• 제목/요약/키워드: sample of random size

검색결과 203건 처리시간 0.019초

A Bayesian inference for fixed effect panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
    • /
    • 제23권2호
    • /
    • pp.179-187
    • /
    • 2016
  • The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

A Note on the Optimum Character of One-Sided Sequential Probability Ratio Tests

  • Abel, Volker
    • 한국경영과학회지
    • /
    • 제9권2호
    • /
    • pp.23-27
    • /
    • 1984
  • We Observe a sequence of i. i. d random variables with density f or g. Only if g is true we should stop the process. Hence. the testing problem is completely described by a stopping time. Among all stopping times with error probability of first kind not exceeding a given bound, the one-sided sequential probability ratio test has smallest expected sample size if g is true. Moreover, the generalized one-sided SPRT has smallest expected sample size for g in the class of stopping times with expected sample size under f not falling below a given bound.

  • PDF

A Note on Parametric Bootstrap Model Selection

  • Lee, Kee-Won;Songyong Sim
    • Journal of the Korean Statistical Society
    • /
    • 제27권4호
    • /
    • pp.397-405
    • /
    • 1998
  • We develop parametric bootstrap model selection criteria in an example to fit a random sample to either a general normal distribution or a normal distribution with prespecified mean. We apply the bootstrap methods in two ways; one considers the direct substitution of estimated parameter for the unknown parameter, and the other focuses on the bias correction. These bootstrap model selection criteria are compared with AIC. We illustrate that all the selection rules reduce to the one sample t-test, where the cutoff points converge to some certain points as the sample size increases.

  • PDF

CONDITIONAL LARGE DEVIATIONS FOR 1-LATTICE DISTRIBUTIONS

  • Kim, Gie-Whan
    • 한국수학교육학회지시리즈B:순수및응용수학
    • /
    • 제4권1호
    • /
    • pp.97-104
    • /
    • 1997
  • The large deviations theorem of Cramer is extended to conditional probabilities in the following sense. Consider a random sample of pairs of random vectors and the sample means of each of the pairs. The probability that the first falls outside a certain convex set given that the second is fixed is shown to decrease with the sample size at an exponential rate which depends on the Kullback-Leibler distance between two distributions in an associated exponential familiy of distributions. Examples are given which include a method of computing the Bahadur exact slope for tests of certain composite hypotheses in exponential families.

  • PDF

Sample Size Determination Using the Stratification Algorithms with the Occurrence of Stratum Jumpers

  • Hong, Taekyong;Ahn, Jihun;Namkung, Pyong
    • Communications for Statistical Applications and Methods
    • /
    • 제11권2호
    • /
    • pp.297-311
    • /
    • 2004
  • In the sample survey for a highly skewed population, stratum jumpers often occur. Stratum jumpers are units having large discrepancies between a stratification variable and a study variable. We propose two models for stratum jumpers: a multiplicative model and a random replacement model. We also consider the modification of the L-H stratification algorithm such that we apply the previous models to L-H algorithm in determination of the sample sizes and the stratum boundaries. We evaluate the performances of the new stratification algorithms using real data. The result shows that L-H algorithm for the random replacement model outperforms other algorithms since the estimator has the least coefficient of variation.

방사성 토양폐기물 시료의 통계적 대표성에 관한 연구 (A Study on the Statistical Representativeness of Samples taken from Radioactive Soil)

  • 조한석;김태국;이강무;안섬진;손종식
    • 한국방사성폐기물학회:학술대회논문집
    • /
    • 한국방사성폐기물학회 2005년도 춘계 학술대회
    • /
    • pp.151-157
    • /
    • 2005
  • 한국원자력연구소에서는 토양폐기물의 규제해제를 통한 처리를 위하여 토양의 핵종 및 방사능분석에 대한 절차를 개발하고 있다. 토양의 규제해제를 위한 기반작업으로 대표성 있는 시료를 추출하기 위하여 균질화, 평균화를 거쳐 임의추출(random sample)하는 시료추출의 방법론을 결정하였다. 통계학적인 관점에서의 대표성은 시료추출의 방법론 뿐 만 아니라 시료의 크기를 얼마로 할 것인가에 대한 설계가 선행 되어야 한다. 본 연구에서는 토양폐기물에서 시료를 채취하는 절차에 따라 예비시료를 추출한 후 핵종 및 방사능평가 작업을 수행한 결과를 사용하여 신뢰구간과 오차 한계에 따른 시료의 개수를 산정하였다.

  • PDF

Optimal Rates of Convergence for Tensor Spline Regression Estimators

  • Koo, Ja-Yong
    • Journal of the Korean Statistical Society
    • /
    • 제19권2호
    • /
    • pp.105-112
    • /
    • 1990
  • Let (X, Y) be a pair random variables and let f denote the regression function of the response Y on the measurement variable X. Let K(f) denote a derivative of f. The least squares method is used to obtain a tensor spline estimator $\hat{f}$ of f based on a random sample of size n from the distribution of (X, Y). Under some mild conditions, it is shown that $K(\hat{f})$ achieves the optimal rate of convergence for the estimation of K(f) in $L_2$ and $L_{\infty}$ norms.

  • PDF

The Choice of a Primary Resolution and Basis Functions in Wavelet Series for Random or Irregular Design Points Using Bayesian Methods

  • Park, Chun-Gun
    • Communications for Statistical Applications and Methods
    • /
    • 제15권3호
    • /
    • pp.379-386
    • /
    • 2008
  • In this paper, the choice of a primary resolution and wavelet basis functions are introduced under random or irregular design points of which the sample size is free of a power of two. Most wavelet methods have used the number of the points as the primary resolution. However, it turns out that a proper primary resolution is much affected by the shape of an unknown function. The proposed methods are illustrated by some simulations.

Tail Probability Approximations for the Ratio of two Independent Sequences of Random Variables

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
    • /
    • 제10권2호
    • /
    • pp.415-428
    • /
    • 1999
  • In this paper, we study the saddlepoint approximations for the ratio of two independent sequences of random variables. In Section 2, we review the saddlepoint approximation to the probability density function. In section 3, we derive an saddlepoint approximation formular for the tail probability by following Daniels'(1987) method. In Section 4, we represent a numerical example which shows that the errors are small even for small sample size.

  • PDF