Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados Anais da ABC (AABC) (1) Ciência e Agrotecnologia (1) Autor Anjos,Lúcia Helena Cunha dos (1) CORDEIRO,GAUSS M. (1) Costa,Elias Mendes (1) POGÁNY,TIBOR K. (1) Samuel-Rosa,Alessandro (1) TAHIR,MUHAMMAD H. (1) ZUBAIR,MUHAMMAD (1) Mais... Palavra-chave Shannon entropy (2) Collinearity (1) Generalized class (1) Maximum likelihood estimation (1) Multinomial logistic regression (1) Normal distribution (1) Power-Cauchy distribution (1) Predictor variables (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2019 (1) 2018 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última The Log-Odd Normal Generalized Family of Distributions with Application Anais da ABC (AABC) ZUBAIR,MUHAMMAD; POGÁNY,TIBOR K.; CORDEIRO,GAUSS M.; TAHIR,MUHAMMAD H.. Abstract: The normal distribution has a central place in distribution theory and statistics. We propose the log-odd normal generalized (LONG) family of distributions based on log-odds and obtain some of its mathematical properties including a useful linear representation for the new family. We investigate, as a special model, the log-odd normal power-Cauchy (LONPC) distribution. Some structural properties of LONPC distribution are obtained including quantile function, ordinary and incomplete moments, generating function and some asymptotics. We estimate the model parameters using the maximum likelihood method. The usefulness of the proposed family is proved empirically by means of a real air pollution data set. Tipo: Info:eu-repo/semantics/article Palavras-chave: Generalized class; Maximum likelihood estimation; Normal distribution; Power-Cauchy distribution; Shannon entropy. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000300203 Digital elevation model quality on digital soil mapping prediction accuracy Ciência e Agrotecnologia Costa,Elias Mendes; Samuel-Rosa,Alessandro; Anjos,Lúcia Helena Cunha dos. ABSTRACT Digital elevation models (DEM) used in digital soil mapping (DSM) are commonly selected based on measures and indicators (quality criteria) that are thought to reflect how well a given DEM represents the terrain surface. The hypothesis is that the more accurate a DEM, the more accurate will be the DSM predictions. The objective of this study was to assess different criteria to identify the DEM that delivers the most accurate DSM predictions. A set of 10 criteria were used to evaluate the quality of nine DEMs constructed with different data sources, processing routines and three resolutions (5, 20, and 30 m). Multinomial logistic regression models were calibrated using 157 soil observations and terrain attributes derived from each DEM. Soil class... Tipo: Info:eu-repo/semantics/article Palavras-chave: Multinomial logistic regression; Predictor variables; Collinearity; Shannon entropy. Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000600608 Registros recuperados: 2 Primeira ... 1 ... Última

Empresa Brasileira de Pesquisa Agropecuária - Embrapa Todos os direitos reservados, conforme Lei n° 9.610 Política de Privacidade Área restrita		Embrapa Parque Estação Biológica - PqEB s/n° Brasília, DF - Brasil - CEP 70770-901 Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco