Results 61 to 70 of about 16,277 (238)
An Iterative Reduced KPCA Hidden Markov Model for Gas Turbine Performance Fault Diagnosis
Energies, 2018 To improve gas-path performance fault pattern recognition for aircraft engines, a new data-driven diagnostic method based on hidden Markov model (HMM) is proposed.
Feng Lu +3 more
doaj +1 more source
Heavy Tailed Approximate Identities and σ-stable Markov Kernels [PDF]
Potential Analysis, 2017 The aim of this paper is to present some results relating the properties of stability, concentration and approximation to the identity of convolution through not necessarily mollification type families of heavy tailed Markov kernels. A particular case is provided by the kernels $K_t$ obtained as the $t$ mollification of $L^{σ(t)}$ selected from the ...
Aimar, Hugo Alejandro +2 more
openaire +3 more sources
Extreme conditional quantile estimation for time series
Canadian Journal of Statistics, EarlyView.Abstract We consider the estimation of an extreme conditional quantile QY(1−p|x0)$$ {Q}_Y\left(1-p|{x}_0\right) $$ for a heavy‐tailed distribution in the case of a strictly stationary time series (Xt,Yt)t∈ℤ$$ {\left({X}_t,{Y}_t\right)}_{t\in \mathbb{Z}} $$. Here, QY(·|x0)$$ {Q}_Y\left(\cdotp |{x}_0\right) $$ denotes the conditional quantile function of
Yuri Goegebeur +2 more
wiley +1 more source
Entropy, 2004 We define heat kernel measure on punctured spheres. The random field which is got by this procedure is not Gaussian. We define a stochastic line bundle on the loop space, such that the punctured sphere corresponds to a generalized parallel transport on ...
Rémi Léandre
doaj +1 more source
Learning sparse mixture‐of‐experts generalized linear models in ultrahigh dimensions
Canadian Journal of Statistics, EarlyView.Abstract Motivated by the challenges of heterogeneity and high dimensionality in the analysis of modern data, we investigate continuous regularization methods for learning sparse mixture‐of‐experts generalized linear models (MoE‐GLM). Although there are foundational results about regularized estimators in a broad class of regression models including ...
Pengqi Liu, Abbas Khalili
wiley +1 more source
Rate Functions for Symmetric Markov Processes via Heat Kernel [PDF]
Potential Analysis, 2016 By making full use of heat kernel estimates, we establish the integral tests on the zero-one laws of upper and lower bounds for the sample path ranges of symmetric Markov processes. In particular, these results concerning on upper rate bounds are applicable for local and non-local Dirichlet forms, while lower rate bounds are investigated in both ...
Shiozawa, Yuichi, Wang, Jian
openaire +2 more sources
Species traits mediate terrestrial mammal density responses to human impacts
Ecography, EarlyView.Human activities are reshaping ecosystems, but their effects on species population density remain poorly understood. Most studies focus on species presence–absence, thus limiting insight into how anthropogenic pressures affect population density. Emerging evidence suggests that responses of natural populations to human disturbance are highly variable ...
Luca Santini +13 more
wiley +1 more source
IEEE Access, 2018 Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang +3 more
doaj +1 more source
Predicting connectivity from movement trajectories and step selection
Ecography, EarlyView.Predicting and mapping connectivity are essential for ecology and conservation in the face of environmental change. Yet connectivity modeling is challenging because it requires understanding how organisms successfully move across complex landscapes.
Robert J. Fletcher Jr +8 more
wiley +1 more source
A Probablistic Origin for a New Class of Bivariate Polynomials
Symmetry, Integrability and Geometry: Methods and Applications, 2008 We present here a probabilistic approach to the generation of new polynomials in two discrete variables. This extends our earlier work on the 'classical' orthogonal polynomials in a previously unexplored direction, resulting in the discovery of an ...
Michael R. Hoare, Mizan Rahman
doaj +1 more source