第23回名古屋大学年代測定総合研究センターシンポジウム平成22(2010)年度報告

Nonparametric Bayesian models have been researched extensively in the past 10 years following the work of Escobar and West (1995) on sampling schemes for Dirichlet processes. The infinite mixture representation of the Dirichlet process makes it useful for clustering problems where the number of clusters is unknown. We develop nonparametric Bayesian models for two different clustering problems, namely functional and graphical clustering. We propose a nonparametric Bayes wavelet model for clustering of functional or longitudinal data. The wavelet modelling is aimed at the resolution of global and local features during clustering. The model also allows the elicitation of prior belief about the regularity of the functions and has the ability to adapt to a wide range of functional regularity. Posterior inference is carried out by Gibbs sampling with conjugate priors for fast computation. We use simulated as well as real datasets to illustrate the suitability of the approach over other alternatives. The functional clustering model is extended to analyze splice microarray data. New microarray technologies probe consecutive segments along genes to observe alternative splicing (AS) mechanisms that produce multiple proteins from a single gene. Clues regarding the number of splice forms can be obtained by clustering the functional expression profiles from different tissues. The analysis was carried out on the Rosetta dataset (Johnson et al., 2003) to obtain a splice variant by tissue distribution for all the 10,000 genes. We were able to identify a number of splice forms that appear to be unique to cancer. We propose a Bayesian model for partitioning graphs depicting dependencies in a collection of objects. After suitable transformations and modelling techniques, the problem of graph cutting can be approached by nonparametric Bayes clustering. We draw motivation from a recent work (Dhillon, 2001) showing the equivalence of kernel k-means clustering and certain graph cutting algorithms. It is shown that loss functions similar to the kernel k-means naturally arise in this model, and the minimization of associated posterior risk comprises an effective graph cutting strategy. We present here results from the analysis of two microarray datasets, namely the melanoma dataset (Bittner et al., 2000) and the sarcoma dataset (Nykter et al., 2006).

Accurately estimating hydrocarbon reserves is important, because it affects every phase of the oil and gas business. Unfortunately, reserves estimation is always uncertain, since perfect information is seldom available from the reservoir, and uncertainty can complicate the decision-making process. Many important decisions have to be made without knowing exactly what the ultimate outcome will be from a decision made today. Thus, quantifying the uncertainty is extremely important. Two methods for estimating original hydrocarbons in place (OHIP) are volumetric and material balance methods. The volumetric method is convenient to calculate OHIP during the early development period, while the material balance method can be used later, after performance data, such as pressure and production data, are available. In this work, I propose a methodology for using a Bayesian approach to quantify the uncertainty of original gas in place (G), aquifer productivity index (J), and the volume of the aquifer (Wi) as a result of combining volumetric and material balance analysis in a water-driven gas reservoir. The results show that we potentially have significant non-uniqueness (i.e., large uncertainty) when we consider only volumetric analyses or material balance analyses. By combining the results from both analyses, the non-uniqueness can be reduced, resulting in OGIP and aquifer parameter estimates with lower uncertainty. By understanding the uncertainty, we can expect better management decision making.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xii, 138 p.; also includes graphics. Includes abstract and vita. Advisor: Greg M. Allenby, Dept. of Business Admnistration. Includes bibliographical references (p. 134-138).

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 192-195). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 192-195). Also available on the Internet.

In evaluating a prospective NBA player, one might consider past performance in the player’s previous years of competition. In doing so, a general manager may ask the following questions: Do certain characteristics of a player’s past statistics play a role in how long a player will last in the NBA? In this study, we examine the data from players who entered in the NBA in a five-­‐year period (1997-­‐1998 through 2001-­‐2002 season) by looking at their attributes from their collegiate career to see if they have any effect on their career longevity. We will look at basic statistics take for each of these players, such as field goal percentage, points per game, rebounds per game and assists per game. We aim to use Bayesian survival methods to model these event times, while exploiting the hierarchical nature of the data. We will look at two types of models and perform model diagnostics to determine which of the two we prefer. / text

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Due to the nature of survey design, the estimation of parameters associated with small areas is extremely problematic. In this study, techniques for the estimation of small area proportions are proposed and implemented. More specifically, empirical Bayes estimation methodologies, where random effects which reflect the complex structure of a multi-stage sample design are incorporated into logistic regression models, are derived and studied. / The proposed techniques are applied to data from the 1950 United States Census to predict local labor force participation rates of females. Results are compared with those obtained using unbiased and synthetic estimation approaches. / Using the proposed methodologies, a sensitivity analysis concerning the prior distribution assumption, conducted with a view toward outlier detection, is performed. The use of bootstrap techniques to correct measures of uncertainty is also studied.

In this study, mitochondrial transcript information from a recent EST project wasextended to obtain complete mitochondrial genome sequence for 5 tiger salamandercomplex species (Ambystoma mexicanum, A. t. tigrinum, A. andersoni, A. californiense,and A. dumerilii). For the first time, aspects of mitochondrial transcription in arepresentative amphibian are described, and then complete mitochondrial sequencedata are used to examine salamander phylogeny at both deep and shallow levels ofevolutionary divergence. The available mitochondrial ESTs for A. mexicanum (N=2481)and A. t. tigrinum (N=1205) provided 92% and 87% coverage of the mitochondrialgenome, respectively. Complete mitochondrial sequences for all species were rapidlyobtained by using long distance PCR and DNA sequencing. A number of genomestructural characteristics (base pair length, base composition, gene number, geneboundaries, codon usage) were highly similar among all species and to other distantlyrelated salamanders. Overall, mitochondrial transcription in Ambystoma approximatedthe pattern observed in other vertebrates. From the mapping of ESTs onto mtDNA it wasinferred that transcription occurs from both heavy and light strand promoters andcontinues around the entire length of the mtDNA, followed by post-transcriptionalprocessing. However, the observation of many short transcripts corresponding to rRNAgenes indicates that transcription may often terminate prematurely to bias transcriptionof rRNA genes; indeed an rRNA transcription termination signal sequence was observedimmediately following the 16S rRNA gene. Phylogenetic analyses of salamander familyrelationships consistently grouped Ambystomatidae in a clade containingCryptobranchidae and Hynobiidae, to the exclusion of Salamandridae. This robust resultsuggests a novel alternative hypothesis because previous studies have consistentlyidentified Ambystomatidae and Salamandridae as closely related taxa. Phylogeneticanalyses of tiger salamander complex species also produced robustly supported trees.The D-loop, used in previous molecular phylogenetic studies of the complex, was foundto contain a relatively low level of variation and we identified mitochondrial regions withhigher rates of molecular evolution that are more useful in resolving relationships amongspecies. Our results show the benefit of using complete mitochondrial genomeinformation in studies of recently and rapidly diverged taxa.