We study a key part of NHS policy to ensure high quality health care: failure to supply such care cost the NHS £787m in clinical negligence payouts during 2009-10. The NHS uses risk management standards to incentivise care and we examine their effects on MRSA infections. Using a specially assembled dataset, our GMM results suggest that improvements in the risk management standards attained by s...

Lee (2003) proposed for spatial autoregressive (SAR) model the best spatial two-stage least squares estimator (BS2SLSE) as an improvement on Kelejian and Prucha (1998)’s S2SLSE. In this paper, we show that one more step iteration based on BS2SLSE gives a spatial counterpart of the three-stage least squares estimator for a system of J equations. This estimator, named BS3SLSE, is shown to be equi...

Banking sector openness may directly increase growth by improving the quality of financial services and increasing funds available, or indirectly by improving the efficiency of financial intermediaries, both of which may reduce the cost of financing, in turn, increase capital accumulation and economic growth. The objective of the paper is to empirically reinvestigate these direct and indirect l...

Macroeconomic Effects of Short-Term Training Measures on the Matching Process in Western Germany This paper investigates the macroeconomic effects of short term training measures on the matching processes in West Germany. The empirical analysis is based on regional data for local employment office districts for the period from January 2003 to December 2004. The empirical model relies on a dynam...

The local robustness properties of generalized method of moments (GMM) estimators and of a broad class of GMM based tests are investigated in a uni"ed framework. GMM statistics are shown to have bounded in#uence if and only if the function de"ning the orthogonality restrictions imposed on the underlying model is bounded. Since in many applications this function is unbounded, it is useful to hav...

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...

This paper focuses on the automatic determination of the age of children in preschool and primary school age. For each child a Gaussian Mixture Model (GMM) is trained. As training method the Maximum A Posteriori adaptation (MAP) is used. MAP derives the speaker models from a Universal Background Model (UBM) and does not perform an independent parameter estimation. The means of each GMM are extr...

The IEEE-ASSP Scene Classification challenge on user-generated content (UGC) aims to classify an audio recording that belongs to a specific scene such as busystreet, office or supermarket. The difficulty of scene content analysis on UGC lies in the lack of structure and acoustic variability of the data. The i-vector system is state-ofthe-art in Speaker Verification and Scene Detection, and is o...

Quantifying how the spectral content of speech relates to changes in mental state may be crucial in building an objective speech-based depression classification system with clinical utility. This paper investigates the hypothesis that important depression based information can be captured within the covariance structure of a Gaussian Mixture Model (GMM) of recorded speech. Significant negative ...