• 제목/요약/키워드: Sequential procedure

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A note on the sample size determination of sequential and multistage procedures

  • Choi, Kiheon
    • Journal of the Korean Data and Information Science Society
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    • 제23권6호
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    • pp.1279-1287
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    • 2012
  • We particularly emphasized how to determine the number of replications with sequential and multistage procedures. So, the t-test is used to achieve some predetermined level of accuracy efficiently with loss function in the case of normal, chi-squared, an exponential distributions. We provided that the relevance of procedures are sequential procedure, two-stage procedure, modified two-stage procedure, three-stage procedure and accelerated sequential procedure. Monte Carlo simulation is carried out to obtain the stopping sample size that minimizes the risk.

Efficiency and Minimaxity of Bayes Sequential Procedures in Simple versus Simple Hypothesis Testing for General Nonregular Models

  • Hyun Sook Oh;Anirban DasGupta
    • Journal of the Korean Statistical Society
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    • 제25권1호
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    • pp.95-110
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    • 1996
  • We consider the question of efficiency of the Bayes sequential procedure with respect to the optimal fixed sample size Bayes procedure in a simple vs. simple testing problem for data coming from a general nonregular density b(.theta.)h(x)l(x < .theta.). Efficiency is defined in two different ways in these caiculations. Also, the minimax sequential risk (and minimax sequential stratage) is studied as a function of the cost of sampling.

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Sequential Confidence Intervals for Quantiles Based on Recursive Density Estimators

  • Kim, Sung-Kyun;Kim, Sung-Lai
    • Journal of the Korean Statistical Society
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    • 제28권3호
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    • pp.297-309
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    • 1999
  • A sequential procedure of fixed-width confidence intervals for quantiles satisfying a condition of coverage probability is provided based on recursive density estimators. It is shown that the proposed sequential procedure is asymptotically efficient. In addition, the asymptotic normality for the proposed stopping time is derived.

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The Sequential Testing of Multiple Outliers in Linear Regression

  • Park, Jinpyo;Park, Heechang
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.337-346
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    • 2001
  • In this paper we consider the problem of identifying and testing the outliers in linear regression. first we consider the problem for testing the null hypothesis of no outliers. The test based on the ratio of two scale estimates is proposed. We show the asymptotic distribution of the test statistic by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure based on the suggested test is proposed and shown to perform fairly well. The forward sequential procedure is unaffected by masking and swamping effects because the test statistic is based on robust estimate.

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SEQUENTIAL MINIMAL OPTIMIZATION WITH RANDOM FOREST ALGORITHM (SMORF) USING TWITTER CLASSIFICATION TECHNIQUES

  • J.Uma;K.Prabha
    • International Journal of Computer Science & Network Security
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    • 제23권4호
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    • pp.116-122
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    • 2023
  • Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

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.

Sequential Estimation with $\beta$-Protection of the Difference of Two Normal Means When an Imprecision Function Is Variable

  • Kim, Sung-Lai;Kim, Sung-Kyun
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.379-389
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    • 2002
  • For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

The Forward Sequential Procedure for the Identifying Multiple Outliers in Linear Regression

  • Park, Jin-Pyo
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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    • pp.1053-1066
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    • 2005
  • In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the use of the so-called scale ratio tests for testing the null hypothesis of no outliers. This test is based on the ratio of two residual scale estimates. We show the asymptotic distribution of the test statistics and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed. The new method is compared with classical procedure in the real data example. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

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Accelerated Sequential Procedure to Estimate the Mean of Unknown Distribution

  • Son, M.S.;Hamdy, H.I.
    • Communications for Statistical Applications and Methods
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    • 제4권2호
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    • pp.367-376
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    • 1997
  • Consider the accelerated sequential procedure of Hall(1983). Second order asymptotic expression of well behaved functions of the stopping variable. The results is demonstrated by working out several point and interval estimation problems.

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On Fixed Width Confidence Bounds for the Difference of the Means of Two Linear Processes

  • Lee, Sang-Yeol
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.603-611
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    • 1996
  • In this article we consider a sequential procedure for the fixed width interval estimation of the means of two mutually independent linear processes. It is shown that the proposed stopping rule is asymptotically efficient as in iid samples (cf. Robbins, Simons and Starr(l967)).

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