High prices in any industry, agricultural especially, tend to spur new investment opportunities. Recent prices for pecans have been high relative to their historical pattern, suggesting investment opportunities for pecans. Prior to any investment, the investor needs to know what products consumers are demanding and how profitable it is to grow those products. This study assessed Texas consumers' preferences for pecan products and the profitability of growing pecans in the central Texas region. A choice experiment was conducted amongst Texas consumers to reveal consumers' preferences and determine their willingness-to-pay for the attributes comprising pecan products. A stochastic production model was formulated to determine the profitability of three different types of pecan orchards: a native orchard with no irrigation, an improved varieties orchard with irrigation, and an improved varieties orchard without irrigation. Results from the choice experiment indicated that consumers preferred large size pecans, native variety pecans, pecan halves, United States-grown pecans, and Texas-grown pecans. The choice experiment also found that consumers were heterogeneous in their preferences for all attributes except pecan variety and U.S. origin. Results from the stochastic production model indicated that the most profitable pecan orchard in central Texas was the irrigated improved orchard.

The shrinkage estimation has proven to be very useful when dealing with a large number of mean parameters. In this dissertation, we consider the problem of simultaneous estimation of multiple variances and construct a shrinkage type, non-parametric estimator. We take the non-parametric empirical Bayes approach by starting with an arbitrary prior on the variances. Under an invariant loss function, the resultant Bayes estimator relies on the marginal cumulative distribution function of the sample variances. Replacing the marginal cdf by the empirical distribution function, we obtain a Non-parametric Empirical Bayes estimator for multiple Variances (NEBV). The proposed estimator converges to the corresponding Bayes version uniformly over a large set. Consequently, the NEBV works well in a post-selection setting. We then apply the NEBV to construct condence intervals for mean parameters in a post-selection setting. It is shown that the intervals based on the NEBV are shortest among all the intervals which guarantee a desired coverage probability. Through real data analysis, we have further shown that the NEBV based intervals lead to the smallest number of discordances, a desirable property when we are faced with the current "replication crisis". / Statistics

The relative power of goodness-of-fit test statistics has long been debated in the literature. Chi-Square type test statistics to determine 'fit' for categorical data are still dominant in the goodness-of-fit arena. Empirical Distribution Function type goodness-of-fit test statistics are known to be relatively more powerful than Chi-Square type test statistics for restricted types of null and alternative distributions. In many practical applications researchers who use a standard Chi-Square type goodness-of-fit test statistic ignore the rank of ordinal classes. This thesis reviews literature in the goodness-of-fit field, with major emphasis on categorical goodness-of-fit tests. The continued use of an asymptotic distribution to approximate the exact distribution of categorical goodness-of-fit test statistics is discouraged. It is unlikely that an asymptotic distribution will produce a more accurate estimation of the exact distribution of a goodness-of-fit test statistic than a Monte Carlo approximation with a large number of simulations. Due to their relatively higher powers for restricted types of null and alternative distributions, several authors recommend the use of Empirical Distribution Function test statistics over nominal goodness-of-fit test statistics such as Pearson's Chi-Square. In-depth power studies confirm the views of other authors that categorical Empirical Distribution Function type test statistics do not have higher power for some common null and alternative distributions. Because of this, it is not sensible to make a conclusive recommendation to always use an Empirical Distribution Function type test statistic instead of a nominal goodness-of-fit test statistic. Traditionally the recommendation to determine 'fit' for multivariate categorical data is to treat categories as nominal, an approach which precludes any gain in power which may accrue from a ranking, should one or more variables be ordinal. The presence of multiple criteria through multivariate data may result in partially ordered categories, some of which have equal ranking. This thesis proposes a modification to the currently available Kolmogorov-Smirnov test statistics for ordinal and nominal categorical data to account for situations of partially ordered categories. The new test statistic, called the Combined Kolmogorov-Smirnov, is relatively more powerful than Pearson's Chi-Square and the nominal Kolmogorov-Smirnov test statistic for some null and alternative distributions. A recommendation is made to use the new test statistic with higher power in situations where some benefit can be achieved by incorporating an Empirical Distribution Function approach, but the data lack a complete natural ordering of categories. The new and established categorical goodness-of-fit test statistics are demonstrated in the analysis of categorical data with brief applications as diverse as familiarity of defence programs, the number of recruits produced by the Merlin bird, a demographic problem, and DNA profiling of genotypes. The results from these applications confirm the recommendations associated with specific goodness-of-fit test statistics throughout this thesis.

The diploma thesis Risks of using VaR models for portfolio management is focused on estimation of the portfolio VaR using basic and modified methods. The goal of this thesis is to point out some weakness of the basic methods and to demonstrate the estimation of VaR using improved methods to overcome these problems. The analysis will be perform theoretically and in practice. Only market risk will be the subject of the study. Several simulation and parametric methods will be introduced.

I detta arbete har studerats hur flödet i en flerstegs- bearbetningsprocess påverkas av stokastiska fluktuationer och störningar i de enskilda processtegen. Mera bestämt har analys utförts av hur de stokastiska variationerna i operationstiderna kan och bör modelleras vid simuleringsstudier. Även hur påverkan av valet av sådana stokastiska modeller kan tänkas ha på processen i sin helhet, till exempel avseende total genomloppstid. Examensarbetet syftar till att undersöka hur val av fördelning på parametern operationstid, påverkar resultatfaktorn genomloppstid vid flödessimuleringar. För att finna svar på denna påverkan har en fallstudie utförts, med utgångspunkt av indata från en produkt som tillverkas på Volvo Aero. Denna produkt genomgår en tillverkningssekvens innehållande 18 stycken bearbetningsoperationer innefattande tre olika processtyper (automatisk, halvautomatisk och manuell). Dessa tre processtyper är i olika grad beroende av operatörers insats. De 18 bearbetningsoperationernas processtid har analyserats numeriskt och grafiskt. Programvaran Stat:fit har använts som hjälpmedel för att erhålla svar på lämplig fördelning per tillverkningsoperation samt vilka teoretiska fördelningar som är lämpliga att använda för de tre olika processtyperna. De rekommenderade fördelningsteorierna per tillverkningsoperation har genomgått fördelningstest (Chi2, Kolmogorov-Smirnov och Anderson-Darling) och använts som grund vid skapande av försöksplan till simuleringsstudien. Simuleringsstudien har utförts enligt försöksplan i programvaran Simul8. Samtliga körningar från simuleringsmodellen är statistiskt säkerställda med 95 % konfidensintervall. Fallstudien har visat att resultatpåverkan från operationstidernas fördelningstyp är relativt liten vid simulering av komplexa system där faktorer som nivå av tillverkningsvolym och tillgänglighet har större påverkan på resultatfaktorn genomloppstid. Vid enklare modeller utan begränsning i form av reducerad tillgänglighet synliggörs skillnad i simuleringsresultat av olika val av fördelning på parametern operationstid. Fördelningen av dessa simuleringsresultat styrks av den centrala gränsvärdessatsen, det vill säga att om antalet observerade värden är tillräckligt stort, uppträder resultatet som normalfördelat. / Discrete event simulation is used to imitate and analyze how systems change over time. The actual behavior of the variation in the system is interpreted by using discrete and continuous probability distributions. In the software program Simul8, simulation models are created based on the information collected from the production. Shifts, operation time and efficiency are examples of information required for the modeling process. The aim with this bachelor´s thesis was to investigate how different choice of probability distributions on the parameter operation time affects the result of a discrete event simulation. The thesis is a result of a case study performed at Volvo Aero Corporation, Sweden. The case study involves investigation of probability distribution for 18 manufacturing operations for a product. The manufacturing sequence consists of three different types of processes (automatic, semiautomatic and manual). These three types of processes need different level of instrumentality. The commercial statistical computer software, Stat:fit has been used to find proper probability distribution for each of the manufacturing operations. The results from Stat:fit have been used to analyze if there are any connections between the process type and the probability distributions. The recommended probability distributions have been tested with Goodness-of-fit tests (Chi2, Kolmogorov-Smirnov and Anderson-Darling) using Stat:fit and used in the simulation modeling. The simulation model has been validated and verified by a simulation advisor at Volvo Aero. Five different simulation models have been evaluated in Simul8, with five different types of distributions. All simulation runs have been statistical proved, in Simul8 with 95% confidence interval. The result of this study indicates that the variation of process time has limited effect for complex simulation models containing low level of efficiency and high load factors, concerning the result of throughput time. For simple models, excluded from restricted efficiency, the effect on the throughput time is featured.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-02T21:21:48Z No. of bitstreams: 1 ALINE BARBOSA TSUYUGUCHI - DISSERTAÇÃO PPGMAT 2012..pdf: 613833 bytes, checksum: c354cd90842e461c0fb29b0ee5f925d3 (MD5) / Made available in DSpace on 2018-08-02T21:21:48Z (GMT). No. of bitstreams: 1 ALINE BARBOSA TSUYUGUCHI - DISSERTAÇÃO PPGMAT 2012..pdf: 613833 bytes, checksum: c354cd90842e461c0fb29b0ee5f925d3 (MD5) Previous issue date: 2012-02 / CNPq / Neste trabalho estudamos testes de bondade de ajuste para a distribuição Birnbaum-Saunders. Consideramos testes clássicos baseados em função de distribuição empírica (Anderson-Darling, Cramér-von Mises e Kolmogorov-Sminorv) e baseados em função característica empírica. Nos limitamos ao caso onde o vetor de parâmetros é desconhecido e, portanto deverá ser estimado. Apresentamos estudos de simulação para verificar o desempenho das estatísticas de teste em estudo. Além disso, propomos estudos de simulação de Monte Carlo para testes de bondade de ajuste para a distribuição Birnbaum-Saunders com dados com censura tipo II. / In this work we study goodness-of-fit tests for Birnbaum-Saunders distribution. We consider classical tests based on empirical distribution function (Anderson-Darling, Cramér-von Mises e Kolmogorov-Sminorv) and based on empirical characteristic function. We limited this study to the case in which the vector of parameters is unknown and, therefore, must be estimated. We present the simulation studies to verify the performance of the test statistics in study. Also, we propose simulation studies of Monte Carlo for goodness-of-fit test for Birnbaum-Saunders distribution using Type-II censored data.

Au cours des dernières années, des changements importants dans le domaine des assurances et des finances attirent de plus en plus l’attention sur la nécessité d’élaborer un cadre normalisé pour la mesure des risques. Récemment, il y a eu un intérêt croissant de la part des experts en assurance sur l’utilisation de l’espérance conditionnelle des pertes (CTE) parce qu’elle partage des propriétés considérées comme souhaitables et applicables dans diverses situations. En particulier, il répond aux exigences d’une mesure de risque “cohérente”, selon Artzner [2]. Cette thèse représente des contributions à l’inférence statistique en développant des outils, basés sur la convergence des intégrales fonctionnelles, pour l’estimation de la CTE qui présentent un intérêt considérable pour la science actuarielle. Tout d’abord, nous développons un outil permettant l’estimation de la moyenne conditionnelle E[X|X > x], ensuite nous construisons des estimateurs de la CTE, développons la théorie asymptotique nécessaire pour ces estimateurs, puis utilisons la théorie pour construire des intervalles de confiance. Pour la première fois, l’approche de bootstrap non paramétrique est explorée dans cette thèse en développant des nouveaux résultats applicables à la valeur à risque (VaR) et à la CTE. Des études de simulation illustrent la performance de la technique de bootstrap.

This diploma thesis focuses on the statistical examination of properties of plant protection products at Agro-Artikel, s.r.o. Using the empirical distribution function, it focuses on the sales price and the shelf life of the products, tests the hypotheses about the properties of the products and the dependencies between them. The thesis also explores the results of the questionnaire survey and offers recommendations for the introduction of new products.

Masters of Science / The multivariate two-sample tests provide a means to test the match between two multivariate distributions. Although many tests exist in the literature, relatively little is known about the relative power of these procedures. The studies reported in the thesis contrasts the effectiveness, in terms of power, of seven such tests with a Monte Carlo study. The relative power of the tests was investigated against location, scale, and correlation alternatives. Samples were drawn from bivariate exponential, normal and uniform populations. Results from the power studies show that there is no single test which is the most powerful in all situations. The use of particular test statistics is recommended for specific alternatives. A possible supplementary non-parametric graphical procedure, such as the Depth-Depth plot, can be recommended for diagnosing possible differences between the multivariate samples, if the null hypothesis is rejected. As an example of the utility of the procedures for real data, the multivariate two-sample tests were applied to photometric data of twenty galactic globular clusters. The results from the analyses support the recommendations associated with specific test statistics.

This thesis concentrates on different approaches of solving decision making problems with an aspect of randomness. The basic methodologies of converting stochastic optimization problems to deterministic optimization problems are described. The proximity of solution of a problem and its empirical counterpart is shown. The empirical counterpart is used when we don't know the distribution of the random elements of the former problem. The distribution with heavy tails, stable distribution and their relationship is described. The stochastic dominance and the possibility of defining problems with stochastic dominance is introduced. The proximity of solution of problem with second order stochastic dominance and the solution of its empirical counterpart is proven. A portfolio management problem with second order stochastic dominance is solved by solving the equivalent empirical problem. Powered by TCPDF (www.tcpdf.org)