Search results for "Component analysis"
showing 10 items of 562 documents
Dimension Estimation in Two-Dimensional PCA
2021
We propose an automated way of determining the optimal number of low-rank components in dimension reduction of image data. The method is based on the combination of two-dimensional principal component analysis and an augmentation estimator proposed recently in the literature. Intuitively, the main idea is to combine a scree plot with information extracted from the eigenvectors of a variation matrix. Simulation studies show that the method provides accurate estimates and a demonstration with a finger data set showcases its performance in practice. peerReviewed
El panel de loterías como tarea no paramétrica para la obtención de la actitud frente al riesgo
2012
In this paper, we propose a simple task for eliciting attitudes toward risky choice, the Sabater-Grande and Georgantzís (SGG) lottery-panel task, which consists in a series of lotteries constructed to compensate riskier options with higher risk-return trade-offs. Using Principal Component Analysis technique, we show that the SGG lotterypanel task is capable of capturing two dimensions of individual risky decision making: subjects’ average willingness to choose risky projects and their sensitivity towards variations in the return to risk. We report results from a large dataset obtained from the implementation of the SGG lottery-panel task and discuss regularities and the desirability of its …
Geographic Distribution and Niche Divergence of Two Stinkbugs,Parastrachia japonensisandParastrachia nagaensis
2014
Parastrachiidae is a small stinkbug family containing only one genus and two species, Parastrachia japonensis (Scott) (Hemiptera: Heteroptera: Pentatomoidea) and Parastrachia nagaensis Distant. The geographic distribution of the genus has been poorly studied. Niche conservatism refers to that idea that closely related species are more ecologically similar than would be expected, whereas niche divergence predicts they occupy distinct niche spaces. The existence of only two species within one genus suggests niche conservatism or differentiation might exist among them. Herein, the distribution of the genus was mapped, potential distributions were predicted using ecological niche modeling, and …
Quantifying brain tumor tissue abundance in HR-MAS spectra using non-negative blind source separation techniques
2012
Given high-resolution magic angle spinning (HR-MAS) spectra from several glial tumor subjects, our goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, highly cellular tumor and border tumor tissue and providing the contribution (abundance) of each of these tumor tissue types to the profile of each spectrum. The problem is formulated as a non-negative source separation problem. Non-negative matrix factorization, convex analysis of non-negative sources and non-negative independent component analysis methods are …
Multivariate analysis in the identification of biological targets for designed molecular structures: The BIOTA protocol
2013
In this work the new protocol BIOlogical Target Assignation (BIOTA) for the prediction of the biological target from molecular structures is proposed. BIOTA is based on the Principal Components Analysis (PCA) application on a matrix of ligands versus molecular descriptors. The application of BIOTA could allow to hypothesize the mechanism of action of a candidate drug prior to its biological evaluation or to repurpose old drugs. The protocol can be fine-tuned by choosing opportune targets (biological or not) and molecular descriptors, and it can be useful in every fields in with it is possible to collect set of compounds with known properties. The robustness of the protocol depends from diff…
The impact of feature extraction on the performance of a classifier : kNN, Naïve Bayes and C4.5
2005
"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and the classification error in high dimensions. In this paper, different feature extraction techniques as means of (1) dimensionality reduction, and (2) constructive induction are analyzed with respect to the performance of a classifier. Three commonly used classifiers are taken for the analysis: kNN, Naïve Bayes and C4.5 decision tree. One of the main goals of this paper is to show the importance of the use of class information in feature extraction for classification and (in)appropriateness of random projection or conventional PCA to feature extraction for …
Sign and Rank Covariance Matrices: Statistical Properties and Application to Principal Components Analysis
2002
In this paper, the estimation of covariance matrices based on multivariate sign and rank vectors is discussed. Equivariance and robustness properties of the sign and rank covariance matrices are described. We show their use for the principal components analysis (PCA) problem. Limiting efficiencies of the estimation procedures for PCA are compared.
Applying univariate vs. multivariate statistics to investigate therapeutic efficacy in (pre)clinical trials: A Monte Carlo simulation study on the ex…
2020
BackgroundSmall sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects.ResultsWe systematically evaluated the performance of univariate ANOVA, Welch's ANOVA and linear mixed effects models ver…
Self-perception about emerging digital skills in higher education students
2020
El mercado laboral actual exige nuevas cualidades y conocimientos a los recién egresados de las universidades, incluidas las habilidades digitales, no existiendo suficientes investigaciones sobre la autopercepción del estudiantado al respecto. El objetivo de esta investigación fue medir la percepción que el estudiantado tiene sobre sus propias habilidades digitales del siglo XXI, en relación con el uso de las tecnologías de la comunicación (TIC) en la Educación Superior. Se generó y aplicó un cuestionario a 356 estudiantes con la técnica de muestreo aleatorio estratificado. Se realizó un análisis de componentes principales avalado por valores adecuados del coeficiente Kaiser-Meyer-Olkin y d…
Embryonic stem cell differentiation studied by FT-IR spectroscopy
2007
We propose, here, an FT-IR method to monitor the spontaneous differentiation of murine embryonic stem (ES) cells in their early development. Principal component analysis and subsequent linear discriminant analysis enabled us to segregate stem cell spectra into separate clusters corresponding to different differentiation times - and to identify the most significant spectral changes during differentiation. Between days 4 to 7 of differentiation, these spectral changes in the protein amide I band (1700-1600 cm(-1)) and in the nucleic acid absorption region (1050-850 cm(-1)) indicated that mRNA translation was taking place and that specific proteins were produced, reflecting the appearance of a…