• 제목/요약/키워드: Empirical Quantiles

검색결과 19건 처리시간 0.023초

Rate of Convergence of Empirical Distributions and Quantiles in Linear Processes with Applications to Trimmed Mean

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.435-441
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    • 1999
  • A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.

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ASYMPTOTIC DEPENDENCE BETWEEN RANDOM CENTRAL QUASI-RANGES AND RANDOM EMPIRICAL QUANTILES

  • Nigm, E.M.
    • Journal of applied mathematics & informatics
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    • 제16권1_2호
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    • pp.289-302
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    • 2004
  • The asymptotic dependence between the central quasi-ranges and empirical quantiles was studied. The asymptotic dependence are obtained when the sample size is a positive integer valued random variable (r. v.). The dependence conditions and limit forms are obtained under generl conditions such as : the interrelation of the basic variables (the original random sample) and the random sample size is not restricted. In additition the normalizing constants do not depend on the random size.

Quantiles for Shapiro-Francia W' Statistic

  • Rahman, Mezbahur;Ali, Mir Masoom
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.1-10
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    • 1999
  • Table of the empirical quantiles for the well known Shapiro-Francia W' goodness of fit statistic is produced which is more accurate than the existing ones. Prediction equation for the quantiles of W' statistic for sample sizes 30 or more we developed. The process of computing the expected values for the standard normal variate is discussed. This work is intended to make the Shapiro-Francia W' statistic more accessible to the practitioner.

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Iterative Support Vector Quantile Regression for Censored Data

  • Shim, Joo-Yong;Hong, Dug-Hun;Kim, Dal-Ho;Hwang, Chang-Ha
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.195-203
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    • 2007
  • In this paper we propose support vector quantile regression (SVQR) for randomly right censored data. The proposed procedure basically utilizes iterative method based on the empirical distribution functions of the censored times and the sample quantiles of the observed variables, and applies support vector regression for the estimation of the quantile function. Experimental results we then presented to indicate the performance of the proposed procedure.

Quantile regression analysis: A novel approach to determine distributional changes in rainfall over Sri Lanka

  • S.S.K, Chandrasekara;Uranchimeg, Sumiya;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2017년도 학술발표회
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    • pp.228-232
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    • 2017
  • Extreme hydrological events can cause serious threats to the society. Hence, the selection of probability distributions for extreme rainfall is a fundamental issue. For this reason, this study was focused on understanding possible distributional changes in annual daily maximum rainfalls (AMRs) over time in Sri Lanka using quantile regression. A simplified nine-category distributional-change scheme based on comparing empirical probability density function of two years (i.e. the first year and the last year), was used to determine the distributional changes in AMRs. Daily rainfall series of 13 station over Sri Lanka were analyzed for the period of 1960-2015. 4 distributional change categories were identified for the AMRs. 5 stations showed an upward trend in all the quantiles (i.e. 9 quantiles: from 0.05 to 0.95 with an increment of 0.01 for the AMR) which could give high probability of extreme rainfall. On the other hand, 8 stations showed a downward trend in all the quantiles which could lead to high probability of the low rainfall. Further, we identified a considerable spatial diversity in distributional changes of AMRs over Sri Lanka.

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WEAK CONVERGENCE FOR STATIONARY BOOTSTRAP EMPIRICAL PROCESSES OF ASSOCIATED SEQUENCES

  • Hwang, Eunju
    • 대한수학회지
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    • 제58권1호
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    • pp.237-264
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    • 2021
  • In this work the stationary bootstrap of Politis and Romano [27] is applied to the empirical distribution function of stationary and associated random variables. A weak convergence theorem for the stationary bootstrap empirical processes of associated sequences is established with its limiting to a Gaussian process almost surely, conditionally on the stationary observations. The weak convergence result is proved by means of a random central limit theorem on geometrically distributed random block size of the stationary bootstrap procedure. As its statistical applications, stationary bootstrap quantiles and stationary bootstrap mean residual life process are discussed. Our results extend the existing ones of Peligrad [25] who dealt with the weak convergence of non-random blockwise empirical processes of associated sequences as well as of Shao and Yu [35] who obtained the weak convergence of the mean residual life process in reliability theory as an application of the association.

Regression Quantile Estimations on Censored Survival Data

  • 심주용
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.31-38
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    • 2002
  • In the case of multiple survival times which might be censored at each covariate vector, we study the regression quantile estimations in this paper. The estimations are based on the empirical distribution functions of the censored times and the sample quantiles of the observed survival times at each covariate vector and the weighted least square method is applied for the estimation of the regression quantile. The estimators are shown to be asymptotically normally distributed under some regularity conditions.

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Value at Risk Forecasting Based on Quantile Regression for GARCH Models

  • Lee, Sang-Yeol;Noh, Jung-Sik
    • 응용통계연구
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    • 제23권4호
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    • pp.669-681
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    • 2010
  • Value-at-Risk(VaR) is an important part of risk management in the financial industry. This paper present a VaR forecasting for financial time series based on the quantile regression for GARCH models recently developed by Lee and Noh (2009). The proposed VaR forecasting features the direct conditional quantile estimation for GARCH models that is well connected with the model parameters. Empirical performance is measured by several backtesting procedures, and is reported in comparison with existing methods using sample quantiles.

COVID-19 팬데믹이 BTC 변동성과 거래량의 관계구조에 미친 영향 분석: CRQ 접근법 (The Impact of COVID-19 Pandemic on the Relationship Structure between Volatility and Trading Volume in the BTC Market: A CRQ approach)

  • 박범조
    • 경제분석
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    • 제27권1호
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    • pp.67-90
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    • 2021
  • 본 연구는 투자자의 거래행태를 민감하게 반영하는 비트코인(BTC) 시장 자료를 이용한 실증분석을 통해 COVID-19 팬데믹이 발생하기 전과 후에 변동성과 거래량의 비선형 관계가 바뀌었다는 흥미로운 사실을 발견하였다. 즉, COVID-19 팬데믹 이전의 안정적 시장 상태에서는 정보 유입 패러다임에 근거한 이론처럼 두 변수의 관계가 양(+)으로 나타났지만 COVID-19 팬데믹 기간에 발생한 극단적 시장 스트레스 상태에서는 두 변수의 의존관계 구조가 달라지고 심지어 음(-)의 관계가 나타났다. 이는 행태경제학적 관점에서 COVID-19 팬데믹 기간의 시장 스트레스 증가가 투자자의 거래 행태(behavior)를 변화시켜 자산시장에 구조변화를 일으켰으며, 변동성과 거래량의 비선형 의존관계(특히, 극단적 분위수(quantiles)의 의존성)에 중대한 영향을 미친 결과라고 추론해 볼 수 있다. 따라서 정보 유입 외에 시장 스트레스로 인한 행태적 편의나 군집행동(herding)과 같은 심리현상이 두 변수의 의존관계 구조를 변화시키는 주요인이 될 수 있다는 전제하에 이를 검정해보았다. 본 연구는 실증분석을 위해 Ross (2015)의 구조변화 탐지 검정을 수행하였으며, 독립적이고 동일하게 분포하는(i.i.d.) 임의변수 가정 없이 비선형 관계구조와 분포 꼬리 부분의 비대칭적 의존관계를 면밀히 파악할 수 있는 Copula 회귀분위수(CRQ) 접근법을 제안하였다.

Do Firm Characteristics Determine Capital Structure of Pakistan Listed Firms? A Quantile Regression Approach

  • KHAN, Karamat;QU, Jing;SHAH, Muhammad Haroon;BAH, Kebba;KHAN, Irfan Ullah
    • The Journal of Asian Finance, Economics and Business
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    • 제7권5호
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    • pp.61-72
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    • 2020
  • The purpose of this study is to investigate the determinants of the capital structure of firms operating in a developing economy, Pakistan. The quantile regression method is applied on a sample of 183 non-financial companies listed on the Pakistan Stock Exchange during the period of 2008-2017. Specifically, the empirical analysis focuses on changes in the coefficients of the determinants according to the leverage ratio quantiles of the examined listed firms. The findings show that the capital structure of Pakistan listed firms differs between firms in different quantiles of leverage. These differences are significant with the sign of explanatory variables changes with the level of leverage. The research result found tangibility, profitability and age to be positively related to leverage among listed firms in Pakistan. However, size, liquidity and non-debt tax shield (NDTS) are negatively related to leverage. A firm's growth and risk are found to be insignificant predictors of capital structure in Pakistan listed firms. Moreover, the study also found a significant impact of industry characteristic on leverage. The findings of this study indicate that an individual firm's finance policy needs to be responsive to the firm's characteristics and should match with the different borrowing requirements of listed firms.