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	Zero inflated Poisson model Veselý, Martin ; Komárek, Arnošt (advisor) ; Hlávka, Zdeněk (referee) This paper deals with the zero-inflated Poisson distribution. First the Poisson model is defined and generalized to a zero-inflated model. The basic properties of this generalized model are derived. After- wards the basics of the method of moments and the maximum likelihood method are described. Both of these are used to derive parameter estimates of such distribution. The feasibility of calculating the distribution of moment method estimates is analyzed. Then the asymptotic distribution of maximum likelihood estimates is derived and used to create confidence intervals. In the last chapter a numeric si- mulation of the derived asymptotic properties is performed. Special attention is paid to situations where regularity conditions are not met. 1 Detailed record
	Maximum Likelihood Estimation of Diagonal Covariance Matrix Turčičová, Marie ; Mandel, Jan ; Eben, Kryštof Fulltext: content.csg - PDF Plný tet: v1228-16 - PDF Detailed record
	On problem of optimization under incomplete information Volf, Petr The paper studies consequences of incomplete information to uncertainty of results of stochastic optimization. Stochastic characteristics of optimized system are evaluated from observed data, moreover, the data may be incomplete. Namely, we consider the random censoring of observations frequently encountered in time-to-event (of lifetime) studies. The analysis of uncertainty will be based both on theoretical properties of estimated stochastic characteristics and on simulated examples. Detailed record
	Information and Entropy of Continuous Random Variables Fabián, Zdeněk Fulltext: content.csg - PDF Plný tet: v694-96 - PDF Detailed record
	Influence Function and Fisher Information of Probability Distributions Fabián, Zdeněk Detailed record

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