Search results for "Variable"
showing 10 items of 1674 documents
New cut-off criterion for uninformative variable elimination in multivariate calibration of near-infrared spectra for the determination of heroin in …
2008
A new cut-off criterion has been proposed for the selection of uninformative variables prior to chemometric partial least squares (PLS) modelling. After variable elimination, PLS regressions were made and assessed comparing the results with those obtained by PLS models based on the full spectral range. To assess the prediction capabilities, uninformative variable elimination (UVE)-PLS and PLS were applied to diffuse reflectance near-infrared spectra of heroin samples. The application of the proposed new cut-off criterion, based on the t-Students distribution, provided similar predictive capabilities of the PLS models than those obtained using the original criteria based on quantile value. H…
Studying students ́satisfaction at music schools in the Valencian Region
2017
[EN] Satisfaction is a key construct but complex to be measured. Within the cultural context and from the discipline of marketing, satisfaction consists of assessing some experiences without considering consumers ́ expectations. From this approach, this paper deals with an empirical research aiming at analyzing satisfaction among students of music conservatoires and schools. The research, qualitative and quantitative in nature, allowed to know users ́ assessment of different variables: studies, teaching staff, information technologies, premises and administration procedures. To do so, a self-administered survey was conducted using a structured questionnaire. Univariate and multivariate anal…
Embedding Quantum into Classical: Contextualization vs Conditionalization
2014
We compare two approaches to embedding joint distributions of random variables recorded under different conditions (such as spins of entangled particles for different settings) into the framework of classical, Kolmogorovian probability theory. In the contextualization approach each random variable is "automatically" labeled by all conditions under which it is recorded, and the random variables across a set of mutually exclusive conditions are probabilistically coupled (imposed a joint distribution upon). Analysis of all possible probabilistic couplings for a given set of random variables allows one to characterize various relations between their separate distributions (such as Bell-type ine…
Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans
2004
Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published. In general, the more toxic compounds exhibit more symmetric molecular structures.
On the use of adaptive spatial weight matrices from disease mapping multivariate analyses
2020
Conditional autoregressive distributions are commonly used to model spatial dependence between nearby geographic units in disease mapping studies. These distributions induce spatial dependence by means of a spatial weights matrix that quantifies the strength of dependence between any two neighboring spatial units. The most common procedure for defining that spatial weights matrix is using an adjacency criterion. In that case, all pairs of spatial units with adjacent borders are given the same weight (typically 1) and the remaining non-adjacent units are assigned a weight of 0. However, assuming all spatial neighbors in a model to be equally influential could be possibly a too rigid or inapp…
Second-order interaction in a Trivariate Generalized Gamma Distribution
2004
The concept of second- (and higher-) order interaction is widely used in categorical data analysis, where it proves useful for explaining the interdependence among three (or more) variables. Its use seems to be less common for continuous multivariate distributions, most likely owing to the predominant role of the Multivariate Normal distribution, for which any interaction involving more than two variables is necessarily zero. In this paper we explore the usefulness of a second-order interaction measure for studying the interdependence among three continuous random variables, by applying it to a trivariate Generalized Gamma distribution proposed by Bologna(2000).
Multivariate Exploratory Comparative Analysis of LaLiga Teams: Principal Component Analysis
2021
The use of principal component analysis (PCA) provides information about the main characteristics of teams, based on a set of indicators, instead of displaying individualized information for each of these indicators. In this work we have considered reducing an extensive data matrix to improve interpretation, using PCA. Subsequently, with new components and with multiple linear regression, we have carried out a comparative analysis between the best and bottom teams of LaLiga. The sample consisted of the matches corresponding to the 2015/16, 2016/17 and 2017/18 seasons. The results showed that the best teams were characterized and differentiated from bottom teams in the realization of a great…
Algorithms for the inference of causality in dynamic processes: Application to cardiovascular and cerebrovascular variability
2015
This study faces the problem of causal inference in multivariate dynamic processes, with specific regard to the detection of instantaneous and time-lagged directed interactions. We point out the limitations of the traditional Granger causality analysis, showing that it leads to false detection of causality when instantaneous and time-lagged effects coexist in the process structure. Then, we propose an improved algorithm for causal inference that combines the Granger framework with the approach proposed by Pearl for the study of causality among multiple random variables. This new approach is compared with the traditional one in theoretical and simulated examples of interacting processes, sho…
Sur les Terminaisons Nerveuses Sensitives du Clitoris chez la Truie (Sus scrofa domesticus)
1991
Summary On the Sensory Nerve-Endings in the Porcine Clitoris Neural receptors of the porcine clitoris were examined using light and electron microscopy. Perfusion with ink allowed study of the unique vascular arrangement associated with the genital corpuscles. Sensory nerve-endings were generally rounded and formed a morphologically and structurally characteristic unit. They were composed of a network of primarily non-myelinated nerve fibers and flat cells. Between these structures, isolated small blood vessels were embedded amongst collagen fibers and amorphous material. An external capsule of variable thickness always surrounded the structures. A complex arrangement of vessels in the cent…
Work satisfaction, psychological resiliency and sense of coherence as correlates of work engagement
2018
The objective of the article is to describe the links between work engagement—the response variable, work satisfaction—the explanatory variable, and sense of coherence, along with resiliency as resources—moderating variables. The theoretical foundations for our hypotheses are Hackman and Oldham’s Job Charcteristics Model, Block and Kremen’s conception of resiliency, Antonovsky’s salutogenesis, the JD-R of relation between work demands and resources and also the model of work engagement in the research of Schaufeli, Salanova, González-romá, and Bakker. Methods: 94 independent workers of Polish branches of international corporations were studied. Work satisfaction was measured using the SSP s…