• 제목/요약/키워드: residual empirical distribution

검색결과 23건 처리시간 0.032초

ON THE GOODNESS OF FIT TEST FOR DISCRETELY OBSERVED SAMPLE FROM DIFFUSION PROCESSES: DIVERGENCE MEASURE APPROACH

  • Lee, Sang-Yeol
    • 대한수학회지
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    • 제47권6호
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    • pp.1137-1146
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    • 2010
  • In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.

On the Residual Empirical Distribution Function of Stochastic Regression with Correlated Errors

  • Zakeri, Issa-Fakhre;Lee, Sangyeol
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.291-297
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    • 2001
  • For a stochastic regression model in which the errors are assumed to form a stationary linear process, we show that the difference between the empirical distribution functions of the errors and the estimates of those errors converges uniformly in probability to zero at the rate of $o_{p}$ ( $n^{-}$$\frac{1}{2}$) as the sample size n increases.

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On scaled cumulative residual Kullback-Leibler information

  • Hwang, Insung;Park, Sangun
    • Journal of the Korean Data and Information Science Society
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    • 제24권6호
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    • pp.1497-1501
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    • 2013
  • Cumulative residual Kullback-Leibler (CRKL) information is well defined on the empirical distribution function (EDF) and allows us to construct a EDF-based goodness of t test statistic. However, we need to consider a scaled CRKL because CRKL is not scale invariant. In this paper, we consider several criterions for estimating the scale parameter in the scale CRKL and compare the performances of the estimated CRKL in terms of both power and unbiasedness.

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.

잔차를 이용한 코플라 모수 추정 (Residual-based copula parameter estimation)

  • 나옥경;권성훈
    • 응용통계연구
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    • 제29권1호
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    • pp.267-277
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    • 2016
  • 본 연구에서는 잔차를 이용하여 오차항의 코플라 함수를 추정하는 문제를 고려하였다. 확률적 회귀모형을 개별모형으로 갖는 경우, 오차항 대신 잔차들의 경험적 분포함수를 이용하여 구한 코플라 모수에 대한 준모수적 추정량의 성질을 살펴보았으며, 이 추정량이 일치추정량이 되기 위한 조건을 구하였다. 응용사례로 코플라-자기회귀이동평균 모형을 다루었으며, 모의실험을 통해 자기회귀 근사를 통해 얻은 잔차를 이용하여 계산한 추정량의 성질도 살펴보았다.

Kullback-Leibler Information of the Equilibrium Distribution Function and its Application to Goodness of Fit Test

  • Park, Sangun;Choi, Dongseok;Jung, Sangah
    • Communications for Statistical Applications and Methods
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    • 제21권2호
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    • pp.125-134
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    • 2014
  • Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

A Study on the Trend Change Point of NBUE-property

  • Kim, Dae-Kyung
    • Communications for Statistical Applications and Methods
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    • 제3권2호
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    • pp.275-282
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    • 1996
  • A life distribution F with survival function $\overline{F}$=1-F, finite mean $\mu$ and mean residual life m(t) is said to be NBUE(NWUE) if m(t)$\leq$($\geq$) .$\mu$ for t$\geq$0. This NBUE property can equivalently be characterized by the fact that $\varphi$(u)$\geq$($\leq$)u for 0$\leq$u$\leq$1, where $\varphi$(u) is the scaled total-time-on test transform of F. A generalization of the NBUE properties is that there is a value of p such that $\varphi$(u)\geq.u$ for 0$\leq$u$\leq$p and $\varphi$(u)\leq$$\leq$u$\leq$1, or vice versa. This means that we have a trend change in the NBUE property. In this paper we point out an error of Klefsjo's paper (1988). He erroneously takes advantage of trend change point of failure rate to calculate the empirical test size and power in lognormal distribution. We solves the trend change point of mean residual lifetime and recalculate the empirical test size and power of Klefsjo (1988) in mocensoring case.

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Estimator of Mean Residual Life for Some Parametric Families Using Censored Data

  • Cho, Byung Yup;Choi, Kuey Chung;Choi, Sook Hee;Son, Young Nam
    • 품질경영학회지
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    • 제23권2호
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    • pp.80-90
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    • 1995
  • In this paper we consider a new estimator of mean residual life(MRL) under the random censorship model, based on the partial moment of the distribution. The parameters of a partial moment are estimated by its maximum likelihood estimators when the underlying distribution is known. Though the new estimator is not a consistent estimator of the MRL, it is shown to have smaller mean squared error than the well known empirical MRL estimator for a parametric family. We also compare the proposed estimator with some other estimators in terms of MSE for exponential and lognormal distributions using censored data.

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모수족에서 평균 잔여수명의 추정량 (Estimator of the Mean Residual Life for Some Parametric Families)

  • Kuey Chung Choi;Kyung Hyun Nam
    • 응용통계연구
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    • 제7권2호
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    • pp.89-100
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    • 1994
  • 본 논문에서는 평균 잔여수명의 추정에 있어서 Weibull과 gamma 분포의 평균 잔여수명을 구하는데 적분이 쉽게 되지 않으므로 부분적률에 근거한 새로운 추정량을 제시하였으며, 비록 이 추정량은 일치추정량이 아니지만 소표본인 경우에서 일치추정량인 기존의 경험적 추정량보다 평균제곱오차가 작다는 것을 몬테칼로 기법을 써서 보였다.

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Comparison of Structural Change Tests in Linear Regression Models

  • Kim, Jae-Hee
    • 응용통계연구
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    • 제24권6호
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    • pp.1197-1211
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    • 2011
  • The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.