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A GENERAL THEORY FOR ORTHOGONAL ARRAY BASED LATIN HYPERCUBE DESIGNS
Functional decomposition Latin hypercube design orthog- onal array statistical property
2016/1/26
Orthogonal array based Latin hypercube designs (LHDs) are popularly adopted for computer experiments. Because of their stratification on multivariate margins in addition to univariate uniformity, the ...
Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles Matrices
Optimal reinsurance Distortion risk measure Reinsurance pre- mium principle Wang’s premium principle VaR TVaR
2016/1/25
Recently the optimal reinsurance strategy concerning the insurer’s risk attitude and the reinsurance premium principle is an interesting topic. This paper discusses the optimal reinsurance problem wit...
Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles Matrices
Optimal reinsurance Distortion risk measure Wang’s premium principle VaR TVaR
2016/1/20
Recently the optimal reinsurance strategy concerning the insurer’s risk attitude and the reinsurance premium principle is an interesting topic. This paper discusses the optimal reinsurance problem wit...
Entropy and Mutual Information for Markov Channels with General Inputs
Entropy Mutual Information Markov Channels General Inputs
2015/7/8
We study new formulas based on Lyapunov exponents for entropy, mutual information, and capacity of finite state discrete time Markov channels. We also develop a method for directly computing mutual in...
Structural Characterization of Taboo-Stationarity for General Processes in Two-sided Time
Quasi-stationarity
2015/7/8
This note considers the taboo counterpart ofstationarity. A general stochastic process in two-sided time is de.ned to be taboo-stationary if its global distribution does not change by shifting the ori...
Capacity of Finite State Markov Channels with General Inputs
Capacity Finite State Markov Channels General Inputs
2015/7/8
We study new formulae based on Lyapunov exponents for entropy, mutual information, and capacity of finite state discrete time Markov channels. We also develop a method for directly computing mutual in...
Opportunities and Challenges in Using Online Preference Data for Vehicle Pricing: A Case Study at General Motors
Opportunities Challenges Online Preference Data Vehicle Pricing General Motors
2015/7/6
Developed by General Motors (GM), the Auto Choice Advisor web site (http://www. autochoiceadvisor.com) recommends vehicles to consumers based on their requirements and budget constraints. Through the ...
Best-fit quasi-equilibrium ensembles: a general approach to statistical closure of underresolved Hamiltonian dynamics
Reduce model Hamiltonian dynamics system model reduction space
2014/12/24
A new method of deriving reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a set of resolved variables that define a mod...
Funding General Education Classes: Alternatives to Meet Current UMass Needs
Funding General Education Classes Meet Current UMass Needs
2014/10/20
The University of Massachusetts has identified general education requirements as being an important component of undergraduate student education. These requirements prepare them for their undergraduat...
A general approach of least squares estimation and optimal filtering
Least squares Optimal filtering Matched filter Noise Optimization Power Spectrum Density
2013/6/17
The least squares method allows fitting parameters of a mathematical model from experimental data. This article proposes a general approach of this method. After introducing the method and giving a fo...
A general approach to the joint asymptotic analysis of statistics from sub-samples
Empirical processes sub-sampling,self-normalization change point weak con-vergence Time series compact differentiability
2013/6/14
In time series analysis, statistics based on collections of estimators computed from sub-samples play a crucial role in an increasing variety of important applications. Proving results about the joint...
A General Bernstein--von Mises Theorem in semiparametric models
A General Bernstein von Mises Theorem semiparametric models
2013/6/14
A Bernstein-von Mises theorem is derived for general semiparametric functionals. The result is applied to a variety of semiparametric problems, in i.i.d. and non-i.i.d. situations. In particular, new ...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Model-based dose finding under model uncertainty using general parametric models
Model-based model uncertainty parametric models
2013/6/13
Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally distributed, homosce...
The problem of estimating the number of unique types or distinct species in a group occurs in many fields, but is not a straightforward one. Given an arbitrary probabilistic distribution of entries to...