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Ocean State Estimation and Prediction in Support of Oceanographic Research
Estimation and Prediction Oceanographic Researc
2015/8/5
The ocean is changing vigorously on a wide range of time and space scales. This variability leads to substantial problems in observing and modeling (simulating) the rapidly changing flow field, the oc...
Antiallergic Activity of Substituted Benzamides:Characterization,Estimation and Prediction
Molecular Descriptors Family on Structure-Activity Relationships (MDF-SAR) Substituted N 4-methoxyphenyl benzamides Antiallergic activity Multiple linear regression (MLR)
2015/7/29
Antiallergic activity of twenty-three substituted N 4-methoxyphenyl benzamides was model by the use of an original methodology. After sketching out the compounds structure and creating the file with t...
PAC-Bayesian Estimation and Prediction in Sparse Additive Models
Additive models sparsity regression estimation PAC-Bayesian bounds oracle inequality MCMC stochastic search.
2012/9/17
The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption (p nparadigm).A PAC-Bayesian strategy is investigated, delivering oracle inequaliti...
Robust quantile estimation and prediction for spatial processes
Spatial processes Kernel estimate Conditional quantile Spatial prediction
2010/3/9
In this paper, we present a statistical framework for modeling conditional quantiles of spatial processes
assumed to be strongly mixing in space. We establish the L1 consistency and the asymptotic no...
A Hierarchical Bayes Approach to Estimation and Prediction for Time Series of Counts
A Hierarchical Bayes Approach Estimation Prediction Time Series of Counts
2009/9/17
A Hierarchical Bayes Approach to Estimation and Prediction for Time Series of Counts。
Regression Estimation and Prediction in Continuous Time
Continuous time nonparametric prediction nonparametric regression
2009/3/5
This paper studies the nonparametric regression estimation and the prediction problem for continuous-time observations. The almost sure convergence of a kernel regression estimator and the associated ...