4,040 research outputs found
Sum-factorization techniques in Isogeometric Analysis
The fast assembling of stiffness and mass matrices is a key issue in
isogeometric analysis, particularly if the spline degree is increased. We
present two algorithms based on the idea of sum factorization, one for matrix
assembling and one for matrix-free methods, and study the behavior of their
computational complexity in terms of the spline order . Opposed to the
standard approach, these algorithms do not apply the idea element-wise, but
globally or on macro-elements. If this approach is applied to Gauss quadrature,
the computational complexity grows as instead of as
previously achieved.Comment: 34 pages, 8 figure
Probabilistic Numerics and Uncertainty in Computations
We deliver a call to arms for probabilistic numerical methods: algorithms for
numerical tasks, including linear algebra, integration, optimization and
solving differential equations, that return uncertainties in their
calculations. Such uncertainties, arising from the loss of precision induced by
numerical calculation with limited time or hardware, are important for much
contemporary science and industry. Within applications such as climate science
and astrophysics, the need to make decisions on the basis of computations with
large and complex data has led to a renewed focus on the management of
numerical uncertainty. We describe how several seminal classic numerical
methods can be interpreted naturally as probabilistic inference. We then show
that the probabilistic view suggests new algorithms that can flexibly be
adapted to suit application specifics, while delivering improved empirical
performance. We provide concrete illustrations of the benefits of probabilistic
numeric algorithms on real scientific problems from astrometry and astronomical
imaging, while highlighting open problems with these new algorithms. Finally,
we describe how probabilistic numerical methods provide a coherent framework
for identifying the uncertainty in calculations performed with a combination of
numerical algorithms (e.g. both numerical optimisers and differential equation
solvers), potentially allowing the diagnosis (and control) of error sources in
computations.Comment: Author Generated Postprint. 17 pages, 4 Figures, 1 Tabl
A unified pricing of variable annuity guarantees under the optimal stochastic control framework
In this paper, we review pricing of variable annuity living and death
guarantees offered to retail investors in many countries. Investors purchase
these products to take advantage of market growth and protect savings. We
present pricing of these products via an optimal stochastic control framework,
and review the existing numerical methods. For numerical valuation of these
contracts, we develop a direct integration method based on Gauss-Hermite
quadrature with a one-dimensional cubic spline for calculation of the expected
contract value, and a bi-cubic spline interpolation for applying the jump
conditions across the contract cashflow event times. This method is very
efficient when compared to the partial differential equation methods if the
transition density (or its moments) of the risky asset underlying the contract
is known in closed form between the event times. We also present accurate
numerical results for pricing of a Guaranteed Minimum Accumulation Benefit
(GMAB) guarantee available on the market that can serve as a benchmark for
practitioners and researchers developing pricing of variable annuity
guarantees.Comment: Keywords: variable annuity, guaranteed living and death benefits,
guaranteed minimum accumulation benefit, optimal stochastic control, direct
integration metho
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