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Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions
Conditional characteristic function Diffusion processes Empirical likelihood Kernel smoothing L′ evy driven processes
2016/1/19
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis
Kernel Methods Global Sensitivity Analysis Sobol-Hoeffding Decomposition
2011/7/6
Given a Reproducing Kernel Hilbert Space (H, h., .i) of real-valued functions and a suitable measure \mu over the source space, we decompose H as sum of a subspace of centered functions for {\mu} and ...
Selection models with monotone weight functions in meta analysis
global constrained optimization meta analysis monotone non-increasing selection bias
2011/3/24
Publication bias, the fact that studies identified for inclusion in a meta analysis do not represent all studies on the topic of interest, is commonly recognized as a threat to the validity of the res...
Estimating composite functions by model selection
Curve estimation model selection composite functions
2011/3/21
We consider the problem of estimating a function $s$ on $[-1,1]^{k}$ for large values of $k$ by looking for some best approximation by composite functions of the form $g\circ u$. Our solution is based...