1,970 research outputs found
Quadrature Points via Heat Kernel Repulsion
We discuss the classical problem of how to pick weighted points on a
dimensional manifold so as to obtain a reasonable quadrature rule
This problem, naturally, has a long history; the purpose of our paper is to
propose selecting points and weights so as to minimize the energy functional
\sum_{i,j =1}^{N}{ a_i a_j \exp\left(-\frac{d(x_i,x_j)^2}{4t}\right) }
\rightarrow \min, \quad \mbox{where}~t \sim N^{-2/d}, is the
geodesic distance and is the dimension of the manifold. This yields point
sets that are theoretically guaranteed, via spectral theoretic properties of
the Laplacian , to have good properties. One nice aspect is that the
energy functional is universal and independent of the underlying manifold; we
show several numerical examples
Parametric estimation of complex mixed models based on meta-model approach
Complex biological processes are usually experimented along time among a
collection of individuals. Longitudinal data are then available and the
statistical challenge is to better understand the underlying biological
mechanisms. The standard statistical approach is mixed-effects model, with
regression functions that are now highly-developed to describe precisely the
biological processes (solutions of multi-dimensional ordinary differential
equations or of partial differential equation). When there is no analytical
solution, a classical estimation approach relies on the coupling of a
stochastic version of the EM algorithm (SAEM) with a MCMC algorithm. This
procedure needs many evaluations of the regression function which is clearly
prohibitive when a time-consuming solver is used for computing it. In this work
a meta-model relying on a Gaussian process emulator is proposed to replace this
regression function. The new source of uncertainty due to this approximation
can be incorporated in the model which leads to what is called a mixed
meta-model. A control on the distance between the maximum likelihood estimates
in this mixed meta-model and the maximum likelihood estimates obtained with the
exact mixed model is guaranteed. Eventually, numerical simulations are
performed to illustrate the efficiency of this approach
- …