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This paper obtains asymptotic results for parametric inference using prediction-based estimating functions when the data are high frequency observations of a diffusion process with an infinite time horizon. Specifically, the data are…

Statistics Theory · Mathematics 2020-07-27 Emil S. Jørgensen , Michael Sørensen

We consider a linear mixed-effects model with a clustered structure, where the parameters are estimated using maximum likelihood (ML) based on possibly unbalanced data. Inference with this model is typically done based on asymptotic theory,…

Statistics Theory · Mathematics 2021-03-30 Chih-Hao Chang , Hsin-Cheng Huang , Ching-Kang Ing

Parametric estimation for diffusion processes is considered for high frequency observations over a fixed time interval. The processes solve stochastic differential equations with an unknown parameter in the diffusion coefficient. We find…

Methodology · Statistics 2017-04-03 Nina Munkholt Jakobsen , Michael Sørensen

Let $\alpha_n(\cdot)=P\bigl(X_{n+1}\in\cdot\mid X_1,\ldots,X_n\bigr)$ be the predictive distributions of a sequence $(X_1,X_2,\ldots)$ of $p$-dimensional random vectors. Suppose $$\alpha_n= \mathcal{N} _p (M_n,Q_n)$$ where…

Statistics Theory · Mathematics 2024-09-17 Samuele Garelli , Fabrizio Leisen , Luca Pratelli , Pietro Rigo

Nonparametric density and regression estimators commonly depend on a bandwidth. The asymptotic properties of these estimators have been widely studied when bandwidths are nonstochastic. In practice, however, in order to improve finite…

Statistics Theory · Mathematics 2014-09-02 Carlos Martins-Filho , Paulo Saraiva

We consider a diffusion $(\xi_t)_{t\ge 0}$ whose drift contains some deterministic periodic signal. Its shape being fixed and known, up to scaling in time, the periodicity of the signal is the unknown parameter $\vartheta$ of interest. We…

Statistics Theory · Mathematics 2010-10-26 Reinhard Hoepfner , Yury Kutoyants

The objective of this article is to study the asymptotic behavior of a new particle filtering approach in the context of hidden Markov models (HMMs). In particular, we develop an algorithm where the latent-state sequence is segmented into…

Statistics Theory · Mathematics 2014-09-16 Hock Peng Chan , Chiang Wee Heng , Ajay Jasra

Datasets from the fields of bioinformatics, chemometrics, and face recognition are typically characterized by small samples of high-dimensional data. Among the many variants of linear discriminant analysis that have been proposed in order…

Machine Learning · Statistics 2020-04-20 Lama B. Niyazi , Abla Kammoun , Hayssam Dahrouj , Mohamed-Slim Alouini , Tareq Y. Al-Naffouri

We deal with a planar random flight $\{(X(t),Y(t)),0<t\leq T\}$ observed at $n+1$ equidistant times $t_i=i\Delta_n,i=0,1,...,n$. The aim of this paper is to estimate the unknown value of the parameter $\lambda$, the underlying rate of the…

Statistics Theory · Mathematics 2007-06-13 Alessandro De Gregorio

The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated time series. We show the asymptotic…

Statistics Theory · Mathematics 2011-02-11 Łukasz Lenart

Efficient estimation of a non-Gaussian stable Levy process with drift and symmetric jumps observed at high frequency is considered. For this statistical experiment, the local asymptotic normality of the likelihood is proved with a…

Statistics Theory · Mathematics 2025-08-19 Alexandre Brouste , Hiroki Masuda

The first purpose of this article is to obtain a.s. asymptotic properties of the maximum likelihood estimator in the autoregressive process driven by a stationary Gaussian noise. The second purpose is to show the local asymptotic normality…

Statistics Theory · Mathematics 2018-10-23 Marius Soltane

We prove the asymptotic mixed normality of the least absolute deviation (LAD) estimator for a locally $\alpha$-stable stochastic differential equation (SDE) observed at high frequency, where $\alpha\in(0,2)$. We investigate both ergodic and…

Statistics Theory · Mathematics 2026-03-31 Oleksii M. Kulyk , Hiroki Masuda

In this article, we consider flexible seasonal time series models which consist of a common trend function over periods and additive individual trend (seasonal effect) functions. The consistency and asymptotic normality of the local linear…

Mathematical Physics · Physics 2014-03-11 Kyong-Hui Kim , Hak-Myong Pak

We introduce a class of semiparametric time series models by assuming a quasi-likelihood approach driven by a latent factor process. More specifically, given the latent process, we only specify the conditional mean and variance of the time…

Methodology · Statistics 2021-04-02 Gisele O. Maia , Wagner Barreto-Souza , Fernando S. Bastos , Hernando Ombao

We consider a stable Cox--Ingersoll--Ross process driven by a standard Wiener process and a spectrally positive strictly stable L\'evy process, and we study asymptotic properties of the maximum likelihood estimator (MLE) for its growth rate…

Statistics Theory · Mathematics 2019-08-23 Matyas Barczy , Mohamed Ben Alaya , Ahmed Kebaier , Gyula Pap

We have shown in previous work that statistical inference for cooperative sequential adsorption model can be based on maximum likelihood estimation. In this paper we continue this research and establish asymptotic normality of the maximum…

Statistics Theory · Mathematics 2010-05-14 Mathew D. Penrose , Vadim Shcherbakov

Asymptotic properties of the local Whittle estimator in the nonstationary case (d>{1/2}) are explored. For {1/2}<d\leq 1, the estimator is shown to be consistent, and its limit distribution and the rate of convergence depend on the value of…

Statistics Theory · Mathematics 2007-06-13 Peter C. B. Phillips , Katsumi Shimotsu

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

When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an influence function. Song (2014) recently developed a local asymptotic…

Statistics Theory · Mathematics 2014-03-12 Kyungchul Song
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