On the Whittle estimator for linear random noise spectral density parameter in continuous-time nonlinear regression models

09/23/2019
by   A. V. Ivanov, et al.
0

A continuous-time nonlinear regression model with Lévy-driven linear noise process is considered. Sufficient conditions of consistency and asymptotic normality of the Whittle estimator for the parameter of the noise spectral density are obtained in the paper.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/22/2019

Parameter estimation for random sampled Regression Model with Long Memory Noise

In this article, we present the least squares estimator for the drift pa...
research
03/28/2021

A Temporal Kernel Approach for Deep Learning with Continuous-time Information

Sequential deep learning models such as RNN, causal CNN and attention me...
research
04/19/2021

Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes

For the class of Gauss-Markov processes we study the problem of asymptot...
research
11/05/2012

Soft (Gaussian CDE) regression models and loss functions

Regression, unlike classification, has lacked a comprehensive and effect...
research
01/16/2020

The Widely Linear Complex Ornstein-Uhlenbeck Process with Application to Polar Motion

Complex-valued and widely linear modelling of time series signals are wi...
research
06/27/2018

von Mises Tapering: A Circular Data Windowing

Continuous standard windowing is revisited and a new taper shape is intr...

Please sign up or login with your details

Forgot password? Click here to reset