Results 91 to 100 of about 20,027 (232)
Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source
A‐optimal model‐based design of experiments for processes with uncertain inputs
Abstract Model‐based design of experiments (MBDoE) techniques are tools for selecting experimental conditions that enable accurate parameter estimation for mechanistic models. Most MBDoE approaches assume that the selected experimental conditions will be implemented perfectly, without uncertainties in the independent variables.
Bright Ofori +3 more
wiley +1 more source
Linear algebraic structure of zero-determinant strategies in repeated games. [PDF]
Ueda M, Tanaka T.
europepmc +1 more source
Subuniformity of harmonic mean p$$ p $$‐values
Abstract We obtain several inequalities on the generalized means of dependent p$$ p $$‐values. In particular, the weighted harmonic mean of p$$ p $$‐values is strictly subuniform under several dependence assumptions of p$$ p $$‐values, including independence, negative upper orthant dependence, the class of extremal mixture copulas, and some Clayton ...
Yuyu Chen +3 more
wiley +1 more source
An observation‐driven state‐space model for claims size modelling
Abstract State‐space models are popular in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state‐space models are of the Kalman‐filter type. These are called parameter‐driven because the observations do not impact the state‐space dynamics.
Jae Youn Ahn +2 more
wiley +1 more source
Asymptotic properties of cross‐classified sampling designs
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
A Markov approach to credit rating migration conditional on economic states
Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
EXPLORING ALGEBRAIC ANALYSIS: DEFINITIONS, INTERPRETATIONS, AND METHODOLOGIES
For further than 200 times, the word algebraic analysis has been used to relate to a variety of motifs and methodologies. These connotations are still present moment.
Altaher A. +3 more
doaj +1 more source
A goodness‐of‐fit test for regression models with discrete outcomes
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source

