I examined patterns of covariation of three morphometric blossom characters [gland area (GA), gland-stigma distance (GSD), and bract length (BL)] within genets, among genets, and among populations of the tropical vine, Dalechampia scandens (Euphorbiaceae). Covariance between BL and GA was evenly distributed among the three levels. This observation, coupled with developmental information, indica...

Most HMM-based speech recognition systems use Gaussian mixtures as observation probability density functions. An important goal in all such systems is to improve parsimony. One method is to adjust the type of covariance matrices used. In this work, factored sparse inverse covariance matrices are introduced. Based on U DU factorization, the inverse covariance matrix can be represented using line...

A new class of stochastic covariance models based on Wishart distribution is proposed. Three categories of dynamic correlation models are introduced depending on how the timevarying covariance matrix is formulated and whether or not it is a latent variable. A stochastic covariance filter is also developed for filtering and predicting covariances. Extensions of the basic models enable the study ...

Authors: Johanna m. de Kort* , Conor V. Dolan*,** and Dorret I. boomsma** In the classical twin study, genetic and environmental influences on a phenotype are usually estimated under the assumption that genotype-environment covariance (Ge covariance) is absent. We explore possibilities to accommodate Ge covariance in longitudinal data using the genetic simplex model. First, the genetic simplex ...

Adaptive beamforming methods degrade in the presence of model mismatch. In this paper, we develop a modified interference covariance matrix reconstruction based beamformer that is robust against large array calibration errors. The calibration errors can come from the element position errors, and/or amplitude and phase errors, etc.. The proposed method is based on the fact that the sample covari...

A new form of covariance modelling for Gaussian mixture models and hidden Markov models is presented. This is an extension to an efficient form of covariance modelling used in speech recognition, semi-tied covariance matrices. In the standard form of semi-tied covariance matrices the covariance matrix is decomposed into a highly shared decorrelating transform and a component-specific diagonal c...

this paper reports the results of using three empirical methods (makkink, priestley-taylor and hargreaves) for estimating the reference evapotranspiration (et0) in the semi-arid region of tensift al haouz, marrakech (center of morocco). the penman-monteith equation, standardized by the food and agriculture organization (fao-pm), is used to evaluate the three empirical methods. the obtained et0 ...

to perform any economic management of a petroleum reservoir in real time, a predictable and/or updateable model of reservoir along with uncertainty estimation ability is required. one relatively recent method is a sequential monte carlo implementation of the kalman filter: the ensemble kalman filter (enkf). the enkf not only estimate uncertain parameters but also provide a recursive estimate of...

Bootstrap and restructuring (BSRS) has been shown in our previous work to be superior over the conventional acoustic modeling approach when dealing with low-resourced languages. This paper presents a full covariance based BSRS scheme, which is an extension of our previous work on diagonal covariance based BSRS acoustic modeling. Since full covariance provides richer structural information of ac...