186 research outputs found
Inferences from prior-based loss functions
Inferences that arise from loss functions determined by the prior are
considered and it is shown that these lead to limiting Bayes rules that are
closely connected with likelihood. The procedures obtained via these loss
functions are invariant under reparameterizations and are Bayesian unbiased or
limits of Bayesian unbiased inferences. These inferences serve as
well-supported alternatives to MAP-based inferences
Invariant -values for model checking
-values have been the focus of considerable criticism based on various
considerations. Still, the -value represents one of the most commonly used
statistical tools. When assessing the suitability of a single hypothesized
distribution, it is not clear that there is a better choice for a measure of
surprise. This paper is concerned with the definition of appropriate
model-based -values for model checking.Comment: Published in at http://dx.doi.org/10.1214/09-AOS727 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Weak Informativity and the Information in One Prior Relative to Another
A question of some interest is how to characterize the amount of information
that a prior puts into a statistical analysis. Rather than a general
characterization, we provide an approach to characterizing the amount of
information a prior puts into an analysis, when compared to another base prior.
The base prior is considered to be the prior that best reflects the current
available information. Our purpose then is to characterize priors that can be
used as conservative inputs to an analysis relative to the base prior. The
characterization that we provide is in terms of a priori measures of prior-data
conflict.Comment: Published in at http://dx.doi.org/10.1214/11-STS357 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Design and Experimental Validation of a Control System for Dynamic Positioning of a Shuttle Tanker
In this paper, a dynamic positioning performance evaluation procedure for a shuttle tanker is discussed through experimental and numerical analyses. A dynamically positioned shuttle tanker with six thrusters (three tunnel thrusters, two azimuth thrusters, and one main propeller with a rudder), operated in deep water condition was considered. A conventional proportional-derivative control algorithm was adopted for the main feedback control algorithm to reduce the position error, and an anti-windup integral control algorithm was introduced to suppress the steady-state error in the dynamic positioning operation. A minimum power consumption algorithm, based on the Lagrange multiplier method, was utilised in the thrust allocation for the thruster systems. An extended Kalman filter was used in the experiment to separate the low-frequency motion from the measured vessel motion. A set of experiments and numerical analyses were conducted in this study under the same environmental conditions and with the same control methodology. The dynamic positioning operation results obtained by the experiments and numerical simulations were compared to evaluate the station-keeping performance of the dynamically positioned shuttle tanker
WaveCNV: allele-specific copy number alterations in primary tumors and xenograft models from next-generation sequencing.
MotivationCopy number variations (CNVs) are a major source of genomic variability and are especially significant in cancer. Until recently microarray technologies have been used to characterize CNVs in genomes. However, advances in next-generation sequencing technology offer significant opportunities to deduce copy number directly from genome sequencing data. Unfortunately cancer genomes differ from normal genomes in several aspects that make them far less amenable to copy number detection. For example, cancer genomes are often aneuploid and an admixture of diploid/non-tumor cell fractions. Also patient-derived xenograft models can be laden with mouse contamination that strongly affects accurate assignment of copy number. Hence, there is a need to develop analytical tools that can take into account cancer-specific parameters for detecting CNVs directly from genome sequencing data.ResultsWe have developed WaveCNV, a software package to identify copy number alterations by detecting breakpoints of CNVs using translation-invariant discrete wavelet transforms and assign digitized copy numbers to each event using next-generation sequencing data. We also assign alleles specifying the chromosomal ratio following duplication/loss. We verified copy number calls using both microarray (correlation coefficient 0.97) and quantitative polymerase chain reaction (correlation coefficient 0.94) and found them to be highly concordant. We demonstrate its utility in pancreatic primary and xenograft sequencing data.Availability and implementationSource code and executables are available at https://github.com/WaveCNV. The segmentation algorithm is implemented in MATLAB, and copy number assignment is implemented [email protected] informationSupplementary data are available at Bioinformatics online
STATIC AND DYNAMIC CHARACTERISTICS OF AIR FOIL THRUST BEARING CONSIDERING TILTING PAD CONDITION
ABSTRACT The thrust pad of the rotor is used to sustain the axial force generated due to the pressure difference between the compressor and turbine sides of turbomachinery such as the gas turbines and turbochargers. Furthermore, this thrust pad has a role to maintain and determines the attitude of the rotor. In a real system, it also helps reinforce the stiffness and damping of the journal bearing. This study was performed for the purpose of analyzing the characteristics of the air foil thrust bearing. The model for the air foil thrust bearing used in this study is composed of two parts: one is an inclined plane, which plays a role to increase the load carrying capacity using the physical wedge effect, and the other is a flat plane. This study mainly consists of three parts. First, the static characteristics were obtained over the region of the thin air film using the finite difference method (FDM) and the bump foil characteristics using the finite element method (FEM). Second, the analysis of the dynamic characteristics was conducted by perturbation method. For more exact calculation, the rarefaction gas coefficients perturbed about the pressure and film thickness were taken into consideration. At last, the static and dynamic characteristics of the tilting condition of the thrust pad were obtained. Furthermore, the load carrying capacity and torque were calculated for both tilting and not-tilting conditions. From this study, several results were presented: 1) the stiffness and damping of the bump foil under the condition of the various bump parameters, 2) the load carrying capacity and bearing torque at the tilting state, 3) the bearing performance under various bearing parameters, 4) the effects considering the rarefaction gas coefficients
Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma
PURPOSE: With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk.
MATERIALS AND METHODS: We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early deathâ1 year or lessâafter surgery in a subset of 823 samples with available transcriptomics and survival data.
RESULTS: The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 (P = 2.6Eâ22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4Eâ04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairsâ1,070 unique genesâunveiled pathways associated with Hedgehog signaling, epithelialâmesenchymal transition, and extracellular matrix signaling.
CONCLUSION: PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial
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