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The weibull distribution to describe aboveground biomass of Lolium multiflorum Lam., in relation to rate of nitrogen application Agrociencia
Gorgoso-Varela,José Javier; Oliveira-Prendes,José Alberto; Afif-Khouri,Elías; Palencia,Pedro.
Abstract Characterization of forage biomass in pasture land is complicated by the temporal and spatial variability that result from variation in vegetation patch sizes. These factors along with topography, water location and distribution of fertilizer result in non-uniform grass. The aim of the study was to evaluate the use of the three-parameter Weibull distribution to describe aerial dry matter (DM) production in the first harvest of a mixture of three Italian ryegrass (Lolium multiflorum Lam.) cultivars (the tetraploid ‘Jivet’ and ‘Barspirit’, and the diploid ’Barprisma’) in Asturias (N Spain). The trial was established in a randomized complete block design with three blocks of 100 m2 (20 m x 5 m) and a fertilizer treatment with three levels (0, 40 and...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Productivity; Nitrogen fertilization; Density function; Moments; Italian ryegrass.
Ano: 2018 URL: http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-31952018000100067
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The Lindley Weibull Distribution: properties and applications Anais da ABC (AABC)
CORDEIRO,GAUSS M.; AFIFY,AHMED Z.; YOUSOF,HAITHAM M.; CAKMAKYAPAN,SELEN; OZEL,GAMZE.
Abstract We introduce a new three-parameter lifetime model called the Lindley Weibull distribution, which accommodates unimodal and bathtub, and a broad variety of monotone failure rates. We provide a comprehensive account of some of its mathematical properties including ordinary and incomplete moments, quantile and generating functions and order statistics. The new density function can be expressed as a linear combination of exponentiated Weibull densities. The maximum likelihood method is used to estimate the model parameters. We present simulation results to assess the performance of the maximum likelihood estimation. We prove empirically the importance and flexibility of the new distribution in modeling two data sets.
Tipo: Info:eu-repo/semantics/article Palavras-chave: Lindley G-Family; Maximum likelihood; Moments; Order statistics.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000602579
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More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields AgEcon
Tack, Jesse B.; Harri, Ardian; Coble, Keith H..
The objective of this article is to propose the use of moment functions and maximum entropy techniques as a flexible way to estimate conditional crop yield distributions. We present a moment based model that extends previous approaches in several dimensions, and can be easily estimated using standard econometric estimators. Upon identification of the yield moments under a variety of climate and irrigation regimes, we utilize maximum entropy techniques to analyze the distributional impacts from switching regimes. We consider the case of Arkansas, Mississippi, and Texas upland cotton to demonstrate how climate and irrigation affect the shape of the yield distribution, and compare our findings to other moment based approaches. We empirically illustrate...
Tipo: Presentation Palavras-chave: Risk; Climate change; Moments; Entropy; Yield; Cotton; Crop Production/Industries; Production Economics; Research Methods/ Statistical Methods; Risk and Uncertainty.
Ano: 2012 URL: http://purl.umn.edu/123330
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