Discontinuities in Robust Nonparametric Regression Discontinuities in Robust Nonparametric Regression with Α-mixing Dependence

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10365791" target="_blank" >RIV/00216208:11320/17:10365791 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.tandfonline.com/doi/full/10.1080/10485252.2017.1303061?scroll=top&needAccess=true" target="_blank" >http://www.tandfonline.com/doi/full/10.1080/10485252.2017.1303061?scroll=top&needAccess=true</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/10485252.2017.1303061" target="_blank" >10.1080/10485252.2017.1303061</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Discontinuities in Robust Nonparametric Regression Discontinuities in Robust Nonparametric Regression with Α-mixing Dependence

Popis výsledku v původním jazyce

The main idea of the paper is to introduce a robust regression estimation method under an α-mixing dependence assumption, staying free of any para- metric model restrictions while also allowing for some sudden changes in the unknown regression function. The sudden changes in the model may correspond to discontinuity points (jumps) or higher order breaks (jumps in corresponding derivatives) as well. We firstly derive some important statistical properties for local polynomial M-smoother estimates and we will propose a statistical test to decide whether some given point of interest is significantly important for a change to occur or not. As the asymptotic distribution of the test statistic depends on quantities which are left unknown we also introduce a bootstrap algorithm which can be used to mimic the target distribution of interest. All necessary proofs are provided together with some experimental results from a simulation study and a real data example.

Název v anglickém jazyce

Discontinuities in Robust Nonparametric Regression Discontinuities in Robust Nonparametric Regression with Α-mixing Dependence

Popis výsledku anglicky

The main idea of the paper is to introduce a robust regression estimation method under an α-mixing dependence assumption, staying free of any para- metric model restrictions while also allowing for some sudden changes in the unknown regression function. The sudden changes in the model may correspond to discontinuity points (jumps) or higher order breaks (jumps in corresponding derivatives) as well. We firstly derive some important statistical properties for local polynomial M-smoother estimates and we will propose a statistical test to decide whether some given point of interest is significantly important for a change to occur or not. As the asymptotic distribution of the test statistic depends on quantities which are left unknown we also introduce a bootstrap algorithm which can be used to mimic the target distribution of interest. All necessary proofs are provided together with some experimental results from a simulation study and a real data example.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA15-09663S" target="_blank" >GA15-09663S: Modelování dynamických finančních procesů se strukturálními změnami</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Nonparametric Statistics

ISSN

1048-5252

e-ISSN

—

Svazek periodika

29

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

29

Strana od-do

447-475

Kód UT WoS článku

000405400300015

EID výsledku v databázi Scopus

—