Results 31 to 40 of about 5,829 (199)

Estimating Ruin Probability in an Insurance Risk Model with Stochastic Premium Income Based on the CFS Method

open access: yesMathematics, 2021
This paper considers the estimation of ruin probability in an insurance risk model with stochastic premium income. We first show that the ruin probability can be approximated by the complex Fourier series (CFS) expansion method.
Yujuan Huang   +3 more
doaj   +1 more source

Optimal Dividends for a Two-Dimensional Risk Model with Simultaneous Ruin of Both Branches

open access: yesRisks, 2022
We consider the optimal dividend problem in the so-called degenerate bivariate risk model under the assumption that the surplus of one branch may become negative.
Philipp Lukas Strietzel   +1 more
doaj   +1 more source

Conditional value-at-risk bounds for compound Poisson risks and a normal approximation

open access: yesJournal of Applied Mathematics, 2003
A considerable number of equivalent formulas defining conditional value-at-risk and expected shortfall are gathered together. Then we present a simple method to bound the conditional value-at-risk of compound Poisson loss distributions under incomplete ...
Werner Hürlimann
doaj   +1 more source

A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums

open access: yesRisks, 2020
In this paper, a flexible count regression model based on a bivariate compound Poisson distribution is introduced in order to distinguish between different types of claims according to the claim size. Furthermore, it allows us to analyse the factors that
Emilio Gómez-Déniz   +1 more
doaj   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

open access: yesMolecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix   +13 more
wiley   +1 more source

Marked Long‐Term Improvement in Lung Function in Melanoma Differentiation–Associated Protein 5 Antibody–Positive Dermatomyositis Patients: Experience of a Single‐Center Longitudinal Cohort in North America

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this study was to describe the longitudinal disease course and pulmonary outcomes of North American patients with melanoma differentiation–associated protein 5 (MDA5) antibody–associated dermatomyositis (DM). Methods Thirty patients with MDA5 antibody–associated DM were identified in a single‐center longitudinal cohort of 352
Jenice X. Cheah   +8 more
wiley   +1 more source

A Regional Catastrophe Bond Pricing Model and Its Application in Indonesia’s Provinces

open access: yesMathematics, 2023
The national scale of catastrophic losses risk linked to state catastrophe bonds (SCB) is enormous. It can reduce investors’ interest in buying them because the capital required and the loss probability are also significant. To overcome this, the SCB can
Sukono   +5 more
doaj   +1 more source

Developing and Evaluating a Laboratory‐Based Frailty Index (FI‐Lab) for the Prediction of Long‐Term Health Outcomes in Systemic Lupus Erythematosus

open access: yesArthritis Care &Research, Accepted Article.
Objective We aimed to construct and evaluate the first laboratory‐based frailty index (FI‐Lab) for predicting adverse outcomes in systemic lupus erythematosus (SLE) and to compare its predictive ability to that of an existing clinical frailty index (FI).
Grace Burns   +2 more
wiley   +1 more source

Extremal Analysis of Flooding Risk and Its Catastrophe Bond Pricing

open access: yesMathematics, 2022
Catastrophic losses induced by natural disasters are receiving growing attention because of the severe increases in their magnitude and frequency.
Jiayi Li   +3 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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