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Likelihood-Quotienten-Tests
Gegenstand dieses Kapitels ist das Testen von Hypothesen innerhalb parametrischer Modelle. Wir beschränken uns dabei auf verallgemeinerte...
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Maximum-Likelihood-Schätzung
In diesem Kapitel lernen wir eine grundlegende Methode kennen, um in parametrischen Modellen Schätzer für unbekannte Parameter zu konstruieren,...
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Maximum Likelihood
In Chapter 2, we discussed the problem of minimizing the Euclidean distance from a data point u to a model X in...
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Maximum Full Likelihood Approach to Randomly Truncated Data
Truncated data are commonly observed in economics, epidemiology, and other fields. The analysis of truncated data is challenging because the observed...
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Threshold Models for Lévy Processes and Approximate Maximum Likelihood Estimation
Using the Lévy process (solution of the Ito–Skorokhod stochastic differential equation), we propose the structure of the model of a threshold process...
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Empirical Likelihood for Generalized Linear Models with Longitudinal Data
Generalized linear models are usually adopted to model the discrete or nonnegative responses. In this paper, empirical likelihood inference for fixed...
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Data-driven slicing for dimension reduction in regressions: A likelihood-ratio approach
To efficiently estimate the central subspace in sufficient dimension reduction, response discretization via slicing its range is one of the most used...
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Empirical Likelihood for a First-Order Generalized Random Coefficient Integer-Valued Autoregressive Process
In this paper, the authors consider the empirical likelihood method for a first-order generalized random coefficient integer-valued autoregressive...
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Likelihood-Quotienten-Tests
Gegenstand dieses Kapitels ist das Testen von Hypothesen innerhalb parametrischer Modelle. Wir beschränken uns dabei auf verallgemeinerte...
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Empirical likelihood for spatial cross-sectional data models with matrix exponential spatial specification
In this paper, we study spatial cross-sectional data models in the form of matrix exponential spatial specification (MESS), where MESS appears in...
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Characterizations of the Maximum Likelihood Estimator of the Cauchy Distribution
AbstractThis paper gives a new approach for the maximum likelihood estimation of the joint of the location and scale of the Cauchy distribution. We...
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Evolving Improved Sampling Protocols for Dose–Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric
Practical limitations of quality and quantity of data can limit the precision of parameter identification in mathematical models. Model-based...
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Optimal distribution-free concentration for the log-likelihood function of Bernoulli variables
This paper aims to establish distribution-free concentration inequalities for the log-likelihood function of Bernoulli variables, which means that...
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LIKELIHOOD-BASED ANALYSIS IN MIXTURE GLOBAL VARs
In this paper we propose a mixture global vector autoregressive model with exogenous variables to study country/region interdependencies that exist...
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A pseudo-likelihood estimator of the Ornstein–Uhlenbeck parameters from suprema observations
In this paper, we propose an estimator for the Ornstein–Uhlenbeck parameters based on observations of its supremum. We derive an analytic expression...
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Maximum-Likelihood-Schätzung
In diesem Kapitel lernen wir eine grundlegende Methode kennen, um in parametrischen Modellen Schätzer für unbekannte Parameter zu konstruieren,...
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The likelihood and Bayesian analyses for asymmetric Laplace nonlinear regression model
Regression model is a popular and well-acknowledged technique for finding a relationship between random phenomena. In this context, the normality...
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Improved Maximum Likelihood Estimation of ARMA Models
AbstractIn this paper we propose a new optimization model for maximum likelihood estimation of causal and invertible ARMA models. Through a set of...
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On partial likelihood and the construction of factorisable transformations
Models whose associated likelihood functions fruitfully factorise are an important minority allowing elimination of nuisance parameters via partial...
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A Continuation Technique for Maximum Likelihood Estimators in Biological Models
Estimating model parameters is a crucial step in mathematical modelling and typically involves minimizing the disagreement between model predictions...
