Search results for "Principal components"
showing 10 items of 17 documents
Assessment of production and qualitative characteristics of different populations of Salvia sclarea L. found in Sicily (Italy)
2021
Salvia sclarea L. is an important industrial crop, valued for its herbal-aromatic properties and high quality essential oils, that is used in food, pharmaceuticals and cosmetics. In this study, carried out from 2009 to 2010, the morphological and production characteristics and essential oil content and composition of three Sicilian populations were studied. In particular, the composition of essential oils extracted from primary and secondary inflorescences using steam distillation was assessed. Morphological, production and qualitative data from the three populations were subjected to analysis of variance and cluster analysis. Regarding the quality of the oils, only the most prevalent compo…
Mediterranean diet and prudent diet are both associated with low circulating esterified 3-hydroxy fatty acids, a proxy of LPS burden, among older adu…
2021
Background LPS-type endotoxins, naturally found in the gut microbiota, are recognized as triggers of inflammation and emerge as detrimental factors of healthy aging. Nutrition represents a promising strategy to reduce LPS burden, yet little is known about the relation of diet to circulating LPS concentrations. Objective The aim was to evaluate the associations between food groups, dietary patterns, and circulating 3-hydroxy fatty acids (3-OH FAs), a proxy of LPS burden. Methods In a cross-sectional study of 698 French older community-dwelling individuals, 3-OH FA concentrations were measured by LC-tandem MS. Dietary patterns were determined using food-frequency questionnaires. Adherence to …
Statistical characterisation of heavy metal contents inParacentrotus lividusfrom Mediterranean Sea
2014
This work focuses on the estimation of Hg, As, Cr, Ni, Cu, V, Cd and Pb by inductively coupled plasma mass spectrometry in 135 adult specimens of Paracentrotus lividus collected in different coastal areas of Sicily (Gela, Punta Secca, Ragusa (RG), Siracusa, Priolo, Catania, Messina, Milazzo, Brolo and Filicudi), in order to monitor the Mediterranean marine ecosystem by use of sea urchin as bioindicator. Moreover, the paper deals with the statistical classification of the tested samples according to the sampling area based on metal concentrations. The descriptive statistics findings were obtained and, a starting multivariate matrix was built. Data-sets were subjected to Kruskal-Wallis test t…
The impact of criminality on the riskiness of cooperative credit banks in Italy: a macro regional approach
2017
In Italy, Cooperative Credit Banks (CCBs), unlike large banks, despite the economic downturn, have continued to extend credit to customers, but at the cost of a higher incidence of bad credit. This increased credit risk of local banks has been caused by management policy choices, such as preferring to modify the conditions applicable to credit supply and to engage firms in long-term credit relationships rather than initiating credit recovery procedures. The originality of this empirical analysis lies in its demonstration of the effects of environmental factors related to the spread of crime and lower economic well-being, higher unemployment and poverty in families on the credit market in So…
Leading indicator properties of US high-yield credit spreads.
2010
Abstract In this paper we examine the out-of-sample forecast performance of high-yield credit spreads for real-time and revised data regarding employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest that the best results come from using only a few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. In particular, for employment and at short-run horizons, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks. Moreover, forecast results based on revised data …
A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data
2008
The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest the use of the principal component methodology of Stock and Watson [Stock, J.H., Watson, M.W., 2002. Macroeconomic forecasting using diffusion indices. Journal of Business and Economic Statistics, 20, 147–162] for the stochastic volatility factor model discussed by Harvey, Ruiz, and Shephard [Harvey, A.C., Ruiz, E., Shephard, N., 1994. Multivariate Stochastic Variance Models. Review of Economic Studies, 61, 247–264]. We provide theoretical and Monte Carlo results on this method and apply it to S&P data.
Assessment of the Geochemical Potential in a Complex Tectonic Environment of South-East Sicily: New Insights From Hydrochemical Data
2019
We analyzed a large dataset (143 water sampling sites, 22 variables) of chemical parameters in local groundwaters from the south-east sector of Sicily, namely the Hyblean plateau, in order to set an original evaluation of its geothermal potential using applied geochemistry. The area was affected by volcanism until about 1.4 Ma. Today, though no active volcanism occurs, it is site of surface gas manifestations of focused degassing to which a mantle source has been attributed. We identified and thence selected the most promising sites (water springs and wells) based both on their main geochemical characteristics and on their calculated equilibrium temperature (resulting in the range between 5…
On approximate system dynamic
1996
In this paper concepts and techniques from system theory are used to obtain state-space (Markovian ) models of dynamic economic processes instead of the usual VARMA models. In this respect the concept of state is reviewed as are Hankel norm approximations,and balanced realizations for stochastic models. We clarify some aspects of the balancing method for state space modelling of observed time series. This method may fail to satisfy the so-called positive real condition for stochastic processes. We us a state variance factorization algorithm which does not require us to solve the algebraic Riccati equation. We relate the Aoki-Havenner method to the Arun - Kung method.
Regional frequency analysis of extreme rainfall in Sicily (Italy)
2018
Extreme rainfall events have large impacts on society and are likely to increase in intensity under climate change. For design and management decisions, particularly regarding hydraulic works, accurate estimates of precipitation magnitudes are needed at different durations. In this article, an objective approach of the regional frequency analysis (RFA) has been applied to precipitation data for the island of Sicily, Italy. Annual maximum series for rainfall with durations of 1, 3, 6, 12, and 24 h from about 130 rain gauges were used. The RFA has been implemented using principal component analysis (PCA) followed by a clustering analysis, through the k-means algorithm, to identify statistical…
The Global Side of the Investment-Saving Puzzle
2009
In this paper, we reexamine the long-standing and puzzling correlation between national saving and investment in industrial countries. We apply an econometric methodology that allows us to separate idiosyncratic correlation at the country level from correlation at the global level. In a major break with the existing literature, we find no evidence of a long-run relationship in the idiosyncratic components of saving and investment. We also find that the global components in saving and investments commove, indicating that they react to shocks of a global nature.