| Autor: |
Leipus, Remigijus, Philippe, Anne, Pilipauskaitė, Vytautė, Surgailis, Donatas |
| Rok vydání: |
2015 |
| Předmět: |
|
| Zdroj: |
Journal of Multivariate Analysis 153 (2017) 121-135 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1016/j.jmva.2016.09.007 |
| Popis: |
We discuss nonparametric estimation of the distribution function $G(x)$ of the autoregressive coefficient $a \in (-1,1)$ from a panel of $N$ random-coefficient AR(1) data, each of length $n$, by the empirical distribution function of lag 1 sample autocorrelations of individual AR(1) processes. Consistency and asymptotic normality of the empirical distribution function and a class of kernel density estimators is established under some regularity conditions on $G(x)$ as $N$ and $n$ increase to infinity. The Kolmogorov-Smirnov goodness-of-fit test for simple and composite hypotheses of Beta distributed $a$ is discussed. A simulation study for goodness-of-fit testing compares the finite-sample performance of our nonparametric estimator to the performance of its parametric analogue discussed in Beran et al. (2010). |
| Databáze: |
arXiv |
| Externí odkaz: |
|
