Model checking for parametric single-index quantile autoregression
نویسندگان
چکیده
منابع مشابه
Quantile Autoregression
We consider quantile autoregression (QAR) models in which the autoregressive coefficients can be expressed as monotone functions of a single, scalar random variable. The models can capture systematic influences of conditioning variables on the location, scale and shape of the conditional distribution of the response, and therefore constitute a significant extension of classical constant coeffic...
متن کاملModel checking for parametric single-index models: A dimension- reduction model-adaptive approach
Local smoothing testing based on multivariate nonparametric regression estimation is one of the main model checking methodologies in the literature. However, the relevant tests suffer from typical curse of dimensionality, resulting in slow convergence rates to their limits under the null hypothesis and less deviation from the null hypothesis under alternative hypotheses. This problem prevents t...
متن کاملEstimation of single-index quantile regression Model
Abstract The conditional quantile function m(X) of response variable Y given the value of covariate X is modeled through a single-index model, i.e. m(X) = m(θ 0 X) for some unknown parameter vector θ0. An iterated algorithm is proposed to estimate θ0. To establish the root-n consistency of the estimator, we prove a convexity lemma for almost sure convergence, parallel to the results by Pollard ...
متن کاملCopula-Based Quantile Autoregression
Parametric copulae are shown to be an attractive device for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed estimators are established, leading to a general framework for inference and model specificat...
متن کاملIssues on quantile autoregression ∗
We congratulate Koenker and Xiao on their interesting and important contribution to the quantile autoregression (QAR). The paper provides a comprehensive overview on the QAR model, from probabilistic aspects, to model identification, statistical inferences, and empirical applications. The attempt to integrate the quantile regression and the QAR process is intriguing. It demonstrates surprisingl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SCIENTIA SINICA Mathematica
سال: 2019
ISSN: 1674-7216
DOI: 10.1360/scm-2018-0259