Alleviating Class Imbalance in Actuarial Applications Using Generative Adversarial Networks
To build adequate predictive models, a substantial amount of data is desirable. However, when expanding to new or unexplored territories, this required level of information is rarely always available.
Kwanda Sydwell Ngwenduna, Rendani Mbuvha
doaj +1 more source
Sex‐dependent effects of parental age on offspring fitness in a cooperatively breeding bird
Abstract Parental age can have considerable effects on offspring phenotypes and health. However, intergenerational effects may also have longer term effects on offspring fitness. Few studies have investigated parental age effects on offspring fitness in natural populations while also testing for sex‐ and environment‐specific effects.
Alexandra M. Sparks+5 more
wiley +1 more source
Modelling Motor Insurance Claim Frequency and Severity Using Gradient Boosting
Modelling claim frequency and claim severity are topics of great interest in property-casualty insurance for supporting underwriting, ratemaking, and reserving actuarial decisions. Standard Generalized Linear Models (GLM) frequency–severity models assume
Carina Clemente+2 more
doaj +1 more source
Robust heavy-tailed versions of generalized linear models with applications in actuarial science [PDF]
Generalized linear models (GLMs) form one of the most popular classes of models in statistics. The gamma variant is used, for instance, in actuarial science for the modelling of claim amounts in insurance. A flaw of GLMs is that they are not robust against outliers (i.e., against erroneous or extreme data points).
arxiv +1 more source
Abstract We assessed the long‐term outcomes and treatment‐related adverse effects of patients with Stage I, “orbital‐type” lymphomas that were uniformly treated with photons. All consecutive patients diagnosed with low‐grade, Ann Arbor Stage IEA orbital lymphoma treated between 1999 and 2020 at our department were retrospectively reviewed.
Christian Hoffmann+19 more
wiley +1 more source
Modeling Vehicle Insurance Loss Data Using a New Member of T-X Family of Distributions
In actuarial literature, we come across a diverse range of probability distributions for fitting insurance loss data. Popular distributions are lognormal, log-t, various versions of Pareto, log-logistic, Weibull, gamma and its variants and a generalized ...
Zubair Ahmad+3 more
doaj +1 more source
Machine Learning in P&C Insurance: A Review for Pricing and Reserving
In the past 25 years, computer scientists and statisticians developed machine learning algorithms capable of modeling highly nonlinear transformations and interactions of input features.
Christopher Blier-Wong+3 more
doaj +1 more source
The development of an extended Weibull model with applications to medicine, industry and actuarial sciences [PDF]
Muhammad Imran+6 more
openalex +2 more sources
Age patterns of net migration and urbanisation dynamics across European municipalities
Abstract Across the European Union (EU) Local Administrative Units (LAUs), populations are experiencing persisting differences in their age structures that can only be interpreted accounting for migration and mobility components. Yet, in the absence of census data, migration patterns of local populations are not available from EU‐official statistics ...
Daniela Ghio+4 more
wiley +1 more source
Modelling Customs Revenue in Ghana Using Novel Time Series Methods
Governments across the world rely on their Customs Administration to provide functions that include border security, intellectual property rights protection, environmental protection, and revenue mobilisation amongst others.
Diana Ayorkor Agbenyega+3 more
doaj +1 more source