Testing convexity of the generalised hazard function

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F22%3A10251335" target="_blank" >RIV/61989100:27510/22:10251335 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s00362-021-01273-w" target="_blank" >https://link.springer.com/article/10.1007/s00362-021-01273-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00362-021-01273-w" target="_blank" >10.1007/s00362-021-01273-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Testing convexity of the generalised hazard function

Popis výsledku v původním jazyce

Let F, G be a pair of absolutely continuous cumulative distributions, where F is the distribution of interest and G is assumed to be known. The composition G(-1) circle F, which is referred to as the generalised hazard function of F with respect to G, provides a flexible framework for statistical inference of F under shape restrictions, determined by G, which enables the generalisation of some well-known models, such as the increasing hazard rate family. This paper is concerned with the problem of testing the null hypothesis H-0: &quot;G(-1) circle F is convex&quot;. The test statistic is based on the distance between the empirical distribution function and a corresponding isotonic estimator, which is denoted as the greatest relatively-convex minorant of the empirical distribution with respect to G. Under H-0, this estimator converges uniformly to F, giving rise to a rather simple and general procedure for deriving families of consistent tests, without any support restriction. As an application, a goodness-of-fit test for the increasing hazard rate family is provided.

Název v anglickém jazyce

Testing convexity of the generalised hazard function

Popis výsledku anglicky

Let F, G be a pair of absolutely continuous cumulative distributions, where F is the distribution of interest and G is assumed to be known. The composition G(-1) circle F, which is referred to as the generalised hazard function of F with respect to G, provides a flexible framework for statistical inference of F under shape restrictions, determined by G, which enables the generalisation of some well-known models, such as the increasing hazard rate family. This paper is concerned with the problem of testing the null hypothesis H-0: &quot;G(-1) circle F is convex&quot;. The test statistic is based on the distance between the empirical distribution function and a corresponding isotonic estimator, which is denoted as the greatest relatively-convex minorant of the empirical distribution with respect to G. Under H-0, this estimator converges uniformly to F, giving rise to a rather simple and general procedure for deriving families of consistent tests, without any support restriction. As an application, a goodness-of-fit test for the increasing hazard rate family is provided.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50200 - Economics and Business

Projekt

<a href="/cs/project/GA20-16764S" target="_blank" >GA20-16764S: Zobecněný přístup ke stochastické dominanci: teorie a finanční aplikace</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Statistical Papers

ISSN

0932-5026

e-ISSN

1613-9798

Svazek periodika

63

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

19

Strana od-do

1271-1289

Kód UT WoS článku

000739289800001

EID výsledku v databázi Scopus

2-s2.0-85121326697