• 제목/요약/키워드: Statistical Procedures

검색결과 691건 처리시간 0.024초

A class of accelerated sequential procedures with applications to estimation problems for some distributions useful in reliability theory

  • Joshi, Neeraj;Bapat, Sudeep R.;Shukla, Ashish Kumar
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.563-582
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    • 2021
  • This paper deals with developing a general class of accelerated sequential procedures and obtaining the associated second-order approximations for the expected sample size and 'regret' (difference between the risks of the proposed accelerated sequential procedure and the optimum fixed sample size procedure) function. We establish that the estimation problems based on various lifetime distributions can be tackled with the help of the proposed class of accelerated sequential procedures. Extensive simulation analysis is presented in support of the accuracy of our proposed methodology using the Pareto distribution and a real data set on carbon fibers is also analyzed to demonstrate the practical utility. We also provide the brief details of some other inferential problems which can be seen as the applications of the proposed class of accelerated sequential procedures.

Nonparametric Procedures for Comparing Ordered Treatment Effects with a Control in a Randomized Block Design

  • Lim, Dong-Hoon
    • Journal of the Korean Statistical Society
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    • 제26권1호
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    • pp.89-100
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    • 1997
  • In this paper we are concerned with comparing ordered treatment effects with a control in a randomized block design with multiple observations per cell. Two nonparametric procedures for detecting which treatment are better than the control are proposed and compared. An example is given and the results of a Monte Carlo power study are discussed.

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A Comparative Study on Bayes Estimators for the Multivariate Normal Mcan

  • Kim, Dal-Ho;Lee, In suk;Kim, Hyun-Sook
    • Communications for Statistical Applications and Methods
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    • 제6권2호
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    • pp.501-510
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    • 1999
  • In this paper, we consider a comparable study on three Bayes procedures for the multivariate normal mean estimation problem. In specific we consider hierarchical Bayes empirical Bayes and robust Bayes estimators for the normal means. Then three procedures are compared in terms of the four comparison criteria(i.e. Average Relative Bias (ARB) Average Squared Relative Bias (ASRB) Average Absolute Bias(AAB) Average Squared Deviation (ASD) using the real data set.

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A Decision Tree Algorithm using Genetic Programming

  • Park, Chongsun;Ko, Young Kyong
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.845-857
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    • 2003
  • We explore the use of genetic programming to evolve decision trees directly for classification problems with both discrete and continuous predictors. We demonstrate that the derived hypotheses of standard algorithms can substantially deviated from the optimum. This deviation is partly due to their top-down style procedures. The performance of the system is measured on a set of real and simulated data sets and compared with the performance of well-known algorithms like CHAID, CART, C5.0, and QUEST. Proposed algorithm seems to be effective in handling problems caused by top-down style procedures of existing algorithms.

A Note on Methodologies Used in I-O Forecasting Model

  • Kim, Dai-Young
    • Journal of the Korean Statistical Society
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    • 제5권1호
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    • pp.35-48
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    • 1976
  • Since the solution vector for input-output forecasting models is not directly obtainable, several iterative procedures have been proposed and utilized. As is often the case in numerical analysis, the question of the consistency between the original system and the converged system of the proposed iteration has been ignored, and no one has tried to express the converged solution explicitly. This paper examines this question and points out the inconsistencies between various well-known iterative procedures used to solve input-output models and the original input-output system.

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On Estimating the Parameters of an Extended Form of Logarithmic Series Distribution

  • Kumar, C. Satheesh;Riyaza, A.
    • Communications for Statistical Applications and Methods
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    • 제20권5호
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    • pp.417-425
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    • 2013
  • We consider an extended version of a logarithmic series distribution and discuss the estimation of its parameters by the method of moments and the method of maximum likelihood. Test procedures are suggested to test the significance of the additional parameter of this distribution and all procedures are illustrated with the help of real life data sets. In addition, a simulation study is conducted to assess the performance of the estimators.

Selection Problems in terms of Coefficients of Vairiation

  • Park, Chi-Hoon;Jeon, Jong-Woo;Kim, Woo-Chul
    • Journal of the Korean Statistical Society
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    • 제11권1호
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    • pp.12-24
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    • 1982
  • Selection procedures are proposed for selecting the 'best' industrial process with the smallest fraction defective. For normally distributed industrial processes, this is equivalent to selecting in terms of coefficients of variation. For the case of known vairances, selection procedures by Bechhofer (1954), and Bechhofer and Turnball (1978) are appropriate. We treat this problem for the case of uknown variances with or without reference to a standard. The large sample solutions of design constants are tabulated and the performance of these approximate solutions are investigated.

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Large-Sample Comparisons of Statistical Calibration Procedures When the Standard Measurement is Also Subject to Error: The Replicated Case

  • Lee, Seung-Hoon;Yum, Bong-Jin
    • Journal of the Korean Statistical Society
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    • 제17권1호
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    • pp.9-23
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    • 1988
  • The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

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CHAIN DEPENDENCE AND STATIONARITY TEST FOR TRANSITION PROBABILITIES OF MARKOV CHAIN UNDER LOGISTIC REGRESSION MODEL

  • Sinha Narayan Chandra;Islam M. Ataharul;Ahmed Kazi Saleh
    • Journal of the Korean Statistical Society
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    • 제35권4호
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    • pp.355-376
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    • 2006
  • To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.

A Note on Bootstrapping in Sufficient Dimension Reduction

  • Yoo, Jae Keun;Jeong, Sun
    • Communications for Statistical Applications and Methods
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    • 제22권3호
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    • pp.285-294
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    • 2015
  • A permutation test is the popular and attractive alternative to derive asymptotic distributions of dimension test statistics in sufficient dimension reduction methodologies; however, recent studies show that a bootstrapping technique also can be used. We consider two types of bootstrapping dimension determination, which are partial and whole bootstrapping procedures. Numerical studies compare the permutation test and the two bootstrapping procedures; subsequently, real data application is presented. Considering two additional bootstrapping procedures to the existing permutation test, one has more supporting evidence for the dimension estimation of the central subspace that allow it to be determined more convincingly.