L'utilizzo del metodo Bootstrap nella statistica inferenziale

In questo lavoro viene introdotto il metodo Bootstrap, sviluppato a partire dal 1979 da Bradley Efron. Il Bootstrap è una tecnica statistica di ricampionamento basata su calcoli informatici, e quindi definita anche computer-intensive. In particolare vengono analizzati i vantaggi e gli svantaggi di tale metodo tramite esempi con set di dati reali implementati tramite il software statistico R. Tali analisi vertono su due tra i principali utilizzi del Bootstrap, la stima puntuale e la costruzione di intervalli di confidenza, basati entrambi sulla possibilità di approssimare la distribuzione campionaria di un qualsiasi stimatore, a prescindere dalla complessità di calcolo.

Métodos de bootstrap e aplicações em problemas biológicos

Pós-graduação em Matemática Universitária - IGCE

Teorema di Cochran e applicazioni

La statistica è un ramo della matematica che studia i metodi per raccogliere, organizzare e analizzare un insieme di dati numerici, la cui variazione è influenzata da cause diverse, con lo scopo sia di descrivere le caratteristiche del fenomeno a cui i dati si riferiscono, sia di dedurre, ove possibile, le leggi generali che lo regolano. La statistica si suddivide in statistica descrittiva o deduttiva e in statistica induttiva o inferenza statistica. Noi ci occuperemo di approfondire la seconda, nella quale si studiano le condizioni per cui le conclusioni dedotte dall'analisi statistica di un campione sono valide in casi più generali. In particolare l'inferenza statistica si pone l'obiettivo di indurre o inferire le proprietà di una popolazione (parametri) sulla base dei dati conosciuti relativi ad un campione. Lo scopo principale di questa tesi è analizzare il Teorema di Cochran e illustrarne le possibili applicazioni nei problemi di stima in un campione Gaussiano. In particolare il Teorema di Cochran riguarda un'importante proprietà delle distribuzioni normali multivariate, che risulta fondamentale nella determinazione di intervalli di fiducia per i parametri incogniti.

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Some factors complicate comparisons between linkage maps from different studies. This problem can be resolved if measures of precision, such as confidence intervals and frequency distributions, are associated with markers. We examined the precision of distances and ordering of microsatellite markers in the consensus linkage maps of chromosomes 1, 3 and 4 from two F 2 reciprocal Brazilian chicken populations, using bootstrap sampling. Single and consensus maps were constructed. The consensus map was compared with the International Consensus Linkage Map and with the whole genome sequence. Some loci showed segregation distortion and missing data, but this did not affect the analyses negatively. Several inversions and position shifts were detected, based on 95% confidence intervals and frequency distributions of loci. Some discrepancies in distances between loci and in ordering were due to chance, whereas others could be attributed to other effects, including reciprocal crosses, sampling error of the founder animals from the two populations, F(2) population structure, number of and distance between microsatellite markers, number of informative meioses, loci segregation patterns, and sex. In the Brazilian consensus GGA1, locus LEI1038 was in a position closer to the true genome sequence than in the International Consensus Map, whereas for GGA3 and GGA4, no such differences were found. Extending these analyses to the remaining chromosomes should facilitate comparisons and the integration of several available genetic maps, allowing meta-analyses for map construction and quantitative trait loci (QTL) mapping. The precision of the estimates of QTL positions and their effects would be increased with such information.

Método de Bootstrap e teoria da credibilidade na estimativa das provisões para sinistros

Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações, no ramo Actuariado, Estatística e Investigação Operacional

Dealing with frame imperfections in a business survey: an empirical study using without replacement bootstrap

This paper approaches issues related to frame problems and nonresponse in surveys. These nonsampling errors affect the accuracy of the estimates whereas the estimators became biased and less precise. We analyse some estimation methods that deal with those problems and give an especial focus to post-stratification procedures.

Bootstrap performance profiles in stochastic algorithms assessment

Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

Forecasting time series combining Holt-Winters and bootstrap approaches

Publicado em "AIP Conference Proceedings", Vol. 1648

A metodologia Bootstrap associada ao método de Holt-Winters na previsão de séries temporais

Os métodos de alisamento exponencial são muito utilizados na modelação e previsão de séries temporais, devido à sua versatilidade e opção de modelos que integram. Na estatística computacional, a metodologia Bootstrap é muito aplicada em inferência estatística no âmbito de séries temporais. Este estudo teve como principal objectivo analisar o desempenho do método de Holt-Winters associado à metodologia Bootstrap, como um processo alternativo na modelação e previsão de séries temporais.

A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

A Consistent Nonparametric Bootstrap Test of Exogeneity

This paper proposes a novel way of testing exogeneity of an explanatory variable without any parametric assumptions in the presence of a "conditional" instrumental variable. A testable implication is derived that if an explanatory variable is endogenous, the conditional distribution of the outcome given the endogenous variable is not independent of its instrumental variable(s). The test rejects the null hypothesis with probability one if the explanatory variable is endogenous and it detects alternatives converging to the null at a rate n..1=2:We propose a consistent nonparametric bootstrap test to implement this testable implication. We show that the proposed bootstrap test can be asymptotically justi.ed in the sense that it produces asymptotically correct size under the null of exogeneity, and it has unit power asymptotically. Our nonparametric test can be applied to the cases in which the outcome is generated by an additively non-separable structural relation or in which the outcome is discrete, which has not been studied in the literature.

Paranasal sinuses in children: size evaluation of maxillary, sphenoid, and frontal sinuses by magnetic resonance imaging and proposal of volume index percentile curves.

Our objective was to establish the age-related 3D size of maxillary, sphenoid, and frontal sinuses. A total of 179 magnetic resonance imaging (MRI) of children under 17 years (76 females, 103 males) were included and sinuses were measured in the three axes. Maxillary sinuses measured at birth (mean+/-standard deviation) 7.3+/-2.7 mm length (or antero-posterior)/4.0+/-0.9 mm height (or cranio-caudal)/2.7+/-0.8 mm width (or transverse). At 16 years old, maxillary sinus measured 38.8+/-3.5 mm/36.3+/-6.2 mm/27.5+/-4.2 mm. Sphenoid sinus pneumatization starts in the third year of life after conversion from red to fatty marrow with mean values of 5.8+/-1.4 mm/8.0+/-2.3 mm/5.8+/-1.0 mm. Pneumatization progresses gradually to reach at 16 years 23.0+/-4.5 mm/22.6+/-5.8 mm/12.8+/-3.1 mm. Frontal sinuses present a wide variation in size and most of the time are not valuable with routine head MRI techniques. They are not aerated before the age of 6 years. Frontal sinuses dimensions at 16 years were 12.8+/-5.0 mm/21.9+/-8.4 mm/24.5+/-13.3 mm. A sinus volume index (SVI) of maxillary and sphenoid sinus was computed using a simplified ellipsoid volume formula, and a table with SVI according to age with percentile variations is proposed for easy clinical application. Percentile curves of maxillary and sphenoid sinuses are presented to provide a basis for objective determination of sinus size and volume during development. These data are applicable to other techniques such as conventional X-ray and CT scan.