Global change research has placed new demands on methods of spatial analysis. In particular, spherical methods for spatial interpolation are required when spatial analyses are performed over large areas of the Earth's surface. In this article, spherical spatial interpolation procedures are reviewed, compared, and evaluated. Three classesof spherical interpolants are evaluated in detail: distanc...

Managing and hedging the risks associated with Variable Annuity (VA) products requires intraday valuation of key risk metrics for these products. The complex structure of VA products and computational complexity of their accurate evaluation has compelled insurance companies to adopt Monte Carlo (MC) simulations to value their large portfolios of VA products. Because the MC simulations are compu...

A Neural Network Approach to Efficient Valuation of Large VA Portfolios Seyed Amir Hejazi Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2016 Variable annuity (VA) products expose insurance companies to considerable risk because of the guarantees they provide to buyers of these products. Managing and hedging the risks associated with VA products requires intr...

This study investigated the effects on the measurement of fractional anisotropy (FA) during interpolation of diffusion tensor images in spatial normalization, which is required for voxel-based statistics. Diffusion tensor imaging data were obtained from nine male patients with attention deficit/hyperactivity disorder and nine age-matched control subjects. Regions of interest were selected from ...

Algorithms based on Pythagorean hodographs (PH) both in Euclidean plane and Minkowski space share common goals, the main one being rationality of offsets of planar domains. However, only separate interpolation techniques based on these curves can be found in the literature. It was recently revealed that rational PH curves in Euclidean plane and Minkowski space are very closely related. In this ...

Managing and hedging the risks associated with Variable Annuity (VA) products require intraday valuation of key risk metrics for these products. The complex structure of VA products and computational complexity of their accurate evaluation have compelled insurance companies to adopt Monte Carlo (MC) simulations to value their large portfolios of VA products. Because the MC simulations are compu...

We present a novel hybrid scheme called “hyper-resolution” that integrates image probability-filtering-based interpolation and improved Poisson maximum a posteriori (MAP) super-resolution to respectively enhance high spatial and spatial-frequency resolutions of a single down-sampled image. A new approach to interpolation is proposed for simultaneous image interpolation and smoothing by exploiti...

Inverse solutions to interpolation techniques in computer graphics may increase the accuracy of the rendered frames. An example is the use of an arbitrary time stamp in time interpolation to evaluate the t-parameter, which in turn can be used for time-variant spatial interpolation. In this paper, an analytic inverse is presented for a shape-preserving piecewise cubic Hermite interpolant, used i...

Stochastic methods of space-time interpolation and conditional simulation have been used in statistical downscaling approaches to increase the resolution of measured fields. One of the popular interpolation methods in geostatistics is kriging, also known as optimal interpolation in data assimilation. Kriging is a stochastic, linear interpolator which incorporates time/space variability by means...

Statistical timing analysis for manufacturing variability requires modeling of spatially-correlated variation. Common grid-based modeling for spatially-correlated variability involves a trade-off between accuracy and computational cost, especially for PCA (principal component analysis). This paper proposes to spatially interpolate variation coefficients for improving accuracy instead of fining ...