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Quasi-likelihood analysis and its applications
The Ibragimov–Khasminskii theory established a scheme that gives asymptotic properties of the likelihood estimators through the convergence of the...
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Statistical inference for the nonparametric and semiparametric hidden Markov model via the composite likelihood approach
In this paper, we propose a new estimation method for a nonparametric hidden Markov model (HMM), in which both the emission model and the transition...
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The distribution of the maximum likelihood estimates of the change point and their relation to random walks
The problem of estimating the change point in a sequence of independent observations is considered. Hinkley (1970) demonstrated that the maximum...
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Empirical Likelihood for Partially Linear Errors-in-variables Models with Longitudinal Data
Empirical likelihood inference for partially linear errors-in-variables models with longitudinal data is investigated. Under regularity conditions,...
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Profile Likelihood-Based Confidence Interval for the Standard Deviation of the Two-Parameter Exponential Distribution
AbstractThis paper introduces the novel score function derived using the profile likelihood method to construct the new confidence interval for the...
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Approximation of the Likelihood Ratio Statistics in the Model of Competing Risks Under Random Censoring from the Right
In the competing risks model under random censoring from the right, an approximation of likelihood ratio statistics by a sequence of normally...
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Empirical Likelihood in Generalized Linear Models with Working Covariance Matrix
Empirical likelihood in generalized linear models with multivariate responses and working covariance matrix is discussed. Under the weakest...
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On comparison of steady-state infinitesimal perturbation analysis and likelihood ratio derivative estimates
In this paper, we compare the infinitesimal perturbation analysis (IPA) and likelihood ratio (LR) derivative estimators for the steady-state system...
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Estimation and likelihood
Hypothesis tests are useful for telling us that there’s something worth investigating in our data, but they don’t answer our most burning question:...
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Empirical Likelihood Inference for the Semiparametric Varying-Coefficient Spatial Autoregressive Model
In this paper empirical likelihood (EL)-based inference for a semiparametric varying-coefficient spatial autoregressive model is investigated. The...
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Likelihood theory for the graph Ornstein-Uhlenbeck process
We consider the problem of modelling restricted interactions between continuously-observed time series as given by a known static graph (or network)...
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Empirical Likelihood of Quantile Difference with Missing Response When High-dimensional Covariates Are Present
We, in this paper, investigate two-sample quantile difference by empirical likelihood method when the responses with high-dimensional covariates of...
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Maximum Quasi-Likelihood Estimation in Fractional Levy Stochastic Volatility Model
Usually asset price process has jumps and volatility process has long memory. We study maximum quasi-likelihood estimators for the parameters of a...
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Asymptotic Properties of Likelihood Ratio Statistics in Competing Risks Model Under Interval Random Censoring
AbstractIn this paper we consider local asymptotic normality of likelihood ratio statistics in competing risks model under random censoring by...
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Maximum Likelihood Estimation for a Markov-Modulated Jump-Diffusion Model
We propose a method for obtaining maximumMaximum likelihood estimates (MLEs) of a Markov-Modulated Jump-Diffusion Model (MMJDM); when the data is a...
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Quasi-likelihood analysis for marked point processes and application to marked Hawkes processes
We develop a quasi-likelihood analysis procedure for a general class of multivariate marked point processes. As a by-product of the general method,...
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Empirical likelihood inference for threshold autoregressive conditional heteroscedasticity model
This paper considers the parameter estimation problem of a first-order threshold autoregressive conditional heteroscedasticity model by using the...
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Performance assessment of the maximum likelihood ensemble filter and the ensemble Kalman filters for nonlinear problems
This study presents a thorough investigation of the performance comparison of three ensemble data assimilation (DA) methods, including the maximum...
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Gauss on least-squares and maximum-likelihood estimation
Gauss’ 1809 discussion of least squares, which can be viewed as the beginning of mathematical statistics, is reviewed. The general consensus seems to...
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Differences between Bayes Factors and Likelihood Ratios for Quantifying the Forensic Value of Evidence
Advances in the interpretation of forensic evidence have led to a number of different statistical methods all reaching for a quantification of the...