|
|
Claims count modeling in insurance
Škoda, Štěpán ; Branda, Martin (advisor) ; Pešta, Michal (referee)
1 Abstract: The present work investigates techniques of insurence ratemaking accor- ding to the claims counts of policyholders on the basis of information contained in policies. At the beginning, we provide a closer examination of the theory of genera- lized linear models, which have wide range of applications in the field of actuarial modeling. The second chapter presents the basic Poisson regression model as well as some particular verification methods. Specifically, deviance and Wald test could be found here and furthermore also important results for residuals. The third chapter contains information on alternative approaches to modeling the claim frequencies and at the end the GEE method, that can be applied in case of panel data, is de- scribed. The numerical study based on real insurace data in last part of this diploma thesis illustrate's previously described techniques which were obtained with the help of statistical software SAS.
|
|
|
Statistical models for capital models of insurance companies
Švagerková, Lýdia ; Šimurda, Miroslav (advisor) ; Mazurová, Lucie (referee)
This work deals with the topic of lapse rate modelling in the field of Life Insurance. First, the theoretical apparatus is established: the linear models and their extension, generalized linear models. Furthermore, we describe the process of model selection and evaluation. In the second part of this work we describe the influence of various individual as well as macroeconomical parameters on the lapse rate. We summarize the findings of previous works in this field. The last part introduces models in statistical software R based on generalized linear models and describes the process of their selection and evaluation. Outputs from these models are interpreted and compared to the ratio analysis results.
|
|
|
Methods for class prediction with high-dimensional gene expression data
Šilhavá, Jana ; Matula, Petr (referee) ; Železný, Filip (referee) ; Smrž, Pavel (advisor)
Dizertační práce se zabývá predikcí vysokodimenzionálních dat genových expresí. Množství dostupných genomických dat významně vzrostlo v průběhu posledního desetiletí. Kombinování dat genových expresí s dalšími daty nachází uplatnění v mnoha oblastech. Například v klinickém řízení rakoviny (clinical cancer management) může přispět k přesnějšímu určení prognózy nemocí. Hlavní část této dizertační práce je zaměřena na kombinování dat genových expresí a klinických dat. Používáme logistické regresní modely vytvořené prostřednictvím různých regularizačních technik. Generalizované lineární modely umožňují kombinování modelů s různou strukturou dat. V dizertační práci je ukázáno, že kombinování modelu dat genových expresí a klinických dat může vést ke zpřesnění výsledku predikce oproti vytvoření modelu pouze z dat genových expresí nebo klinických dat. Navrhované postupy přitom nejsou výpočetně náročné. Testování je provedeno nejprve se simulovanými datovými sadami v různých nastaveních a následně s~reálnými srovnávacími daty. Také se zde zabýváme určením přídavné hodnoty microarray dat. Dizertační práce obsahuje porovnání příznaků vybraných pomocí klasifikátoru genových expresí na pěti různých sadách dat týkajících se rakoviny prsu. Navrhujeme také postup výběru příznaků, který kombinuje data genových expresí a znalosti z genových ontologií.
|
|
|
Mathematical modelling in general insurance
Zajíček, Jakub ; Bílková, Diana (advisor) ; Bohatová Chládková, Dana (referee)
This diploma thesis deals with the mathematical models in general insurance. The aim of this thesis is to analyse selected mathematical models that are widely used in general insurance for the estimation of insurance portfolio statistics, pricing and the regulatory capital requirement calculation. Claim frequency models, claim severity models, aggregate loss models and generalized linear models are analysed. This thesis consists of a theoretical and a practical part. The theoretical part contains description of selected models. Described models are then applied to a real dataset in the practical part. The real dataset modelling was performed using the statistical software R. It has been proved that maximum likelihood parameter estimations are of better quality than the method of moments or quantile method estimations. The results of aggregate loss distribution computational methods are comparable. This comparability is mostly caused by a large number of observations. In the context of tariff analysis it was found that the most significant factors are driver's age and the driver's area of residence.
|
|
|
The role of wood decay fungi in the dynamics of a mountain spruce forest
POUSKA, Václav
This thesis is focused on environmental preferences of wood-decaying fungi and their relationships with forest structure and development. Relationships of fungi to properties of wood and forest stands were studied on the basis of field observations in Central-European mountain spruce forests. Plot-based approach was used to reveal a general pattern in the diversity of fungi within a single forest stand and between different stands. The analysis of stand structure provided a background for plot-based approach. Substrate-based approach was used to study single species preferences and their communities. In addition, the influence of wood properties (including fungi and their rots) on the regeneration of spruce on logs was studied.
|
|
|
Retail loan repayment analysis using generalized linear models
Šolc, Michal ; Jarošová, Eva (advisor) ; Forbelská, Marie (referee)
This Diploma thesis concern with generalized linear models and their application in bank practice. Especially to analyze retail loan repayment. First of all we see into theoretical viewpoint of generalized linear models. We shortly try to summarize problems of clasical linear model restrictions and after that we apply to theory on which generalized models are based. We introduce an overview of generalized linear models and after that we concern models, where dependent variable have multinomial and gamma distribution in detail. Main part this thesis is dedicated to data analysis about bank retail loans repayments. In this analysis we use those early mentioned models. We try to create good statistical models on which base the risk ratio of current bank clients could be predicted. The risk ratio is measured by two main indicators, which are: "overdue time" and "overdue amount". For analysis is used statistical software SAS.
|
guest ::
