Search results for "regression"
showing 10 items of 2619 documents
Biological mineral content in Iberian skeletal cremains for control of diagenetic factors employing multivariate statistics
2013
Abstract The aim of this study was to define a strategy for a correct selection of bone samples by employing inductively coupled plasma optical emission spectroscopy (ICP-OES) for reconstructing the biological mineral content in bones through the determination of major elements, trace elements and Rare Earth Elements (REE, lanthanides) in skeletal cremains of ancient Iberians (III–II B.C), discovered in the Necropolis of Corral de Saus (Moixent, Valencia) between 1972 and 1979. The biological mineral content was determined taking into account diagenetic factors. A control method for a better reading of results was applied. To explore large geochemical datasets and to reduce the number of va…
Contribution to modeling the viscosity Arrhenius-type equation for some solvents by statistical correlations analysis
2014
Abstract Estimation and knowledge of transport properties of fluids are essential for heat and mass flow. Viscosity is one of the important properties which are affected by temperature and pressure. In the present work, based on the use of econometric and statistical techniques for parametric and non-parametric regression analysis and statistical correlation tests, we propose an equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the Arrhenius energy ( E a ) or the pre-exponential factor ( A s ). In addition, we introduce a third interesting parameter called Arrhenius temperature ( T A ), to enrich the discussion. Empirical validation …
Influence of the metabolic syndrome on aortic stiffness in never treated hypertensive patients
2004
Summary Background and aim Metabolic syndrome (MS) carries an increased risk for cardiovascular events and there is a growing awareness that large artery stiffening is a powerful predictor of cardiovascular morbidity and mortality. Little is known about the relationship of MS with aortic stiffness. The aim of our study was to analyze, in patients with essential hypertension, the influence of MS, defined according to the criteria proposed by the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (NCEP-ATP III), on carotid–femoral pulse wave velocity (PWV), a measure of aortic stiffness. Methods N…
Determinants and Congruence of Species Richness Patterns across Multiple Taxonomic Groups on a Regional Scale
2012
Applying multiple generalized regression models, we studied spatial patterns in species richness for different taxonomic groups (amphibians, reptiles, grasshoppers, plants, mosses) within the German federal state Rhineland-Palatinate (RP). We aimed (1) to detect their centres of richness, (2) to rate the influence of climatic and land-use parameters on spatial patterns, and (3) to test whether patterns are congruent between taxonomic groups in RP. Centres of species richness differed between taxonomic groups and overall richness was the highest in the valleys of large rivers and in different areas of southern RP. Climatic parameters strongly correlated with richness in all taxa whereas land…
An ANN model to correlate roughness and structural performance in asphalt pavements
2017
Abstract In this paper, using a large database from the Long Term Pavement Performance program, the authors developed an Artificial Neural Network (ANN) to estimate the structural performance of asphalt pavements from roughness data. Considering advantages of modern high-performance survey devices in the acquisition of road pavement functional parameters, it would be of practical significance if the structural state of a pavement could be estimated from its functional conditions. To differentiate various road section conditions, several significant input parameters, related to traffic, weather, and structural aspects, have been included in the analysis. The results are very interesting and …
Multiple criteria assessment of methods for forecasting building thermal energy demand
2020
Abstract Nowadays worldwide directives have focused the attention on improving energy efficiency in the building sector. The research of models able to predict the energy consumption from the first design and energy planning phase is conducted to improve building sustainability. Use of traditional forecasting tools for building thermal energy demand tends to encounter difficulties relevant to the amount of data required, implementation of the models, computational costs and inability to generalize the output. Therefore, many studies focused on the research and development of alternative resolution methods, but the choice of the most convenient is not clear and simple. Single comparison of s…
Optimal Pruned K-Nearest Neighbors: OP-KNN Application to Financial Modeling
2008
The paper proposes a methodology called OP-KNN, which builds a one hidden-layer feed forward neural network, using nearest neighbors neurons with extremely small computational time. The main strategy is to select the most relevant variables beforehand, then to build the model using KNN kernels. Multi-response sparse regression (MRSR) is used as the second step in order to rank each k-th nearest neighbor and finally as a third step leave-one-out estimation is used to select the number of neighbors and to estimate the generalization performances. This new methodology is tested on a toy example and is applied to financial modeling.
Semi-Supervised Support Vector Biophysical Parameter Estimation
2008
Two kernel-based methods for semi-supervised regression are presented. The methods rely on building a graph or hypergraph Laplacian with both the labeled and unlabeled data, which is further used to deform the training kernel matrix. The deformed kernel is then used for support vector regression (SVR). The semi-supervised SVR methods are sucessfully tested in LAI estimation and ocean chlorophyll concentration prediction from remotely sensed images.
Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators
2021
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…
Improved reliability estimates for the serial color-word test
1978
Starting from Lennart Sjoberg's serial scoring of the Color-Word Test and his critical review of the test, the possibilities of attaining better reliability estimates are briefly surveyed. As a simple step, the orthogonalization of the regression model is suggested. Ways of maximizing the reliability estimate are demonstrated. On the basis of 261 subjects from five differing subsamples, clinical and control groups, the reliability estimates of the oblique system of the orthogonalized system and of the maximum reliability solutions are compared empirically. The significance of the results for test theoretic evaluation of the Color-Word Test is discussed.