AUTHOR

Tsagris Michail

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Agricultural Economics , Applied Research - 2021

Nitrate Pollution and Efficiency Measurement in Intensive Farming Systems: A Parametric By-Production Technology Approach

This paper develops a novel empirical framework for estimating individual emission levels in a nonpoint source (NPS) pollution problem. For doing so we incorporate into the GME model suggested by Kaplan et al., (2003) a specific theoretical structure describing both crop production technology and nature's residual generating mechanism based on the multiple production relations model suggested by Murty et al, (2012) fitted into a parametric stochastic framework.

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Statistics , Data Analytics - 2019

Comparison of discriminant analysis methods on the sphere

We compared maximum likelihood and the k-NN algorithm in the context of discriminant analysis with spherical data.

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Statistics , Data Analytics - 2018

Modelling Structural Zeros in Compositional Data

We present new model for analyzing compositional data with structural zeros. Inspired by Butler and Glasbey (2008) who suggested a model in the presence of zero values in the data we propose a model that treats the zero values in a different manner.

https://9b9ec758578b3ee0d46b-305404f9eb35eaf4130aa2d106c6a91c.ssl.cf3.rackcdn.com/597/main_gallery/images//p1cour2i2q130ir9jf801s6cr565.jpg
Statistics , Data Analytics - 2018

Discriminant Analysis with Spherical Data

Discriminant analysis for spherical data, or directional data in general, has not been extensively studied, and most papers focus on one distribution, the von Mises-Fisher. In this work, we study more distributions, escaping the rotational symmetry bound of the aforementioned distribution and also include a non parametric classier, the k-NN algorithm.

https://9b9ec758578b3ee0d46b-305404f9eb35eaf4130aa2d106c6a91c.ssl.cf3.rackcdn.com/597/main_gallery/images//p1cour2i2q1ckg1pf11vjb3ik1dli4.jpg
Statistics , Data Analytics - 2018

A Folded Model for Compositional Data Analysis

A folded type model is developed for analyzing compositional data based that provides a new and flexible class of distributions for modeling data defined on the simplex sample space. Despite its rather seemingly complex structure, employment of the EM algorithm guarantees efficient parameter estimation.

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