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Estimating betamixing coefficients
"... The literature on statistical learning for time series assumes the asymptotic independence or “mixing ” of the datagenerating process. These mixing assumptions are never tested, and there are no methods for estimating mixing rates from data. We give an estimator for the betamixing rate based on a ..."
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Cited by 2 (0 self)
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The literature on statistical learning for time series assumes the asymptotic independence or “mixing ” of the datagenerating process. These mixing assumptions are never tested, and there are no methods for estimating mixing rates from data. We give an estimator for the betamixing rate based on a
Constructing processes with prescribed mixing coefficients
, 2008
"... The rate at which dependencies between future and past observations decay in a random process may be quantified in terms of mixing coefficients. The latter in turn appear in strong laws of large numbers and concentration of measure results for dependent random variables. Questions regarding what rat ..."
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Cited by 1 (1 self)
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The rate at which dependencies between future and past observations decay in a random process may be quantified in terms of mixing coefficients. The latter in turn appear in strong laws of large numbers and concentration of measure results for dependent random variables. Questions regarding what
Variational Bayes estimation of mixing coefficients
, 2004
"... We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 as the sample size n grows large, the iterative algorithm for the variational Bayes approximation converges locally to the ..."
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We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 as the sample size n grows large, the iterative algorithm for the variational Bayes approximation converges locally
ON THE MIXING COEFFICIENTS OF PIECEWISE MONOTONIC MAPS.
, 2004
"... Abstract. We investigate the mixing coefficients of interval maps satisfying Rychlik’s conditions. A mixing LasotaYorke map is reverse φmixing. If its invariant density is uniformly bounded away from 0, it is φmixing iff all images of all orders are big in which case it is ψmixing. Among βtrans ..."
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Cited by 5 (2 self)
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Abstract. We investigate the mixing coefficients of interval maps satisfying Rychlik’s conditions. A mixing LasotaYorke map is reverse φmixing. If its invariant density is uniformly bounded away from 0, it is φmixing iff all images of all orders are big in which case it is ψmixing. Among β
MIXED MNL MODELS FOR DISCRETE RESPONSE
 JOURNAL OF APPLIED ECONOMETRICS J. APPL. ECON. 15: 447470 (2000)
, 2000
"... This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as ..."
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Cited by 487 (15 self)
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This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated
Mixing Coefficients Between Discrete and Real Random Variables: Computation and Properties
"... Abstract—In this paper, we study the problem of estimating the alpha, beta, and phimixing coefficients between two random variables, that can either assume values in a finite set or the set of real numbers. In either case, explicit closedform formulas for the betamixing coefficient are already ..."
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Abstract—In this paper, we study the problem of estimating the alpha, beta, and phimixing coefficients between two random variables, that can either assume values in a finite set or the set of real numbers. In either case, explicit closedform formulas for the betamixing coefficient are already
Local convergence of variational Bayes estimators for mixing coefficients
, 2003
"... In this paper we prove theoretically that for mixture models involving known component densities the variational Bayes estimator converges locally to the maximum likelihood estimator at the rate of O(1/n) in the large sample limit. ..."
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Cited by 5 (4 self)
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In this paper we prove theoretically that for mixture models involving known component densities the variational Bayes estimator converges locally to the maximum likelihood estimator at the rate of O(1/n) in the large sample limit.
2011a), “Estimating βmixing coefficients
 in Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics
"... ar ..."
Convergence of the EM Algorithm for Gaussian Mixtures with Unbalanced Mixing Coefficients
"... The speed of convergence of the Expectation Maximization (EM) algorithm for Gaussian mixture model fitting is known to be dependent on the amount of overlap among the mixture components. In this paper, we study the impact of mixing coefficients on the convergence of EM. We show that when the mixture ..."
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Cited by 2 (0 self)
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The speed of convergence of the Expectation Maximization (EM) algorithm for Gaussian mixture model fitting is known to be dependent on the amount of overlap among the mixture components. In this paper, we study the impact of mixing coefficients on the convergence of EM. We show that when
Climate Variability in the Equatorial Pacific Ocean Induced by Decadal Variability of Mixing Coefficient
, 2005
"... The circulation in the equatorial Pacific Ocean is studied in a series of numerical experiments based on an isopycnal coordinate model. The model is subject to monthly mean climatology of wind stress and surface thermohaline forcing. In response to decadal variability in the diapycnal mixing coeffic ..."
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in diapycnal mixing coefficient that varies between 0.03 104 and 0.27 104 m2 s1. Changes in diapycnal mixing coefficient of this amplitude are within the bulk range consistent with the external mechanical energy input in the global ocean, especially when considering the great changes of tropical cyclones
Results 1  10
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