Results 31 to 40 of about 388,098 (264)
SPATIAL CLUSTERING USING THE LIKELIHOOD FUNCTION
Conference on Applied Statistics in Agriculture, 2007 Clustering has been widely used as a tool to group multivariate observations that have similar characteristics. However, there have been few attempts at formulating a method to group similar multivariate observations while taking into account their spatial location.
Kerby, April +3 more
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The Analysis of Ranking Data Using Score Functions and Penalized Likelihood
Austrian Journal of Statistics, 2017 In this paper, we consider different score functions in order summarize certain characteristics for one and two sample ranking data sets. Our approach is flexible and is based on embedding the nonparametric problem in a parametric framework.
Mayer Alvo, Hang Xu
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New developments in the ROOT fitting classes [PDF]
EPJ Web of Conferences, 2019 The ROOT Mathematical and Statistical libraries have been recently improved both to increase their performance and to facilitate the modelling of parametric functions that can be used for performing maximum likelihood fits to data sets to estimate ...
Valls Xavier +3 more
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The Annals of Statistics, 1983 The connection between quasi-likelihood functions, exponential family models and nonlinear weighted least squares is examined. Consistency and asymptotic normality of the parameter estimates are discussed under second moment assumptions. The parameter estimates are shown to satisfy a property of asymptotic optimality similar in spirit to, but more ...
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Copula cosmology: Constructing a likelihood function [PDF]
Physical Review D, 2011 To estimate cosmological parameters from a given dataset, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is
Sato, Masanori +2 more
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Evaluation of likelihood functions
Information and Control, 1968 An expression is obtained for the likelihood function for the detection of a stochastic signal (diffusion process) in white noise. A stochastic differential equation is then obtained for the evolution of the likelihood function and the coefficients of this differential equation are related to a corresponding nonlinear filtering problem. Some extensions
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Spatially multi-scale dynamic factor modeling via sparse estimation
International Journal of Mathematics for Industry, 2019 In many spatio-temporal data, their spatial variations have inherent global and local structures. The spatially continuous dynamic factor model (SCDFM) decomposes the spatio-temporal data into a small number of spatial and temporal variations, where the ...
Takamitsu Araki, Shotaro Akaho
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Occupational stress and body composition of hospital workers: a follow-up study
Frontiers in Public HealthThis study sought to analyze the influence of occupational stress on the body composition of hospital workers after one year of follow-up. This prospective cohort study included 218 workers from one of the leading private hospitals in the municipality of
Carlos Rodrigo Nascimento de Lira +4 more
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Indoor Ultra-Wide Band Network Adjustment using Maximum Likelihood Estimation [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 This study is the part of our ongoing research on using ultra-wide band (UWB) technology for navigation at the Ohio State University. Our tests have indicated that the UWB two-way time-of-flight ranges under indoor circumstances follow a Gaussian mixture
Z. Koppanyi, C. K. Toth
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Mathematics, 2022 This paper explores statistical inferences when the lifetime of product follows the inverse Nakagami distribution using progressive Type-II censored data.
Liang Wang +2 more
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