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We consider a stochastic differential equation with additive fractional noise with Hurst parameter $H>1/2$, and a non-linear drift depending on an unknown parameter. We show the Local Asymptotic Normality property (LAN) of this parametric…

Probability · Mathematics 2017-11-07 Yanghui Liu , Eulalia Nualart , Samy Tindel

Least squares estimator of the stability parameter $\varrho := |\alpha| + |\beta|$ for a spatial unilateral autoregressive process $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\varepsilon_{k,\ell}$ is investigated. Asymptotic…

Statistics Theory · Mathematics 2016-06-21 Sándor Baran , Gyula Pap , Kinga Sikolya

We consider least squares estimators of the finite regression parameter $\alpha$ in the single index regression model $Y=\psi(\alpha^T X)+\epsilon$, where $X$ is a $d$-dimensional random vector, $\E(Y|X)=\psi(\alpha^T X)$, and where $\psi$…

Statistics Theory · Mathematics 2023-01-31 Fadoua Balabdaoui , Piet Groeneboom

Given a single trajectory of a dynamical system, we analyze the performance of the nonparametric least squares estimator (LSE). More precisely, we give nonasymptotic expected $l^2$-distance bounds between the LSE and the true regression…

Machine Learning · Computer Science 2022-02-22 Ingvar Ziemann , Henrik Sandberg , Nikolai Matni

A biomechanical model often requires parameter estimation and selection in a known but complicated nonlinear function. Motivated by observing that data from a head-neck position tracking system, one of biomechanical models, show…

Methodology · Statistics 2024-02-13 Hojun You , Kyubaek Yoon , Wei-Ying Wu , Jongeun Choi , Chae Young Lim

The double Heston model is one of the most popular option pricing models in financial theory. It is applied to several issues such that risk management and volatility surface calibration. This paper deals with the problem of global…

Statistics Theory · Mathematics 2025-01-29 Mohamed Ben Alaya , Houssem Dahbi , Hamdi Fathallah

Using and extending fractional order statistic theory, we characterize the $O(n^{-1})$ coverage probability error of the previously proposed confidence intervals for population quantiles using $L$-statistics as endpoints in Hutson (1999).…

Statistics Theory · Mathematics 2018-02-28 Matt Goldman , David M. Kaplan

We consider a model where the failure hazard function, conditional on a covariate $Z$ is given by $R(t,\theta^0|Z)=\eta\_{\gamma^0}(t)f\_{\beta^0}(Z)$, with $\theta^0=(\beta^0,\gamma^0)^\top\in \mathbb{R}^{m+p}$. The baseline hazard…

Statistics Theory · Mathematics 2007-06-13 Marie-Laure Martin-Magniette , Marie-Luce Taupin

This paper investigates the properties of Quasi Maximum Likelihood estimation of an approximate factor model for an $n$-dimensional vector of stationary time series. We prove that the factor loadings estimated by Quasi Maximum Likelihood…

Econometrics · Economics 2024-06-28 Matteo Barigozzi

We noisily observe solutions of an ordinary differential equation $\dot u = f(u)$ at given times, where $u$ lives in a $d$-dimensional state space. The model function $f$ is unknown and belongs to a H\"older-type smoothness class with…

Statistics Theory · Mathematics 2024-07-23 Christof Schötz , Maximilian Siebel

In this article, we study the limit distribution of the least square estimator, properly normalized, from a regression model in which observations are assumed to be finite ($\alpha N$) and sampled under two different random times. Based on…

Statistics Theory · Mathematics 2020-12-17 Tania Roa , Soledad Torres , Ciprian tudor

We study asymptotics of the partition function $Z_N$ of a Laguerre-type random matrix model when the matrix order $N$ tends to infinity. By using the Deift-Zhou steepest descent method for Riemann-Hilbert problems, we obtain an asymptotic…

Classical Analysis and ODEs · Mathematics 2013-04-18 Yi Zhao , Lihua Cao , Dan Dai

We introduce stochastic sequences $\zeta(k)$ with periodically stationary generalized multiple increments of fractional order which combines cyclostationary, multi-seasonal, integrated and fractionally integrated patterns. We solve the…

Statistics Theory · Mathematics 2020-07-24 Maksym Luz , Mikhail Moklyachuk

Additive regression models are actively researched in the statistical field because of their usefulness in the analysis of responses determined by non-linear relationships with multivariate predictors. In this kind of statistical models,…

Methodology · Statistics 2018-04-10 German A. Schnaidt Grez , Brani Vidakovic

We consider a one-dimensional diffusion process $(X_t)$ which is observed at $n+1$ discrete times with regular sampling interval $\Delta$. Assuming that $(X_t)$ is strictly stationary, we propose nonparametric estimators of the drift and…

Statistics Theory · Mathematics 2009-09-29 Fabienne Comte , Valentine Genon-Catalot , Yves Rozenholc

In a wide range of applications, the stochastic properties of the observed time series change over time. The changes often occur gradually rather than abruptly: the prop- erties are (approximately) constant for some time and then slowly…

Methodology · Statistics 2014-03-18 Michael Vogt , Holger Dette

We address the inference problem concerning regression coefficients in a classical linear regression model using least squares estimates. The analysis is conducted under circumstances where network dependency exists across units in the…

Methodology · Statistics 2024-04-03 Jing Lei , Kehui Chen , Haeun Moon

In this paper, we consider the problem of finding the Least Squares estimators of two isotonic regression curves $g^\circ_1$ and $g^\circ_2$ under the additional constraint that they are ordered; e.g., $g^\circ_1 \le g^\circ_2$. Given two…

Methodology · Statistics 2023-04-17 Fadoua Balabdaoui , Kaspar Rufibach , Filippo Santambrogio

We study the dynamics of a continuous-time model of the Stochastic Gradient Descent (SGD) for the least-square problem. Indeed, pursuing the work of Li et al. (2019), we analyze Stochastic Differential Equations (SDEs) that model SGD either…

Machine Learning · Computer Science 2024-07-03 Adrien Schertzer , Loucas Pillaud-Vivien

In the regression model with errors in variables, we observe $n$ i.i.d. copies of $(Y,Z)$ satisfying $Y=f_{\theta^0}(X)+\xi$ and $Z=X+\epsilon$ involving independent and unobserved random variables $X,\xi,\epsilon$ plus a regression…

Statistics Theory · Mathematics 2009-09-29 Cristina Butucea , Marie-Luce Taupin
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