In this paper we propose an instrumental variables (IV) estimator for a semiparametric outcome model with endogeous discrete treatment variables. The main contribution of our paper is that the identi…cation, consistency and asymptotic normality of our estimator all hold even under misspeci…cation of the treatment model. As expected from Newey and McFadden (1994), the covariance matrix for the p...

In this paper, we investigate the use of the minimum mean square error (MMSE) spectral energy estimator for use in environmentrobust automatic speech recognition (ASR). In the past, it has been common to use the MMSE log-spectral amplitude estimator for this task. However, this estimator was originally derived under subjective human listening criteria. Therefore its complex suppression rule may...

In this paper we propose an estimator of the entropy of a continuous random variable. The estimator is obtained by modifying the estimator proposed by Vasicek (1976). Consistency of estimator is proved, and comparisons are made with Vasicek’s estimator (1976), van Es’s estimator (1992), Ebrahimi et al.’s estimator (1994) and Correa’s estimator (1995). The results indicate that the proposed esti...

Dionissios T. Hristopulos Department of Mineral Resources Engineering Technical University of Crete Chania 73100, Greece Abstract The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at points where observations are not availa...

The purpose of this article is to discuss the importance of uncertainty analysis in water quality modeling, with an emphasis on the identi cation of the correct model speci cation. A wetland phosphorus retention model is used as an example to illustrate the procedure of using a ltering technique for model structure identi cation. Model structure identi cation is typically done through model par...

We consider the problem of multichannel estimation, in which we seek to estimate N deterministic input vectors xk that are observed through a set of linear transformations and corrupted by additive noise, where the linear transformations are subjected to uncertainty. To estimate the inputs xk we propose a minimax mean-squared error (MSE) approach in which we seek the linear estimator that minim...