Explicit cost bounds of algorithms for multivariate tensor product problems
Journal of Complexity
A generalized discrepancy and quadrature error bound
Mathematics of Computation
When are quasi-Monte Carlo algorithms efficient for high dimensional integrals?
Journal of Complexity
Complexity of weighted approximation over R
Journal of Approximation Theory
Constructing Randomly Shifted Lattice Rules in Weighted Sobolev Spaces
SIAM Journal on Numerical Analysis
Component-by-component construction of good lattice rules
Mathematics of Computation
The effective dimension and quasi-Monte Carlo integration
Journal of Complexity
Variance Reduction via Lattice Rules
Management Science
Finite-order weights imply tractability of multivariate integration
Journal of Complexity
Journal of Complexity
Halton Sequences Avoid the Origin
SIAM Review
Letter section: Randomization of lattice rules for numerical multiple integration
Journal of Computational and Applied Mathematics
Time complexity estimation and optimisation of the genetic algorithm clustering method
WSEAS Transactions on Mathematics
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We study the problem of multivariate integration on the unit cube for unbounded integrands. Our study is motivated by problems in statistics and mathematical finance, where unbounded integrands can arise as a result of using the cumulative inverse normal transformation to map the integral from the unbounded domain R^d to the unit cube [0,1]^d. We define a new space of functions which possesses the boundary behavior of those unbounded integrands arising from statistical and financial applications, however, we assume that the functions are analytic, which is not usually the case for functions from finance problems. Our new function space is a weighted tensor-product reproducing-kernel Hilbert space. We carry out a worst-case analysis in this space and show that good randomly shifted lattice rules can be constructed component-by-component to achieve a worst-case error of order O(n^-^1^/^2), where the implied constant in the big O notation is independent of d if the sum of the weights is finite. Numerical experiments indicate that our lattice rules are reasonably robust and perform well in pricing Asian options.