Modeling Various Survival Distributions using a Nonparametric Hypothesis Testing Based on Laplace Transform Approach with Some Real Applications. [PDF]
Gadallah AM+6 more
europepmc +1 more source
Orthogonal polynomials arising in the numerical evaluation of inverse Laplace transforms [PDF]
Herbert E. Salzer
openalex +1 more source
Overview of the Investigation into the Effective Operating Parameters of the Foamy Oil Process. Abstract This research employed a visual method to explore the behaviour of foamy oil in heavy oil systems. A Hele‐Shaw cell was designed for observing the volumetric expansion of foamy oil as the system pressure decreased.
Morteza Sabeti+2 more
wiley +1 more source
The Study for Synchronization between Two Coupled FitzHugh-Nagumo Neurons Based on the Laplace Transform and the Adomian Decomposition Method. [PDF]
Zhen B, Song Z.
europepmc +1 more source
Asymptotic Behaviour Of The Inverse Of a Laplace Transform [PDF]
T. E. Hull, Charlotte Froese
openalex +1 more source
Computer-Aided Numerical Inversion of Laplace Transform
This paper explores the technique for the computer aided numerical inversion of Laplace transform. The inversion technique is based on the properties of a family of three parameter exponential probability density functions.
Umesh Kumar
doaj +1 more source
A Synchronization Criterion for Two Hindmarsh-Rose Neurons with Linear and Nonlinear Coupling Functions Based on the Laplace Transform Method. [PDF]
Su C, Zhen B, Song Z.
europepmc +1 more source
A General Card-Program for the Evaluation of the Inverse Laplace Transform [PDF]
C. K. Titus
openalex +1 more source
Some Laplace transforms and integral representations for parabolic cylinder functions and error functions [PDF]
This paper uses the convolution theorem of the Laplace transform to derive new inverse Laplace transforms for the product of two parabolic cylinder functions in which the arguments may have opposite sign. These transforms are subsequently specialized for products of the error function and its complement thereby yielding new integral representations for
arxiv
Fast and scalable inference for spatial extreme value models
Abstract The generalized extreme value (GEV) distribution is a popular model for analyzing and forecasting extreme weather data. To increase prediction accuracy, spatial information is often pooled via a latent Gaussian process (GP) on the GEV parameters. Inference for GEV‐GP models is typically carried out using Markov Chain Monte Carlo (MCMC) methods,
Meixi Chen, Reza Ramezan, Martin Lysy
wiley +1 more source