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Bias Corrected Maximum Likelihood Estimators in Nonlinear Overdispersed Models。
The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak...
This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology an...
This paper introduces a Monte Carlo method for maximum likelihood inference in the context of discretely observed diffusion processes. The method gives unbiased and a.s. continuous estimators of th...
This paper studies the quasi-maximum-likelihood estimator (QMLE) in a general conditionally heteroscedastic time series model of multiplicative form Xt = tZt, where the unobservable volatility t ...
This expository note describes how to apply the method of maximum likelihood to estimate the parameters of the “q-exponential distributions introduced by Tsallis and collaborators. It also describes...

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