Identification-robust inference for endogeneity parameters in linear structural models
Texte intégral
Figure
Documents relatifs
The Hamiltonian Monte Carlo algorithm and a method based on a system of dynamical stochastic differential equations were considered and applied to a simplified pyrolysis model to
In the presence of small deviations from the model (Figure 2), the χ 2 approximation of the classical test is extremely inaccurate (even for n = 100), its saddlepoint version and
Robust and Accurate Inference for Generalized Linear Models:..
By starting from a natural class of robust estimators for generalized linear models based on the notion of quasi-likelihood, we define robust deviances that can be used for
Therefore, usual results for linear spectral method as the one given in Equation (4.8) cannot apply. Because the PLS filter factors can be larger than one, [FF93] proposed to bound
Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference... Estimating parameters and hidden variables in
Inspired by the Bayesian evidence framework proposed in [31] to solve noisy interpolation problems, we have derived a generic and reliable hierarchical model for robust
In addition to handling the relationship between observed data and the latent trait via the link and distribution functions, any system for expected and observed scale quantitative