Using a Quasi-Likelihood Approach
Functional GARCH models: the quasi likelihood approach and its applications
... based—an approach which is known to be relatively inefficient in this ...alternative quasi-likelihood approach, for which we derive consistency and asymptotic normality ...our approach ...
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Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes : a quasi-likelihood approach
... A quasi-likelihood approach Abstract: This paper extends the ordinary quasi-likelihood estimator for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck (OU) processes ...
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A QUASI-LIKELIHOOD APPROACH TO PARAMETER ESTIMATION FOR SIMULATABLE STATISTICAL MODELS
... of likelihood functions for such statistical models, which is often the case in stochastic geometric modelling, the idea is to follow a quasi-likelihood (QL) approach to construct an optimal ...
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Quasi-Likelihood Estimation of Benchmark Rates for Excess of Loss Reinsurance Programs
... of quasi-likelihood regression theory as rooted in the theory of generalised non-linear ...the quasi-likelihood approach one does not need to specify a distribution function for the ...
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Performance Analysis of the Gaussian Quasi-Maximum Likelihood Approach for Independent Vector Analysis
... addition, using the classical “first-order” perturbation analysis (under the “small-errors” assumption), we provided closed-form analytical expressions for the approximated predicted ...
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Semiparametric quasi-likelihood estimation with missing data
... local quasi-scores are ...same approach used by Foutz (1977), and complements the standard approach based on the global concavity of the quasi-likelihood ...of using parametric ...
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A mixed portmanteau test for ARMA GARCH model by the quasi maximum exponential likelihood estimation approach
... This paper investigates the joint limiting distribution of the residual autocorrelation functions and the absolute residual au- tocorrelation functions of ARMA-GARCH model. This leads a mixed portmanteau test for ...
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Parametrically guided local quasi-likelihood with censored data
... an approach known, in the literature, as para- metrically guided nonparametric ...this approach has been investigated in different frameworks such as density estimation, least squares regression and local ...
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Detecting multiple change-points in general causal time series using penalized quasi-likelihood
... ’on-line’ approach leading to sequential estimation and an ’off-line’ approach which arises when the series of observations is ...last approach, numerous results were obtained for independent random ...
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A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions
... obtained using proxy ...this approach treats volatility as a truly unobservable state and therefore uses only half the data, a strong argument can be made that the results are ...conditioning ...
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Analytical quasi maximum likelihood inference in multivariate volatility models
... maximum likelihood estimation using the Student-t ...this approach is that, if the as- sumption is wrong, then in general the ML estimates are not even ...hand, using a Gaussian ...
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On Marginal Quasi-Likelihood Inference in Generalized Linear Mixed Models
... theory likelihood based on a first- order variance approximation to estimate the variance ...this approach may not be satisfac- tory. Also, this approach may produce a negative estimate of the ...
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A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions
... accuracy using Gaussian ...new approach to dealing with unobserved state variables within the quasi-maximum likelihood framework is presented, which is based on conditioning the multivariate ...
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A Likelihood Approach to Bornhuetter–Ferguson Analysis
... maximum likelihood in a Poisson ...maximum likelihood estimators in a conditional Poisson model conditioning on row sums, while Kuang et ...maximum likelihood result means that it is possible to ...
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Estimation for stochastic volatility model: Quasi-likelihood and asymptotic quasi-likelihood approaches
... methodology enables a substitute technique for parameter esti- mation when the conditional variance process is unknown. This paper is structured as follows. The QL and AQL approaches are introduced in Section 2 . The ...
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A quasi maximum likelihood approach for large approximate dynamic factor models
... 3. The Maximum Likelihood estimates always dominate simple principal compo- nents and to a less extend the two-step procedure. As both n, T become large, the precision of the estimated common factors increases and ...
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Inference of Population History Using a Likelihood Approach
... an approach to revealing the likelihood of different population histories that utilizes an explicit model of sequence evolution for the DNA segment under ...a likelihood approach to conducting ...
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On the quasi-likelihood estimation for random coefficient autoregressions
... COEFFICIENT AUTOREGRESSIONS L. TRUQUET AND J. YAO Abstract. We examine the Gaussian Quasi-Maximum Likelihood Estimator (QMLE) for random coefficient autoregressions. Consistency and asymptotic normality are ...
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Bootstrapping Quasi Likelihood Ratio Tests under Misspecification
... We consider quasi likelihood ratio (QLR) tests for restrictions on parameters un- der potential model misspecification. For convex M-estimation, including quantile regression, we propose a general and ...
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Quasi-Maximum Likelihood estimation of Stochastic Volatility models.
... The relative efficiency of the QML estimator when compared with estimators based on the General- ized Method of Moments is shown to be quite high for parameter values often fou[r] ...
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