joint maximum-likelihood estimation
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
... semi-blind joint maximum likelihood (ML) channel and data estimation schemes for MIMO ...the joint ML optimisation process for channel and data estimation is decomposed into two ...
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Joint maximum likelihood time delay estimation for LTE positioning in multipath channels
... a joint time-delay and channel estimator to assess the achievable positioning performance of the Long Term Evolution (LTE) system in multipath ...channel estimation model based on equi-spaced taps is ...
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Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
... for joint maximum likelihood (ML) channel estimation and data detection of single- input multiple-output (SIMO) ...The joint ML optimisation over channel and data is decomposed into an ...
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A mixed portmanteau test for ARMA GARCH model by the quasi maximum exponential likelihood estimation approach
... the joint limiting distribution of the residual autocorrelation functions and the absolute residual au- tocorrelation functions of ARMA-GARCH ...exponential likelihood estimation approach in Zhu and ...
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Computational approaches for maximum likelihood estimation for nonlinearmixed models.
... Nonlinear mixed eects models have become a routine tool in biomedical appli- cations to represent repeated measurement data on each of several individuals. A key area where nonlinear mixed eects models have seen ...
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Maximum likelihood estimation for directional conditionally autoregressive models
... dimensional joint distributions of the spatial process are multivariate Gaussian dis- ...the maximum likelihood (ML) and the Bayesian estimates are easily ...on maximum likelihood (ML) ...
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nihms-995808.pdf
... of joint models, under which the event time of interest follows a semiparametric transformation model with a random effect and the dropout time follows a different semiparametric transformation model but with the ...
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Blind joint maximum likelihood channel estimation and data detection for single input multiple output systems
... tion loop by combining a global optimization method, referred to as the repeated weighted boosting search technique RWBS [11] invoked for the optimal estimation of the SIMO channel and t[r] ...
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Maximum likelihood joint channel and data estimation using genetic algorithms
... too expensive to compute, except for the simplest case. In practice, suboptimal solutions are adopted for computational purposes. The algorithm based on a blind trellis search technique [10] is such an example. In the ...
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Joint Angle-Delay Estimation Based on Smoothed Maximum-Likelihood Algorithm
... In this paper, based on physical channel model an iterative ML method to estimate both TOA and DOA jointly has been proposed for uniform linear array (ULA) at receive side. Frequency smoothing is employed to the ...
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Maximum likelihood estimation for stochastic processes - a martingale approach
... Another contribution to ML estimation for dependent observations has been made in two papers by Weiss [1, 2], which are discussed in detail in 2.§5. These do not use the martingale property and are restricted to ...
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Asymptotics of Maximum Composite Likelihood Estimation for Geostatistical Data
... of maximum composite likelihood estimation as an alternative to maximum likelihood ...full likelihood computationally expensive to evaluate for large sample ...blockwise ...
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Approximate maximum likelihood estimation for population genetic inference
... approximate maximum likelihood methods have been proposed that estimate the likelihood surface in an ABC like fashion (Creel and Kristensen, 2013; Rubio and Johansen, 2013) or using MCMC (de Valpine, ...
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Maximum Likelihood Estimation of the Multivariate Normal Mixture Model
... This paper is organized as follows. In Section 2 we discuss how to take account of the two constraints: symmetry of the variance matrices and the fact that the weights sum to one. Our general result (Theorem 1) is formu- ...
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Model-Free IRL Using Maximum Likelihood Estimation
... The problem of learning an expert’s unknown reward func- tion using a limited number of demonstrations recorded from the expert’s behavior is investigated in the area of inverse re- inforcement learning (IRL). To gain ...
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Estimation and tests for power-transformed and threshold GARCH models
... [21] Mikosch, T. and Straumann, D. (2006).Stable limits of martingale transforms with appli- cation to the estimation of GARCH parameters. The Annals of Statistics, 34(1), 493-522. [22] Mittnik, S. and Rachev, S. ...
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Maximum-Likelihood Estimation of Coalescence Times in Genealogical Trees
... by maximum likelihood in population genetics appears new, a number of maximum-likelihood methods exist (F elsenstein 1981) for phylogenetic analysis of a sam- ple of DNA sequences, which could ...
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Maximum likelihood estimation for multiscale Ornstein Uhlenbeck processes
... We consider the case where the multiscale system is an OU process, where the av- eraging and homogenization principles still hold. We look at the MLE estimators of both the drift and diffusion coefficients of the ...
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A maximum likelihood approach to correlation dimension and entropy estimation
... To obtain the correlation dimension and entropy from an experimental time series we derive estimators for these quantities together with expressions for their variances [r] ...
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Maximum likelihood estimation of variance components
... the estimation of variance components has been a rich source of research problems over the last ...which estimation method is to be preferred in a particular ...
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