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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
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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...
On Functional Central Limit Theorems for Semi-Markov and Related Processes
Semi-Markov processes Markov chains Central limit theorem Martingales Discrete-event systems
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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...
Modules over the small quantum group and semi-infinite flag manifold
Abnormal manifold bundle of semi-infinite flag subclass sheaf quantum
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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
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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
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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.
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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
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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.
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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
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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
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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
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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...
Semi-parametric dynamic time series modelling with applications to detecting neural dynamics
Dynamic time series modeling change-point testing Bayesian statistics statistics for neural data
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2010/11/8
This paper illustrates novel methods for nonstationary time se-ries modeling along with their applications to selected problems in neuroscience. These methods are semi-parametric in that inferences ar...
Non-Negative Integer-Valued Semi-Selfsimilar Processes
Semi-selfsimilar process Levy process Semi-stable law integer-valuedprocess auto-regressive time series
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2010/4/27
Non-negative integer-valued semi-selfsimilar processes are introduced. Levy
processes in this class are characterized. Its relation to an AR(1) scheme is derived.
A goodness-of-fit test for parametric and semi-parametric models in multiresponse regression
additive regression bootstrap empirical likelihood goodness of fit infinite-dimensional parameter kernel estimation monotone regression
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2010/3/9
We propose an empirical likelihood test that is able to test the goodness of fit of a class of parametric and semi-parametric multiresponse regression models. The class includes as special cases
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Semi-stable and self-decomposable measures on separable Banach spaces
Semi-stable and self-decomposable measures separable Banach spaces
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2009/9/24
Semi-stable and self-decomposable measures on separable Banach spaces。