Weak instruments arise when the instruments in linear instrumental variables (IV) regression are weakly correlated with the included endogenous variables. In generalized method of moments (GMM), more generally, weak instruments correspond to weak identification of some or all of the unknown parameters. Weak identification leads to GMM statistics with nonnormal distributions, even in large sampl...

Properties of GMM estimators for panel data, which have become very popular in the empirical economic growth literature, are not well known when the number of individuals is small. This paper analyses through Monte Carlo simulations the properties of various GMM and other estimators when the number of individuals is the one typically available in country growth studies. It is found that, provid...

This paper presents the programming language induced by the ordered structure of the Geometric Machine Model (GMM). The GMM is an abstract machine model, based on Girard’s coherence space, capable of modelling sequential, alternative, parallel (synchronous) and non-deterministic computations on a (possibly infinite) shared memory. The processes of the GMM are inductively constructed in a Cohere...

Moving object detection is critical task in video analytics. Gaussian Mixture Model (GMM) based background subtraction is widely popular technique for moving object detection due to its robustness to multimodality and lighting changes. This paper presents the critical survey about various GMM based approaches for handling critical background situations. This survey describes various challenges ...

The Gaussian mixture model (GMM) has been widely used in pattern recognition problems for clustering and probability density estimation. For pattern classification, however, the GMM has to consider two issues: model structure in high-dimensional space and discriminative training for optimizing the decision boundary. In this paper, we propose a classification method using subspace GMM density mo...