Ce travail établit des inégalités d’information non-asymptotiques dans le cadre de l’estimation espaces propres d’un opérateur covariance. Ces résultats généralisent d’une part minorations antérieures valables pour modèle perturbation la covariance, et montrent d’autre l’optimalité majorations récentes établies modèles sous contraintes décroissance valeurs propres. La preuve repose sur nouvelle...

As a useful alternative to the Cox proportional hazards model, the linear regression survival model assumes a linear relationship between the covariates and a known monotone transformation, for example logarithm, of an event time of interest. In this article, we study the linear regression survival model with right censored survival data, when high-dimensional microarray measurements are presen...

to determine the yield stability, adaptability and analysis of the genotype× environment interaction of virginia tobacco, 15 hybrids of tobacco including 10 iranian and 5 international hybrids were evaluated in two different experiments (water stress and normal irrigation) using a randomized complete block design (rcbd) with three replications at two locations including rasht and tirtash tobacc...

Facial expression recognition has different applications in the real world. We present a method to identify facial expressions taken from camera and build a parallel facial expression recognition system. A statistical technique such as Principal Component Analysis is used for dimensionality reduction and recognition and widely used for facial feature extraction and recognition. To test and eval...

A novel spectral imaging method for the classification of light-induced autofluorescence spectra based on principal component analysis (PCA), a multivariate statistical analysis technique commonly used for studying the statistical characteristics of spectral data, is proposed and investigated. A set of optical spectral filters related to the diagnostically relevant principal components is propo...

We show how to efficiently project a vector onto the top principal components of a matrix, without explicitly computing these components. Specifically, we introduce an iterative algorithm that provably computes the projection using few calls to any black-box routine for ridge regression. By avoiding explicit principal component analysis (PCA), our algorithm is the first with no runtime dependen...

[1] This paper analyzes MODIS 1 km albedo kernels of 7 spectral bands over Northern Africa and the Arabian Peninsula and through these kernels develops a new high quality dataset that provides a simple statistical method to scale up spectral and broadband albedos from pixel to arbitrary coarse resolution grid square for use in climate models. This dataset significantly improves characterization...

In this work, we propose a frame selection scheme based on the smoothed instantaneous energy of samples, local order statistics for them, and average of a binary energy indicator over the frame to measure the reliability of frames. By selection of reliable frames, a four-stage feature normalization and transformation process is further proposed: mean normalization, variance normalization, first...

abstract climate change means a significant change in the long-term weather of a region in comparison with what has been observed during a long term period. precipitation and minimum and maximum temperature are three variables which are affected directly by the climate change. furthermore, the water yield of a river is one of the most important hydrological variables of a basin which is affecte...

Chemometric methods can enhance geochemical interpretations, especially when working with large datasets. With this aim, exploratory hierarchical cluster analysis (HCA) and principal component analysis (PCA) methods are used herein to study the bulk pyrolysis parameters of 534 samples from the Persian Gulf basin. These methods are powerful techniques for identifying the patterns of variations i...