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Spatial econometrics
Nývltová, Veronika ; Pawlas, Zbyněk (advisor) ; Kopa, Miloš (referee)
This thesis is devoted to the models that are suitable for modelling spatial data. For this purpose, random fields with finite index set are used. Based on the neighbourhood relationship a spatial weight matrix is introduced which describes spatial dependencies. A recognition and testing of spatial dependence is mentioned and it is applied for macroeconomic indicators in the Czech Republic. Spatial models originated from generalization of usual time series models are subsequently combined with linear regression models. The parameter estimators are derived for selected models by three different methods. These methods are ordinary least squares, maximum likelihood and method of moments. Theoretical asymptotic results are supplemented by a simulation study that examines the performance of estimators for finite sample size. Finally, a short illustration on real data is demonstrated. Powered by TCPDF (www.tcpdf.org)
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Spatial econometrics
Nývltová, Veronika ; Pawlas, Zbyněk (advisor) ; Kopa, Miloš (referee)
This thesis is devoted to the models that are suitable for modelling spatial data. For this purpose, random fields with finite index set are used. Based on the neighbourhood relationship a spatial weight matrix is introduced which describes spatial dependencies. A recognition and testing of spatial dependence is mentioned and it is applied for macroeconomic indicators in the Czech Republic. Spatial models originated from generalization of usual time series models are subsequently combined with linear regression models. The parameter estimators are derived for selected models by three different methods. These methods are ordinary least squares, maximum likelihood and method of moments. Theoretical asymptotic results are supplemented by a simulation study that examines the performance of estimators for finite sample size. Finally, a short illustration on real data is demonstrated. Powered by TCPDF (www.tcpdf.org)
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Characteristics of rainfall in observed data and regional climate model simulations
Svoboda, Vojtěch ; Pech, Pavel (advisor) ; Josef, Josef (referee)
Precipitation in the form of heavy rainfall events is of significant societal concern, not only due to the potential for more frequent flash floods, after evidence of changes in rainfall characteristics has recently strengthened. Despite the importance of individual rainfall events with respect to many hydrological applications, only a few studies dealt with characteristics of individual rainfall events (in contrast with the other daily/sub-daily indices of rainfall depths/intensities). Dissertation thesis presents a comprehensive analysis of heavy rainfall event characteristics for the Czech Republic derived from observed data and large ensemble of regional climate model (RCM) simulations. In addition, spatial correlation structure of observed rainfall data at a mesoscale region of north-eastern Bohemia was analysed. Since an RCM grid box represents a spatial average rather than a point measurement, the effects from areal averaging of rainfall data on characteristics of events were investigated considering the observed data. Characteristics of rainfall events were evaluated according to several indices against the at-site and area-averaged observed data for the control period 1981-2000. The changes of rainfall event characteristics were assesed over two scenario periods (2020-2049 and 2070-2099) with respect to control period. We analysed also relations between changes in simulated rainfall event characteristics and changes in radiative forcing and temperature.
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