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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dirros.openscience.si/IzpisGradiva.php?id=8217"><dc:title>DendroTools : R package for studying linear and nonlinear responses between tree-rings and daily environmental data</dc:title><dc:creator>Jevšenak,	Jernej	(Avtor)
	</dc:creator><dc:creator>Levanič,	Tom	(Avtor)
	</dc:creator><dc:subject>dendroclimatology</dc:subject><dc:subject>daily climate data</dc:subject><dc:subject>running window</dc:subject><dc:subject>nonlinear modelling</dc:subject><dc:subject>tree-ring proxies</dc:subject><dc:subject>climate reconstruction</dc:subject><dc:description>We introduce in this paper the dendroTools R package for studying the statistical relationships between tree-ring parameters and daily environmental data. The core function of the package is daily_response(), which works by sliding a moving window through daily environmental data and calculating statistical metrics with one or more tree ring proxies. Possible metrics are correlation coefficient, coefficient of determination and adjusted coeffi- cient of determination. In addition to linear regression, it is possible to use a nonlinear artificial neural network with the Bayesian regularization training algorithm (brnn). dendroTools provides the opportunity to use daily climate data and robust nonlinear functions for the analysis of climate-growth relationships. Models should thus be better adapted to the real (continuous) growth of trees and should gain in predictive capabilities. The dendroTools R package is freely available in the CRAN repository. The functionality of the package is demonstrated on two examples, one using a mean vessel area (MVA) chronology and one a traditional tree-ring width (TRW).</dc:description><dc:date>0</dc:date><dc:date>2018-04-16 15:10:25</dc:date><dc:type>Delo ni kategorizirano</dc:type><dc:identifier>8217</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
