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Maximum-Likelihood Estimation in a Special Integer Autoregressive Model
Econometrics, 2020 The paper is concerned with estimation and application of a special stationary integer autoregressive model where multiple binomial thinnings are not independent of one another.
Robert C. Jung, Andrew R. Tremayne
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Nonparametric Sieve Maximum Likelihood Estimation of Semi-Competing Risks Data
Mathematics, 2022 In biomedical studies involving time-to-event data, a subject may experience distinct types of events. We consider the problem of estimating the transition functions for a semi-competing risks model under illness-death model framework.
Xifen Huang, Jinfeng Xu
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stochprofML: stochastic profiling using maximum likelihood estimation in R
BMC Bioinformatics, 2021 Background Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue.
Lisa Amrhein, Christiane Fuchs
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Disjoint Tree Mergers for Large-Scale Maximum Likelihood Tree Estimation
Algorithms, 2021 The estimation of phylogenetic trees for individual genes or multi-locus datasets is a basic part of considerable biological research. In order to enable large trees to be computed, Disjoint Tree Mergers (DTMs) have been developed; these methods operate ...
Minhyuk Park +2 more
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Semi-Nonparametric Maximum Likelihood Estimation [PDF]
Econometrica, 1987 The density of Hermite forms: \[ h(u)=P^ 2_ k(u-\tau)\Phi^ 2(u| \tau,diag(\gamma)) \] where \(P_ k\) is a polynomial of degree K and \(\Phi\) is the density function of the multivariate normal distribution is shown to be capable of approximating any density arbitrarily closely subject to minimal qualifications relating to compactness, denseness ...
Gallant, A Ronald, Nychka, Douglas W
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Maximum‐likelihood estimation of the geometric niche preemption model
Ecosphere, 2021 The geometric series or niche preemption model is an elementary ecological model in biodiversity studies. The preemption parameter of this model is usually estimated by regression or iteratively by using May's equation.
Jan Graffelman
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High-Order Maximum Likelihood Methods for Direction of Arrival Estimation
IEEE Open Journal of Signal Processing, 2021 It is shown that using high-order statistics (higher than two) is beneficial in subspace-based Direction Of Arrival (DOA) estimation methods. Particularly, the high-order MUltiple SIgnal Classification (MUSIC) method, also known as $ 2q$-MUSIC method ...
Mohammadhossein Barat +2 more
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Maximum likelihood estimation of Wiener models [PDF]
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002 A Wiener model consists of a linear dynamic system followed by a static nonlinearity. The input and output are measured, but not the intermediate signal. We discuss the maximum likelihood estimate for Gaussian measurement and process noise, and the special cases when one of the noise sources is zero.
Hagenblad, Anna, Ljung, Lennart
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Estimation of servo-system parameters using maximum likelihood method
Vojnotehnički Glasnik, 1998 The problem of estimation of servo system parameters that cannot be measured is solved. Unknown parameters are estimated using system response measurements. A special discrete, recursive and iterative form of maximum likelihood method is presented.
Nenad Dodić
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Implicit Maximum Likelihood Estimation
CoRR, 2018 Implicit probabilistic models are models defined naturally in terms of a sampling procedure and often induces a likelihood function that cannot be expressed explicitly. We develop a simple method for estimating parameters in implicit models that does not require knowledge of the form of the likelihood function or any derived quantities, but can be ...
Ke Li 0011, Jitendra Malik
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