languages.
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Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems, 1986
In estimating minimax values, an important topic in the study of heuristic game tree searches, a pathological phenomenon sometimes results when the conventional minimax procedure is used as a back-up process. In this paper exact methods are derived for two different games, one using product-propagation rules as a back-up process and another not using ...
C H Tzeng, P Purdom
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In estimating minimax values, an important topic in the study of heuristic game tree searches, a pathological phenomenon sometimes results when the conventional minimax procedure is used as a back-up process. In this paper exact methods are derived for two different games, one using product-propagation rules as a back-up process and another not using ...
C H Tzeng, P Purdom
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Journal of Information and Optimization Sciences, 1996
Abstract Suppose we have a sequence of independent and identically distributed random variables X 1, X 2,… from an absolutely continuous distribution F(x; θ). The corresponding sequence of record values X(1), X(2), … will be used to estimate the parameter θ. The results of these estimates will be compared to those when using the original data.
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Abstract Suppose we have a sequence of independent and identically distributed random variables X 1, X 2,… from an absolutely continuous distribution F(x; θ). The corresponding sequence of record values X(1), X(2), … will be used to estimate the parameter θ. The results of these estimates will be compared to those when using the original data.
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2011
This chapter reviews the recent developments of Value at Risk (VaR) estimation. In this survey, the most available univariate and multivariate methods are presented. The robustness and accuracy of these estimation methods are investigated based on the simulated and real data.
Ying Chen, Jun Lu
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This chapter reviews the recent developments of Value at Risk (VaR) estimation. In this survey, the most available univariate and multivariate methods are presented. The robustness and accuracy of these estimation methods are investigated based on the simulated and real data.
Ying Chen, Jun Lu
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