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It has been argued by Daryl Bem in his 2011 paper that 8 out of 9 experiments yielded statistically significant results in favour of the psi effect.
Multivariate Evolutionary Analyses in Astrophysics
Multivariate Evolutionary Analyses Astrophysics
2011/7/7
The large amount of data on galaxies, up to higher and higher redshifts, asks for sophisticated statistical approaches to build adequate classifications.
Identifying and understanding modular organizations is centrally important in the study of complex systems. Several approaches to this problem have been advanced, many framed in information-theoretic ...
Semi-Blind System Identification in Wireless Relay Networks via Gaussian Process Iterated Conditioning on the Modes Estimation
Relay networks System Identification Gaussian processes Kernel methods
2011/7/7
This paper presents a flexible stochastic model developed for a class of cooperative wireless relay networks, in which the relay processing functionality is not known at the destination. The challenge...
Goodness-of-Fit tests with Dependent Observations
Extreme value statistics Stochastic processes Models of financial markets
2011/7/7
We revisit the Kolmogorov-Smirnov and Cram\'er-von Mises goodness-of-fit (GoF) tests and propose a generalisation to identically distributed, but dependent univariate random variables. We show that th...
In this paper, we consider the problem of compressed sensing where the goal is to recover almost all the sparse vectors using a small number of fixed linear measurements. For this problem, we propose ...
Omni-tomography/Multi-tomography -- Integrating Multiple Modalities for Simultaneous Imaging
Tomography CT MRI PET SPECT US imaging optical imaging functional imaging
2011/7/6
Current tomographic imaging systems need major improvements, especially when multi-dimensional, multi-scale, multi-temporal and multi-parametric phenomena are under investigation.
Research on the visitor flow pattern of Expo 2010
Visitor flow visibility graph complex network time series Expo
2011/7/6
Expo 2010 Shanghai China was a successful, splendid and unforgettable event, remaining us with valuable experiences. The visitor flow pattern of Expo is investigated in this paper. The Hurst exponent,...
Considerate Approaches to Achieving Sufficiency for ABC model selection
Considerate Approaches Achieving Sufficiency ABC model selection
2011/7/6
For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to ...
Kernels for Vector-Valued Functions: a Review
Kernels for Vector-Valued Functions: a Review
2011/7/6
Kernel methods are among the most popular techniques in machine learning. From a frequentist/discriminative perspective they play a central role in regularization theory as they provide a natural choi...
Grouped Variable Selection via Nested Spike and Slab Priors
Log-sum approximation Majorization-minimization algorithms
2011/7/6
In this paper we study grouped variable selection problems by proposing a specified prior, called the nested spike and slab prior, to model collective behavior of regression coefficients.
Statistical Distribution of Crystallographic Groups for Inorganic Crystal Structure Database
Statistical Distribution Crystallographic Groups Inorganic Crystal Structure Database
2011/7/6
We introduce a method that defines the species (representatives) of inorganic compounds, and studied the statistical distribution of the defined species among space groups (distribution of space group...
A pseudo-RIP for multivariate regression
Multivariate regression Restricted Isometry Property
2011/7/6
We give a suitable RI-Property under which recent results for trace regression translate into strong risk bounds for multivariate regression. This pseudo-RIP is compatible with the setting $n < p$.
Revealing spatial variability structures of geostatistical functional data via Dynamic Clustering
functional data clustering geostatistics variogram
2011/7/6
In several environmental applications data are functions of time, essentially con- tinuous, observed and recorded discretely, and spatially correlated. Most of the methods for analyzing such data are ...
k-Nearest neighbor density estimation on Riemannian Manifolds
Asymptotic results Density estimation Meteorological applications
2011/7/6
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belong in a Riemannian manifolds.