Results 121 to 130 of about 92,555 (240)
Bayesian Inference for Spatially‐Temporally Misaligned Data Using Predictive Stacking
ABSTRACT Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is challenging due to the complex nature of exposure data. Recent technological advances have led to the collection of various indicators of air pollution at increasingly
Soumyakanti Pan, Sudipto Banerjee
wiley +1 more source
Extension of Huygens type inequalities for Bessel and modified Bessel Functions
In this paper, new sharpened Huygens type inequalities involving Bessel and modified Bessel functions of the first kinds are ...
openaire +2 more sources
Special Relativity via Modified Bessel Functions
The recursive formulas of modified Bessel functions give the relativistic expressions for energy and momentum. Modified Bessel functions are solutions to a continuous time, one-dimensional discrete jump process. The jump process is analyzed from two inertial frames with a relative constant velocity; the average distance of a particle along the chain ...
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Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data
ABSTRACT Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that links misaligned data to a continuous‐domain model through an iteratively linearised integration scheme implemented with the Integrated Nested Laplace Approximation (
Man Ho Suen, Mark Naylor, Finn Lindgren
wiley +1 more source
This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced.
Jiajie Kong, Robert Lund
wiley +1 more source
Vector wind profile gust model [PDF]
A five parameter gamma distribution (BGD) having two shape parameters, two location parameters, and a correlation parameter is investigated. This general BGD is expressed as a double series and as a single series of the modified bessel function, and ...
Adelfang, S. I.
core +1 more source
A Mixture Transition Distribution Modeling for Higher‐Order Circular Markov Processes
ABSTRACT This study considers the stationary higher‐order Markov process for circular data by employing the mixture transition distribution modeling. The underlying circular transition distribution is based on Wehrly and Johnson's bivariate joint circular models.
Hiroaki Ogata, Takayuki Shiohama
wiley +1 more source
Semiparametric regression for circular response with application in ecology
ABSTRACT A regression model for a circular response variable depending on a linear or a circular predictor is presented in this paper. The conditional density belongs to a parametric flexible family that allows for asymmetry and varying peakedness around the modal direction.
Jose Ameijeiras‐Alonso, Irène Gijbels
wiley +1 more source
On goodness‐of‐fit testing for self‐exciting point processes
Abstract Despite the wide usage of parametric point processes in theory and applications, a sound goodness‐of‐fit procedure to test whether a given parametric model is appropriate for data coming from a self‐exciting point process has been missing in the literature.
José Carlos Fontanesi Kling +1 more
wiley +1 more source
The extension of interval-valued and real-valued functions known as fuzzy interval-valued function (FIVF) has made substantial contributions to the theory of interval analysis.
Yaqun Niu +7 more
doaj +1 more source

