Asymptotic Properties of Koenker–Bassett Estimator in Regression Model with Long-Range Dependence
Анотація
This article deals with asymptotic distribution of Koenker-Bassett estimator in continuous time regression model with long-range dependent noise. It is proved that the asymptotic distribution of the normed estimator coincides with asymptotic distribution of the integral of an indicator random process generated by the random noise weighted by regression function gradient. A theorem is formulated also on asymptotic normality of the last integral.
Класифікація
Ідентифікатори
Рецензії (0)
Написати рецензіюРецензій ще немає. Будьте першим!
Схожі роботи
New copulas based on general partitions-of-unity and their applications to risk management (part II)
Схоже за: Bayesian Methods and Mixture Models · Financial Risk and Volatility Modeling · Statistical Methods and Inference
Nonparametric estimation of the kernel function of symmetric stable moving average random functions
Схоже за: Bayesian Methods and Mixture Models · Financial Risk and Volatility Modeling · Statistical Methods and Inference
Harmonic analysis tools for statistical inference in the spectral domain
Схоже за: Bayesian Methods and Mixture Models · Statistical Methods and Inference
Jacobi probability distribution for approximation of emperic statistic distributions
Схоже за: Bayesian Methods and Mixture Models · Financial Risk and Volatility Modeling
On the Whittle estimators for some classes of continuous-parameter random processes and fields
Схоже за: Financial Risk and Volatility Modeling · Statistical Methods and Inference
Standard maximum likelihood drift parameter estimator in the homogeneous diffusion model is always strongly consistent
Схоже за: Financial Risk and Volatility Modeling · Statistical Methods and Inference