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In this paper, we consider parameter estimation and quasi-likelihood ratio tests for multidimensional jump-diffusion processes defined by stochastic differential equations. In general, simultaneous estimation faces challenges such as an…

Statistics Theory · Mathematics 2025-02-25 Hiromasa Nishikawa , Tetsuya Kawai , Masayuki Uchida

We prove the local asymptotic mixed normality (LAMN) property for a family of probability measures defined by parametrized diffusion processes with nonsynchronous observations. We assume that observation times of processes are independent…

Statistics Theory · Mathematics 2015-09-21 Teppei Ogihara

In this paper, we consider a diffusion process with jumps whose drift and jump coefficient depend on an unknown parameter. We then give a self-contained proof of the local asymptotic mixed normality (LAMN) property when the process is…

Probability · Mathematics 2016-11-26 Ngoc Khue Tran , Eulalia Nualart

We study local asymptotic properties of likelihood ratios of certain Heston models. We distinguish three cases: subcritical, critical and supercritical models. For the drift parameters, local asymptotic normality is proved in the…

Statistics Theory · Mathematics 2019-10-17 János Marcell Benke , Gyula Pap

This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for transition density is proposed and…

Statistics Theory · Mathematics 2013-08-14 Chenxu Li

The Gaussian mixed-effects model driven by a stationary integrated Ornstein-Uhlenbeck process has been used for analyzing longitudinal data having an explicit and simple serial-correlation structure in each individual. However, the…

Statistics Theory · Mathematics 2023-11-07 Takumi Imamura , Hiroki Masuda , Hayato Tajima

We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonrandom and observation occurs in nonsynchronous manner. The problem of nonsynchronous observations is important when we consider the analysis…

Statistics Theory · Mathematics 2022-07-04 Teppei Ogihara

Asymptotic theory for approximate martingale estimating functions is generalised to diffusions with finite-activity jumps, when the sampling frequency and terminal sampling time go to infinity. Rate optimality and efficiency are of…

Methodology · Statistics 2018-09-05 Nina Munkholt Jakobsen , Michael Sørensen

The quasi-likelihood estimator and the Bayesian type estimator of the volatility parameter are in general asymptotically mixed normal. In case the limit is normal, the asymptotic expansion was derived in Yoshida (1997) as an application of…

Statistics Theory · Mathematics 2013-01-04 Nakahiro Yoshida

The transition density of a diffusion process does not admit an explicit expression in general, which prevents the full maximum likelihood estimation (MLE) based on discretely observed sample paths. A\"{\i}t-Sahalia [J. Finance 54 (1999)…

Statistics Theory · Mathematics 2012-03-12 Jinyuan Chang , Song Xi Chen

The paper concerns the asymptotic distribution of the mixture density estimator, proposed by Oppenheim et al 2006, in the aggregation/disaggregation problem of random parameter AR(1) process. We prove that, under mild conditions on the…

Statistics Theory · Mathematics 2008-02-07 Dmitrij Celov , Remigijus Leipus , Anne Philippe

We study asymptotic behaviors of Bayes type estimators and give sufficient conditions to obtain asymptotic limit distribution of estimation error. We assume polynomial type large deviation inequalities and prove asymptotic equivalence of…

Statistics Theory · Mathematics 2013-12-31 Teppei Ogihara

We will focus on estimating the integrated covariance of two diffusion processes observed in a nonsynchronous manner. The observation data is contaminated by some noise, which is possibly correlated with the returns of the diffusion…

Statistics Theory · Mathematics 2013-05-07 Yuta Koike

The paper presents a generalization of the local limit theorem on the convergence of inhomogeneous Markov chains to the diffusion limit for the case where the corresponding process coefficients satisfy weak regularity conditions and…

Probability · Mathematics 2025-06-02 I. Bitter , V. Konakov

For affine stochastic differential equation with uniformly distributed time delay the local asymptotic properties of the likelihood function are studied. Local asymptotic normality, local asymptotic mixed normality, periodic local…

Statistics Theory · Mathematics 2015-09-10 János Marcell Benke , Gyula Pap

In this paper, we consider a one-dimensional jump-type Cox-Ingersoll-Ross process driven by a Brownian motion and a subordinator, whose growth rate is an unknown parameter. Considering the process observed continuously or discretely at high…

Probability · Mathematics 2025-02-11 Mohamed Ben Alaya , Ahmed Kebaier , Gyula Pap , Ngoc Khue Tran

We consider the Halfin-Whitt diffusion process $X_d(t)$, which is used, for example, as an approximation to the $m$-server $M/M/m$ queue. We use recently obtained integral representations for the transient density $p(x,t)$ of this diffusion…

Probability · Mathematics 2015-05-06 Qiang Zhen , Charles Knessl

We obtain an asymptotic normality result that reveals the precise asymptotic behavior of the maximum likelihood estimators of parameters for a very general class of linear mixed models containing cross random effects. In achieving the…

Statistics Theory · Mathematics 2026-02-10 Jiming Jiang , Matt P. Wand , Swarnadip Ghosh

We consider a two-species simple exclusion process on a periodic lattice. We use the method of matched asymptotics to derive evolution equations for the two population densities in the dilute regime, namely a cross-diffusion system of…

Mathematical Physics · Physics 2023-01-25 James Mason , Robert L Jack , Maria Bruna

In this paper, we consider an ergodic Ornstein-Uhlenbeck process with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its jump intensity depend on unknown parameters.…

Probability · Mathematics 2016-03-14 Ngoc Khue Tran
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