An Application of Directional Quantiles to Economic Data with a Multivariate Response

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F20%3A00534849" target="_blank" >RIV/67985807:_____/20:00534849 - isvavai.cz</a>

Výsledek na webu

<a href="http://hdl.handle.net/11104/0313010" target="_blank" >http://hdl.handle.net/11104/0313010</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5937/sjm15-22671" target="_blank" >10.5937/sjm15-22671</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Application of Directional Quantiles to Economic Data with a Multivariate Response

Popis výsledku v původním jazyce

Quantile regression represents a popular and useful methodology for modeling quantiles of a response variable based on one or more independent variables. Directional quantiles represent an available extension to the linear regression model with a multivariate response. However, we are not aware of any application of directional quantiles to real data in the literature. An illustration of directional quantiles to an economic dataset is presented in this paper, particularly a modeling of a two-dimensional response in the classical Engel's dataset on household consumption from the 19th century. The results reveal the directional quantiles to yield meaningful results. They order individual observations according to their depth, i.e. from the most central to the most outlying. We compare their result with those of a (more standard) outlier detection. On the whole, we perceive directional quantiles as a potentially useful tool for the analysis of data, if accompanied by a thorough analysis by standard tools.

Název v anglickém jazyce

An Application of Directional Quantiles to Economic Data with a Multivariate Response

Popis výsledku anglicky

Quantile regression represents a popular and useful methodology for modeling quantiles of a response variable based on one or more independent variables. Directional quantiles represent an available extension to the linear regression model with a multivariate response. However, we are not aware of any application of directional quantiles to real data in the literature. An illustration of directional quantiles to an economic dataset is presented in this paper, particularly a modeling of a two-dimensional response in the classical Engel's dataset on household consumption from the 19th century. The results reveal the directional quantiles to yield meaningful results. They order individual observations according to their depth, i.e. from the most central to the most outlying. We compare their result with those of a (more standard) outlier detection. On the whole, we perceive directional quantiles as a potentially useful tool for the analysis of data, if accompanied by a thorough analysis by standard tools.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Serbian Journal of Management

ISSN

1452-4864

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

RS - Srbská republika

Počet stran výsledku

11

Strana od-do

193-203

Kód UT WoS článku

000589838100002

EID výsledku v databázi Scopus

2-s2.0-85098551347