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IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Semiparametric regression time series Particulate Matter (PM) Generalized Additive Model Generalized Linear Model Mean Squared Error Bandwidth Selection
2015/8/21
In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders conce...
Connections Between Semi-Infinite and Semidefinite Programming
Connections Between Semi-Infinite Semidefinite Programming
2015/7/10
Some interesting semi-infinite optimization problems can be reduced to semidefinite optimization problems, and hence solved efficiently using recent interior-point methods. In this paper we discuss se...
Importance Sampling Using the Semi-Regenerative Method
Importance Sampling Semi-Regenerative Method
2015/7/8
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate the expected cumulative reward until hitting a fixed set of states for a discrete-time Markov chain o...
On Functional Central Limit Theorems for Semi-Markov and Related Processes
Semi-Markov processes Markov chains Central limit theorem Martingales Discrete-event systems
2015/7/6
The semi-Markov process (SMP) has long been used as a model for the underlying process of a discrete-event stochastic system. Important refinements of this model include the continuous-time Markov cha...
Laws of Large Numbers and Functional Central Limit Theorems for Generalized Semi-Markov Processes
Central limit theorem Discrete-event stochastic systems Generalized semi-Markov processes
2015/7/6
Because of the fundamental role played by generalized semi-Markov processes (GSMPs) in the modeling and analysis of complex discrete-event stochastic systems, it is important to understand the conditi...
The Semi-Regenerative Method of Simulation Output Analysis
Variance reduction effi ciency improvement importance sampling bias reduction
2015/7/6
We develop a class of techniques for analyzing the output of simulations of a semi-regenerative process. Called the semi-regenerative method, the approach is a generalization of the regenerative metho...
Modules over the small quantum group and semi-infinite flag manifold
Abnormal manifold bundle of semi-infinite flag subclass sheaf quantum
2014/12/25
We develop a theory of perverse sheaves on the semi-infinite flag manifold G((t))/N((t)) · T[[t]], and show that the subcategory of Iwahori-monodromy perverse sheaves is equivalent to the regular bloc...
Functional and Parametric Estimation in a Semi- and Nonparametric Model with Application to Mass-Spectrometry Data
Local linear regression Bandwidth selection Nonparamet-ric estimation
2013/6/13
Motivated by modeling and analysis of mass-spectrometry data, a semi- and nonparametric model is proposed that consists of a linear parametric component for individual location and scale and a nonpara...
Variational Semi-blind Sparse Deconvolution with Orthogonal Kernel Bases and its Application to MRFM
Variational Bayesian inference posterior image distribution image reconstruction hyperparameter estimation MRFM experiment
2013/5/2
We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known. To solve this semi-blind d...
Semi-supervised Clustering Ensemble by Voting
clustering ensembles semi supervised clustering consensus function ensemble generation.
2012/9/18
Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of ...
Bayesian semi-parametric forecasting with penalised splines and autoregressive errors
splines, autoregressive errors, semi-parametric regression, Bayesian
2012/9/18
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for exible regression models that are able to c...
Estimation of Scale and Hurst Parameters of Semi-Selfsimilar Processes
Hurst estimation Discrete self-similarity Fractional Brownian motion Semi-selfsimilar processes Scale parameter.
2012/9/19
The characteristic feature of semi-selfsimilar process is the invariance of its finite dimensional distributions by certain dilation for specific scaling factor. Estimating the scale parameter λand th...
Semi-Blind System Identification in Wireless Relay Networks via Gaussian Process Iterated Conditioning on the Modes Estimation
Relay networks System Identification Gaussian processes Kernel methods
2011/7/7
This paper presents a flexible stochastic model developed for a class of cooperative wireless relay networks, in which the relay processing functionality is not known at the destination. The challenge...
Properties of semi-elementary imsets as sums of elementary imsets
Markov basis semi-graphoid toric ideal
2011/6/20
We study properties of semi-elementary imsets and elementary imsets introduced by
Studen´y [10]. The rules of the semi-graphoid axiom (decomposition, weak union and contraction)
for conditiona...
Semi-supervised logistic discrimination for functional data
EM algorithm Functional data analysis Model selec-tion Regularization Semi-supervised learning
2011/3/24
Multi-class classification methods based on both labeled and unlabeled functional data sets are discussed. We present semi-supervised logistic models for classification in the context of functional da...