• Title/Summary/Keyword: Statistical Functions

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A Bayesian analysis based on beta-mixtures for software reliability models

  • Nam Seungmin;Kim Kiwoong;Cho Sinsup;Yeo Inkwon
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2004.04a
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    • pp.430-435
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    • 2004
  • Nonhomogeneous Poisson Process is often used to model failure times which occurred in software reliability and hardware reliability models. It can be characterized by its intensity functions or mean value functions. Many parametric intensity models have been proposed to account for the failure mechanism in real situation. In this paper, we propose a Bayesian semiparametric approach based on beta-mixtures. Two real datasets are analyzed.

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Multivariate Test based on the Multiple Testing Approach

  • Hong, Seung-Man;Park, Hyo-Il
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.821-827
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    • 2012
  • In this study, we propose a new nonparametric test procedure for the multivariate data. In order to accommodate the generalized alternatives for the multivariate case, we construct test statistics via-values with some useful combining functions. Then we illustrate our procedure with an example and compare efficiency among the combining functions through a simulation study. Finally we discuss some interesting features related with the new nonparametric test as concluding remarks.

ASYMPTOTICAL INVARIANT AND ASYMPTOTICAL LACUNARY INVARIANT EQUIVALENCE TYPES FOR DOUBLE SEQUENCES VIA IDEALS USING MODULUS FUNCTIONS

  • Dundar, Erdinc;Akin, Nimet Pancaroglu;Ulusu, Ugur
    • Honam Mathematical Journal
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    • v.43 no.1
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    • pp.100-114
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    • 2021
  • In this study, we present some asymptotical invariant and asymptotical lacunary invariant equivalence types for double sequences via ideals using modulus functions and investigate relationships between them.

Coefficient Bounds for a Subclass of Harmonic Mappings Convex in One Direction

  • Shabani, Mohammad Mehdi;Yazdi, Maryam;Sababe, Saeed Hashemi
    • Kyungpook Mathematical Journal
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    • v.61 no.2
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    • pp.269-278
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    • 2021
  • In this paper, we investigate harmonic univalent functions convex in the direction 𝜃, for 𝜃 ∈ [0, 𝜋). We find bounds for |fz(z)|, ${\mid}f_{\bar{z}}(z){\mid}$ and |f(z)|, as well as coefficient bounds on the series expansion of functions convex in a given direction.

On The Sets of f-Strongly Cesàro Summable Sequences

  • Ibrahim Sulaiman Ibrahim;Rifat Colak
    • Kyungpook Mathematical Journal
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    • v.64 no.2
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    • pp.235-244
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    • 2024
  • In this paper, we establish relations between the sets of strongly Cesàro summable sequences of complex numbers for modulus functions f and g satisfying various conditions. Furthermore, for some special modulus functions, we obtain relations between the sets of strongly Cesàro summable and statistically convergent sequences of complex numbers.

Comparison of Objective Functions for Feed-forward Neural Network Classifiers Using Receiver Operating Characteristics Graph

  • Oh, Sang-Hoon;Wakuya, Hiroshi
    • International Journal of Contents
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    • v.10 no.1
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    • pp.23-28
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    • 2014
  • When developing a classifier using various objective functions, it is important to compare the performances of the classifiers. Although there are statistical analyses of objective functions for classifiers, simulation results can provide us with direct comparison results and in this case, a comparison criterion is considerably critical. A Receiver Operating Characteristics (ROC) graph is a simulation technique for comparing classifiers and selecting a better one based on a performance. In this paper, we adopt the ROC graph to compare classifiers trained by mean-squared error, cross-entropy error, classification figure of merit, and the n-th order extension of cross-entropy error functions. After the training of feed-forward neural networks using the CEDAR database, the ROC graphs are plotted to help us identify which objective function is better.

CLASSIFICATION FUNCTIONS FOR EVALUATING THE PREDICTION PERFORMANCE IN COLLABORATIVE FILTERING RECOMMENDER SYSTEM

  • Lee, Seok-Jun;Lee, Hee-Choon;Chung, Young-Jun
    • Journal of applied mathematics & informatics
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    • v.28 no.1_2
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    • pp.439-450
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    • 2010
  • In this paper, we propose a new idea to evaluate the prediction accuracy of user's preference generated by memory-based collaborative filtering algorithm before prediction process in the recommender system. Our analysis results show the possibility of a pre-evaluation before the prediction process of users' preference of item's transaction on the web. Classification functions proposed in this study generate a user's rating pattern under certain conditions. In this research, we test whether classification functions select users who have lower prediction or higher prediction performance under collaborative filtering recommendation approach. The statistical test results will be based on the differences of the prediction accuracy of each user group which are classified by classification functions using the generative probability of specific rating. The characteristics of rating patterns of classified users will also be presented.

A Note on Eigen Transformation of a Correlation-type Random Matrix

  • Kim, Kee-Young;Lee, Kwang-Jin
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.339-345
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    • 1993
  • It is well known that distribution of functions of eigen values and vectors of a certain matrix plays an important role in multivariate analysis. This paper deals with the transformation of a correlation-type random matrix to its eigen values and vectors. Properties of the transformation are also considered. The results obtained are applied to express the joint distribution of eigen values and vectors of the correlation matrix when sample is taken from a m-variate spherical distribution.

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Efficient Sequential Estimation in a Compound Poisson Process

  • Bai, Do-Sun;Kim, Myung-Soo;Jang, Joong-Soon
    • Journal of the Korean Statistical Society
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    • v.15 no.2
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    • pp.87-96
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    • 1986
  • Sequential estimation of parameters in a compound Poisson process whose jump sizes are one-parameter exponential class random variables is discussed. Cramer-Rao type information inequality is used as an efficiency cirterion. Unbiased estimators for certain parametric functions whose variance attain the lower bound are all characterized with the corresponding sampling plans.

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A Simultaneous Test Procedure

  • Hong, Seungman;Cho, Joong-Jae;Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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    • pp.11-22
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    • 2014
  • In this study, we propose a simultaneous test procedure based on the individual - values for each sub-null hypothesis with several well-known combining functions. We then compare the efficiency of our procedure with existing tests by obtaining empirical powers through a simulation study. Finally, we discuss some interesting features related to simultaneous test and point out a misconduct for the simulation study published in the previous work.