Maximum Likelihood Estimation
Mostrando 1-12 de 136 artigos, teses e dissertações.
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1. Sparse Estimation of the Precision Matrix and Plug-In Principle in Linear Discriminant Analysis for Hyperspectral Image Classification
ABSTRACT In this paper, a new method for supervised classification of hyperspectral images is proposed for the case in which the size of the training sample is small. It consists of replacing in the Mahalanobis distance the maximum likelihood estimator of the precision matrix by a sparse estimator. The method is compared with two other existing versions of L
Trends in Computational and Applied Mathematics. Publicado em: 2022
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2. Mathematical Analysis and Improvement of the Maximum Spatial Eigenfilter for Direction of Arrival Estimation
Abstract Maximum spatial eigenfiltering improves the accuracy of maximum likelihood direction-of-arrival estimators for closely-spaced signal sources but may interchangeably attenuate widely-spaced signal sources, producing a severe performance degradation. Although this behavior has been observed experimentally, it still lacks a mathematical explanation. In
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2021-03
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3. MULTILEVEL NONLINEAR MIXED-EFFECTS MODEL AND MACHINE LEARNING FOR PREDICTING THE VOLUME OF Eucalyptus SPP. TREES
ABSTRACT Volumetric equations is one of the main tools for quantifying forest stand production, and is the basis for sustainable management of forest plantations. This study aimed to assess the quality of the volumetric estimation of Eucalyptus spp. trees using a mixed-effects model, artificial neural network (ANN) and support-vector machine (SVM). The datab
CERNE. Publicado em: 2020-03
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4. Resistance of the wild tomato Solanum habrochaites to Phytophthora infestans is governed by a major gene and polygenes
Abstract: This work aimed to study the inheritance of resistance to Phytophthora infestans in tomato plants, using the maximum likelihood estimation function. The susceptible cultivar Santa Clara (Solanum lycopersicum) was used as the female genitor and the P. infestans resistant S. habrochaites f. glabratum accession (BGH 6902) as the male genitor. F1 plant
An. Acad. Bras. Ciênc.. Publicado em: 11/11/2019
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5. Pure line selection in a heterogeneous soybean cultivar
Abstract Although cultivars of autogamous plants are homogeneous genotypes, they may show natural variability due to mechanical mixing, natural hybridization, and mutation. The aim of the present study was to estimate genetic and phenotypic parameters and to identify and select superior genotypes that associate good performance in traits of interest from a h
Crop Breed. Appl. Biotechnol.. Publicado em: 31/10/2019
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6. Estimation of genetic parameters for weight traits and Kleiber Index in a Brahman cattle population
ABSTRACT: Interest in improving feed efficiency of cattle has been increasing. The residual feed intake (RFI), the most commonly used measurement of feed efficiency, is expensive and can only be used in a small number of animals. The Kleiber Index has also been proposed to measure RFI. In this study, we estimated genetic parameters for the Kleiber Index aver
Sci. agric. (Piracicaba, Braz.). Publicado em: 30/05/2019
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7. The Nadarajah-Haghighi Lindley distribution
Abstract: We define a new lifetime model based on compounding the Lindley and Nadarajah-Haghighi distributions. The proposed distribution is very competitive to other lifetime models. Some of its mathematical properties are investigated including generating function, mean residual life, moments, Bonferroni and Lorenz curves and mean deviations. We discuss th
An. Acad. Bras. Ciênc.. Publicado em: 08/04/2019
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8. A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model w
An. Acad. Bras. Ciênc.. Publicado em: 08/04/2019
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9. Slash Spatial Linear Modeling: Soybean Yield Variability as a Function of Soil Chemical Properties
ABSTRACT: In geostatistical modeling of soil chemical properties, one or more influential observations in a dataset may impair the construction of interpolation maps and their accuracy. An alternative to avoid the problem would be to use most robust models, based on distributions that have heavier tails. Therefore, this study proposes a spatial linear model
Rev. Bras. Ciênc. Solo. Publicado em: 15/02/2018
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10. A new model for describing remission times: the generalized beta-generated Lindley distribution
New generators are required to define wider distributions for modeling real data in survival analysis. To that end we introduce the four-parameter generalized beta-generated Lindley distribution. It has explicit expressions for the ordinary and incomplete moments, mean deviations, generating and quantile functions. We propose a maximum likelihood procedure t
An. Acad. Bras. Ciênc.. Publicado em: 2017-09
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11. SPATIAL VARIABILITY OF SOYBEAN YIELD THROUGH A REPARAMETERIZED T-STUDENT MODEL
ABSTRACT: The t-Student distribution has been used to the spatial dependence modelling of soybean yield as an alternative to the normal distribution, being used for data with heavier tails or discrepant values. However, a usual Student t-distribution does not allow direct comparisons of geostatistical methods with a normal distribution. The aim of this study
Eng. Agríc.. Publicado em: 2017-08
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12. The Extended Log-Logistic Distribution: Properties and Application
Abstract We propose a new four-parameter lifetime model, called the extended log-logistic distribution, to generalize the two-parameter log-logistic model. The new model is quite flexible to analyze positive data. We provide some mathematical properties including explicit expressions for the ordinary and incomplete moments, probability weighted moments, mean
An. Acad. Bras. Ciênc.. Publicado em: 2017-03