Statistical modeling of space shuttle environmental data

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application

Random harmonic analysis program, L221 (TEV156). Volume 2: Supplemental system design and maintenenace document

Volume 2 of a two volume document is presented. A computer program, L222 (TEV 156), available for execution on the CDC 6600 computer is described. The program is capable of calculating steady-state solutions for linear second-order differential equations due to sinusoidal forcing functions. From this, steady-state solutions, generalized coordinates, and load frequency responses may be determined. Statistical characteristics of loads for the forcing function spectral shape may also be calculated using random harmonic analysis techniques. The particular field of application of the program is the analysis of airplane response and loads due to continuous random air turbulence

A Variational Stereo Method for the Three-Dimensional Reconstruction of Ocean Waves

We develop a novel remote sensing technique for the observation of waves on the ocean surface. Our method infers the 3-D waveform and radiance of oceanic sea states via a variational stereo imagery formulation. In this setting, the shape and radiance of the wave surface are given by minimizers of a composite energy functional that combines a photometric matching term along with regularization terms involving the smoothness of the unknowns. The desired ocean surface shape and radiance are the solution of a system of coupled partial differential equations derived from the optimality conditions of the energy functional. The proposed method is naturally extended to study the spatiotemporal dynamics of ocean waves and applied to three sets of stereo video data. Statistical and spectral analysis are carried out. Our results provide evidence that the observed omnidirectional wavenumber spectrum S(k) decays as k-2.5 is in agreement with Zakharov's theory (1999). Furthermore, the 3-D spectrum of the reconstructed wave surface is exploited to estimate wave dispersion and currents

Range-based techniques for discovering optimality and analyzing scaling relationships in neuromechanical systems

In this paper, a method for decoupling the neuromuscular function of a set of limbs from the role morphology plays in regulating the performance of an activity is introduced. This method is based on two previous methods: the rescaled range analysis specific to time series data, and the use of scaling laws. A review of the literature suggests that limb geometry can either facilitate or constrain performance as measured experimentally. Whether limb geometry is facilitatory or acts as a constraint depends on the size differential between arm morphology and the underlying muscle. "Changes in size and shape" are theoretically extrapolations of morphological geometry to other members of a population or species, to other species, or to technological manipulations of an individual via prosthetic devices. Three datasets are analyzed using the range-based method and a Monte-Carlo simulation, and are used to test the various ways of executing this analysis. It was found that when performance is kept stable but limb size and shape is scaled by a factor of .25, the greatest gain in performance results. It was also found that introducing force-based perturbations results in 'shifts' in the body geometry/performance relationship. While results such as this could be interpreted as a statistical artifact, the non-linear rise within a measurement class and linear decrease between measurement classes suggests an effect of scale in the optimality of this relationship. Overall, range-based techniques allow for the simulation and modeling of myriad changes in phenotype that result from biological and technological manipulation

A Variational Wave Acquisition Stereo System for the 3-D Reconstruction of Oceanic Sea States

We propose a novel remote sensing technique that infers the three-dimensional wave form and radiance of oceanic sea states via a variational stereo imagery formulation. In this setting, the shape and radiance of the wave surface are minimizers of a composite cost functional which combines a data fidelity term and smoothness priors on the unknowns. The solution of a system of coupled partial differential equations derived from the cost functional yields the desired ocean surface shape and radiance. The proposed method is naturally extended to study the spatio-temporal dynamics of ocean waves, and applied to three sets of video data. Statistical and spectral analysis are carried out. The results shows evidence of the fact that the omni-directional wavenumber spectrum S(k) of the reconstructed waves decays as k^{-2.5} in agreement with Zakharov's theory (1999). Further, the three-dimensional spectrum of the reconstructed wave surface is exploited to estimate wave dispersion and currents

BNP-Seq: Bayesian Nonparametric Differential Expression Analysis of Sequencing Count Data

We perform differential expression analysis of high-throughput sequencing count data under a Bayesian nonparametric framework, removing sophisticated ad-hoc pre-processing steps commonly required in existing algorithms. We propose to use the gamma (beta) negative binomial process, which takes into account different sequencing depths using sample-specific negative binomial probability (dispersion) parameters, to detect differentially expressed genes by comparing the posterior distributions of gene-specific negative binomial dispersion (probability) parameters. These model parameters are inferred by borrowing statistical strength across both the genes and samples. Extensive experiments on both simulated and real-world RNA sequencing count data show that the proposed differential expression analysis algorithms clearly outperform previously proposed ones in terms of the areas under both the receiver operating characteristic and precision-recall curves.Comment: To appear in Journal of the American Statistical Associatio