Related papers: The Four-Year COBE Normalization and Large-Scale S…
We present a detailed analysis of the cosmic microwave background structure in the Tenerife Dec=+40 degrees data. The effect of local atmospheric contributions on the derived fluctuation amplitude is considered, resulting in an improved…
The possibility of determining cosmological parameters on the basis of a wide set of observational data including the Abell-ACO cluster power spectrum and mass function, peculiar velocities of galaxies, the distribution of Ly-$\alpha$…
ABSRACT: We review recent progress on testing the hypothesis of the existence of cosmic string perturbations in microwave background maps. Using an analytical model for the string network we show that the predicted amplitude and spectrum of…
We have measured the topology (genus) of the fluctuations in the cosmic microwave background seen in the recently completed (four-year) data set produced by the COBE satellite. We find that the genus is consistent with that expected from a…
Evaluation of likelihood functions for cosmological large scale structure data sets (including CMB, galaxy redshift surveys, etc.) naturally involves marginalization, i.e., integration, over an unknown underlying random signal field.…
We estimate the power spectrum of mass density fluctuations from peculiar velocities of galaxies by applying an improved maximum-likelihood technique to the new all-sky SFI catalog. Parametric models are used for the power spectrum and the…
We develop technique concerning statistical analyses of the large-scale structure of the universe in the presence of biasing in the structure formation. We formulate the diagrammatic method to calculate the correlation functions of the…
The purpose of this study is to explore three numerical approaches to the elastic homogenization of disordered masonry structures with moderate meso/macro-lengthscale ratio. The methods investigated include a representative of perturbation…
The normal parameters are a non--linear transformation of the cosmological parameters whose likelihood function is very well--approximated by a normal distribution. This transformation serves as an extreme form of data compression allowing…
We propose a methodology for improving the accuracy of surrogate models of the observable response of physical systems as a function of the systems' spatially heterogeneous parameter fields with applications to uncertainty quantification…
Axially symmetric processes on spheres, for which the second-order dependency structure may substantially vary with shifts in latitude, are a prominent alternative to model the spatial uncertainty of natural variables located over large…
Estimation of the mean vector and covariance matrix is of central importance in the analysis of multivariate data. In the framework of generalized linear models, usually the variances are certain functions of the means with the normal…
We discuss the algorithmic information approach to the analysis of the observational data on the Universe. Kolmogorov complexity is proposed as a descriptor of the Cosmic Microwave Background (CMB) radiation maps. An algorithm of…
Fourier analysis and power spectrum estimation of the cosmic microwave background anisotropy on an incompletely sampled sky developed by Gorski (1994) has been applied to the high-latitude portion of the 4-year COBE DMR 31.5, 53 and 90 GHz…
We compute the three-point temperature correlation function of the {\it COBE} Differential Microwave Radiometer (DMR) first-year sky maps to search for non-Gaussian temperature fluctuations. The level of fluctuations seen in the computed…
Shape-restricted inferences have exhibited empirical success in various applications with survival data. However, certain works fall short in providing a rigorous theoretical justification and an easy-to-use variance estimator with…
Approximation of elliptic PDEs with random diffusion coefficients typically requires a representation of the diffusion field in terms of a sequence $y=(y_j)_{j\geq 1}$ of scalar random variables. One may then apply high-dimensional…
We describe an approximate statistical model for the sample variance distribution of the non-linear matter power spectrum that can be calibrated from limited numbers of simulations. Our model retains the common assumption of a multivariate…
This article studies the limiting behavior of a class of robust population covariance matrix estimators, originally due to Maronna in 1976, in the regime where both the number of available samples and the population size grow large. Using…
We describe the Bayesian-based signal-to-noise eigenmode method for cosmological parameter estimation, show how it can be used to optimally compress large CMB anisotropy data sets to manageable sizes, and apply it to the DMR 4-year, South…