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Statistic evaluation of phylogeny of biological sequences
Vadják, Šimon ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
The master's thesis provides a comprehensive overview of resampling methods for testing the correctness topology of the phylogenetic trees which estimate the process of phylogeny on the bases of biological sequences similarity. We focused on the possibility of errors creation in this estimate and the possibility of their removal and detection. These methods were implemented in Matlab for Bootstrapping, jackknifing, OTU jackknifing and PTP test (Permutation tail probability). The work aims to test their applicability to various biological sequences and also to assess the impact of the choice of input analysis parameters on the results of these statistical tests.
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Bootstrap methods in phylogenetics
Sedlář, Karel ; Vohánka,, Jaroslav (referee) ; Škutková, Helena (advisor)
In recent decades, phylogenetic reconstruction has noted great development. It was achieved by using newly acquired molecular characteristics and processing that it began to be taken as an objective science. Rapid development showed that it is necessary to evaluate the results because new techniques provided phylograms from unreliable data. For these purposes, statistical sampling methods have been applied to the phylogeny, of which bootstrapping began later to dominate. However, it also has limitations, which should be considered during interpreting the results it provided to us. This work demonstrates by combining the principles of bootstrapping and consensus trees we can obtain phylograms with better properties than those of conventional phylograms.
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Statistic evaluation of phylogeny of biological sequences
Zembol, Filip ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
The topic of my diploma thesis is the statistical evaluation of biological sequences with the help of phylogenic trees. In the theoretical part we will create a literary recherche of estimation methodology concerning the course of phylogeny on the basis of the similarity of biological sequences (DNA and proteins) and we will focus on the inaccuracies of the estimation, their causes and the possibilities of their elimination. Afterwards, we will compare the methods for the statistical evaluation of the correctness of the course of phylogeny. In the practical part of the thesis we will suggest algorithms that will be used for testing the correctness of the phylogenic trees on the basis of bootstrapping, jackknifing, OTU jackknifing and PTP test which are able to the capture phylogenic tree with the method neighbor joining from the biological sequences in FASTA code. It is also possible to change the distance model and the substitution matrix. To be able to use these algorithms for the statistical support of phylogenic trees we have to verify their right function. This verification will be evaluated on the theoretical sequences of the amino acids. For the verification of the correct function of the algorithms, we will carry out single statistical tests on real 10 sequences of mammalian ubiquitin. These results will be analysed and appropriately discussed.
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Statistical models for prediction of project duration
Oberta, Dušan ; Žák, Libor (referee) ; Hübnerová, Zuzana (advisor)
Cieľom tejto bakalárskej práce je odvodiť štatistické modely vhodné pre analýzu dát a aplikovať ich na analýzu reálnych dát týkajúcich sa časovej náročnosti projektov v závislosti na charakteristikách projektov. V úvodnej kapitole sú študované lineárne regresné modely založené na metóde najmenších štvorcov, vrátane ich vlastností a predikčných intervalov. Nasleduje kapitola zaoberajúca sa problematikou zobecnených lineárnych modelov založených na metóde maximálnej vierohodnosti, ich vlastností a zostavením asymptotických konfidenčných intervalov pre stredné hodnoty. Ďalšia kapitola sa zaoberá problematikou regresných stromov, kde sú znova ukázané metóda najmenších štvrocov a metóda maximálnej vierohodnosti. Boli ukázané základné princípy orezávania regresných stromov a odvodenie konfidenčných intervalov pre stredné hodnoty. Metóda maximálnej vierohodnosti pre regresné stromy a odvodenie konfidenčných intervalov boli z podstatnej časti vlastným odvodením autora. Posledným študovaným modelom sú náhodné lesy, vrátane ich základných vlastností a konfidenčných intervalov pre stredné hodnoty. V týchto kapitolách boli taktiež ukázané metódy posúdenia kvality modelu, výberu optimálneho podmodelu, poprípade určenia optimálnych hodnôt rôznych parametrov. Na záver sú dané modely a algoritmy implementované v jazyku Python a aplikované na reálne dáta.
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The Effects of Different Malaria Prevention Measures: Panel Data Analysis
Pavelková, Adéla ; Pertold-Gebicka, Barbara (advisor) ; Bryndová, Lucie (referee)
The main aim of this diploma thesis was to explore the topic of malaria preventive measures. Concretely, to study which preventive measures are useful and to see how they are distributed around the world. For international organizations, this is very important as they need to know whether funds allocated for malaria aid are distributed effectively. This study is using manually compounded data from the World Health Organization for all countries threatened by malaria mostly from 2001 to 2018. For this purpose, panel data regression methods using robust standard errors, bootstrapping and cluster analysis were used. The results showed that generally, the most useful preventive measures are indoor-residual sprayings, a combination of sprayings and insecticide-treated nets and rapid diagnostic tests. Furthermore, the effect of the population living in rural areas is significant. Besides, gross domestic product is a very important factor for African countries. The stability analysis - bootstrapping - confirmed our results. However, we examined that insecticide-treated nets are still the most distributed measures. Doing the cluster analysis, we observed that countries on the same continent should not be treated similarly and we emphasized countries that should receive higher attention. Overall, the...
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Modern stochastic claims reserving methods in insurance and their comparison
Vosáhlo, Jaroslav ; Pešta, Michal (advisor) ; Mazurová, Lucie (referee)
This thesis deals with an issue of claims reserving for non-life insurance. The issue is approached in a sense of analytical calculation and stochastic modelling. First, Chain-ladder, Bornhuetter-Ferguson, Benktander-Hovinen and Cape-Cod method are introduced. In following chapters, we try to find related stochastic underlying models including Generalized linear models and Mack's distribution-free approaches, we analyze second moments of claims estimates for each of the methods and examine alternative Merz-Wüthrich approach to reserve risk measurement. At the end, bootstrap algorithm and estimates are suggested and simulation results are compared with analytic ones.
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Long-term memory detection with bootstrapping techniques: empirical analysis
Albert, Branislav ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
A time series has long range dependence if its autocorrelation function is not absolutely convergent. Presence of long memory in a time series has important consequences for consistency of several time series estimators and forecasting. We present a self-contained theoretical treatment of time series models necessary for study of long range dependence and survey a large list of parametric and semiparametric estimators of long range dependence. In a Monte Carlo study, we compare size and power properties of four estimators, namely R/S, DFA, GPH and Wavelet based method, when relying on asymptotic normality of the estimators and distributions obtained from the moving block bootstrap. We find out that the moving block bootstrap can improve the size of the R/S estimator. In general however, the moving block bootstrap did not perform satisfactorily for other estimators. GPH and Wavelet estimators offer the most reliable asymptotic confidence intervals.
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Bootstrap methods in phylogenetics
Sedlář, Karel ; Vohánka,, Jaroslav (referee) ; Škutková, Helena (advisor)
In recent decades, phylogenetic reconstruction has noted great development. It was achieved by using newly acquired molecular characteristics and processing that it began to be taken as an objective science. Rapid development showed that it is necessary to evaluate the results because new techniques provided phylograms from unreliable data. For these purposes, statistical sampling methods have been applied to the phylogeny, of which bootstrapping began later to dominate. However, it also has limitations, which should be considered during interpreting the results it provided to us. This work demonstrates by combining the principles of bootstrapping and consensus trees we can obtain phylograms with better properties than those of conventional phylograms.
|
|
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Statistic evaluation of phylogeny of biological sequences
Vadják, Šimon ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
The master's thesis provides a comprehensive overview of resampling methods for testing the correctness topology of the phylogenetic trees which estimate the process of phylogeny on the bases of biological sequences similarity. We focused on the possibility of errors creation in this estimate and the possibility of their removal and detection. These methods were implemented in Matlab for Bootstrapping, jackknifing, OTU jackknifing and PTP test (Permutation tail probability). The work aims to test their applicability to various biological sequences and also to assess the impact of the choice of input analysis parameters on the results of these statistical tests.
|
|
|
Statistic evaluation of phylogeny of biological sequences
Zembol, Filip ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
The topic of my diploma thesis is the statistical evaluation of biological sequences with the help of phylogenic trees. In the theoretical part we will create a literary recherche of estimation methodology concerning the course of phylogeny on the basis of the similarity of biological sequences (DNA and proteins) and we will focus on the inaccuracies of the estimation, their causes and the possibilities of their elimination. Afterwards, we will compare the methods for the statistical evaluation of the correctness of the course of phylogeny. In the practical part of the thesis we will suggest algorithms that will be used for testing the correctness of the phylogenic trees on the basis of bootstrapping, jackknifing, OTU jackknifing and PTP test which are able to the capture phylogenic tree with the method neighbor joining from the biological sequences in FASTA code. It is also possible to change the distance model and the substitution matrix. To be able to use these algorithms for the statistical support of phylogenic trees we have to verify their right function. This verification will be evaluated on the theoretical sequences of the amino acids. For the verification of the correct function of the algorithms, we will carry out single statistical tests on real 10 sequences of mammalian ubiquitin. These results will be analysed and appropriately discussed.
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