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Statistical analysis of ROC curves
Kutálek, David ; Bednář, Josef (referee) ; Michálek, Jaroslav (advisor)
The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.
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Numerical study on simultanious equations
Šaroch, Vojtěch ; Lachout, Petr (advisor) ; Cipra, Tomáš (referee)
Title: Numerical study on simultanious equations Author: Vojtěch Šaroch Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Petr Lachout, CSc. Abstract: In this thesis we deal with the simultaneous equation model. In the first chapter we introduce theoretical aspect of this problem, especially estimation procedures and their properties. We mention issues of an identification and an inconsistency of OLS-estimates for simultaneous modeling. In th second chapter we introduce theory of estimation, especially we will focus on the interval estimation and precision. We mention empirical approach too. In the third chapter we perform a numerical study on the simple macroeconomic model of generated dates. We are interested in properties of interval estimations of parameters, the convergence rate, difference between the empirical and theoretical extimation etc. Keywords: simultaneous equations model, interval estimation, empirical estimation 1
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Numerical study on simultanious equations
Šaroch, Vojtěch ; Lachout, Petr (advisor) ; Hendrych, Radek (referee)
Title: Numerical study on simultanious equations Author: Vojtěch Šaroch Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Petr Lachout, CSc. Abstract: In this thesis we deal with simultaneous equation model. In first chapter we introduce to theoretical aspect of this problem, especially estimation procedures and their properties. We mention issues of identification and an inconsistency of OLS-estimates for the simultaneous modeling. In second chapter we introduce theory of estimation, especially we will focus on interval estimation and precision. We mention empirical approach too. In the third chapter we perform a numerical study on simple macroeconomic model on generated dates. We are interested in properties interval estimations of parameters, the convergence rate, difference between empirical and theoretical extimation etc. Keywords: simultaneous equations model, interval estimation, empirical estimation 1
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Statistical analysis of ROC curves
Kutálek, David ; Bednář, Josef (referee) ; Michálek, Jaroslav (advisor)
The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.
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Estimating Efficiency Offset between Two Groups of Decision-Making Units
Macek, Karel
The comparison of two groups of decision-making units (DMUs) has been already subject of scientific reflection. So far, some statistical tests have been developed. This article addresses estimating the difference between expected outputs of two groups of DMUs. In contrast to other efficiency evaluation methods, this publication focuses on quantitative assessment of this difference, not on the hypothesis testing. The article focuses on single output DMUs and the designed statistical tests are examined on various simulated data sets as well as on one realworld example. Some of them stem from the data envelopment analysis, others are related to the local regression.
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