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Asymptotic equivalence for nonparametric regression with dependent errors: Gauss–Markov processes
For the class of Gauss–Markov processes we study the problem of asymptotic equivalence of the nonparametric regression model with errors given by the...
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Editorial for special issue on advances in Actuarial Science and quantitative finance
This article provides an overview of all papers published on the special issue, Advances in Actuarial Science and Quantitative Finance. The special...
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Maximum Likelihood Estimation in the Mixed Fractional Vasicek Model
We investigate the asymptotic properties of the maximum likelihood estimator of the unknown parameters in the fractional Vasicek model driven by a...
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Simulation of Conditional Expectations Under Fast Mean-Reverting Stochastic Volatility Models
We study the simulation of a large system of stochastic processes subject to a common driving noise and fast mean-reverting stochastic volatilities....
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Least squares estimator of fractional Ornstein-Uhlenbeck processes with periodic mean
We first study the drift parameter estimation of the fractional Ornstein-Uhlenbeck process (fOU) with periodic mean for every ½ < H < 1. More...
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Multiple Time Model
In this chapter, we introduce discrete-time stochastic processes. We show that we can consider Ito formulas even in discrete-time models, which are...
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Adaptive efficient estimation for generalized semi-Markov big data models
In this paper we study generalized semi-Markov high dimension regression models in continuous time, observed at fixed discrete time moments. The...
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Exit Times, Undershoots and Overshoots for Reflected CIR Process with Two-Sided Jumps
In this paper, we investigate the reflected CIR process with two-sided jumps to capture the jump behavior and its non-negativeness. Applying the...
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Least-squares estimators based on the Adams method for stochastic differential equations with small Lévy noise
We consider stochastic differential equations (SDEs) driven by small Lévy noise with some unknown parameters and propose a new type of least-squares...
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Inference for a change-point problem under a generalised Ornstein–Uhlenbeck setting
Determining accurately when regime and structural changes occur in various time-series data is critical in many social and natural sciences. We...
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A review on asymptotic inference in stochastic differential equations with mixed effects
This paper is a survey of recent contributions on estimation in stochastic differential equations with mixed effects. These models involve N ...
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Prediction-based estimation for diffusion models with high-frequency data
This paper obtains asymptotic results for parametric inference using prediction-based estimating functions when the data are high-frequency...
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Function-on-Function Partial Quantile Regression
A function-on-function linear quantile regression model, where both the response and predictors consist of random curves, is proposed by extending...
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Optimal Berry-Esseen bound for an estimator of parameter in the Ornstein-Uhlenbeck process
This paper is concerned with the study of the rate of central limit theorem for the maximum likelihood estimator θ̂ T of the unknown parameter θ > 0,...
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Testing for linearity in scalar-on-function regression with responses missing at random
A goodness-of-fit test for the Functional Linear Model with Scalar Response (FLMSR) with responses Missing at Random (MAR) is proposed in this paper....
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A Bayesian quantile joint modeling of multivariate longitudinal and time-to-event data
Linear mixed models are traditionally used for jointly modeling (multivariate) longitudinal outcomes and event-time(s). However, when the outcomes...
