• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.513-521
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• 2018

The goal of sufficient dimension reduction (SDR) is to replace original p-dimensional predictors with a lower-dimensional linearly transformed predictor. The sliced inverse regression (SIR) (Li, Journal of the American Statistical Association, 86, 316-342, 1991) is one of the most popular SDR methods because of its applicability and simple implementation in practice. However, SIR may yield different dimension reduction results for different numbers of slices and despite its popularity, is a clear deficit for SIR. To overcome this, a fused sliced inverse regression was recently proposed. The study shows that the dimension-reduced predictors is robust to the numbers of the slices, but it does not investigate how robust its dimension determination is. This paper suggests a permutation dimension determination for the fused sliced inverse regression that is compared with SIR to investigate the robustness to the numbers of slices in the dimension determination. Numerical studies confirm this and a real data example is presented.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.401-413
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• 2015

In this article, we review the statistical methods and theory for dose finding in early phase clinical trials, where the primary objective is to identify an acceptable dose for further clinical investigation. The dose finding literature is initially motivated by applications in phase I clinical trials, in which dose finding is often formulated as a percentile estimation problem. We will present some important phase I methods and give an update on new theoretical developments since a recent review by Cheung (2010), with an aim to cover a broader class of dose finding problems and to illustrate how the general dose finding theory may be applied to evaluate and improve a method. Specifically, we will illustrate theoretical techniques with some numerical results in the context of a phase I/II study that uses trinary toxicity/efficacy outcomes as basis of dose finding.

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.359-370
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• 2019

Grouping structures in covariates are often ignored in regression models. Recent statistical developments considering grouping structure shows clear advantages; however, reflecting the grouping structure on the quantile regression model has been relatively rare in the literature. Treating the grouping structure is usually conducted by employing a group penalty. In this work, we explore the idea of group penalty to the quantile regression models. The grouping structure is assumed to be known, which is commonly true for some cases. For example, group of dummy variables transformed from one categorical variable can be regarded as one group of covariates. We examine the group quantile regression models via two real data analyses and simulation studies that reveal the beneficial performance of group quantile regression models to the non-group version methods if there exists grouping structures among variables.

• Nonlinear Functional Analysis and Applications
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• v.28 no.1
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• pp.135-173
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• 2023

The purpose of this paper is to introduce and study a method for solving the split equality of variational inequality and f, g-fixed point problems in reflexive real Banach spaces, where the variational inequality problems are for uniformly continuous pseudomonotone mappings and the fixed point problems are for Bregman relatively f, g-nonexpansive mappings. A strong convergence theorem is proved under some mild conditions. Finally, a numerical example is provided to demonstrate the effectiveness of the algorithm.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.291-308
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• 2024

The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.221-235
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• 2009

This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.

• Computers and Concrete
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• v.19 no.5
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• pp.527-535
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• 2017

In this study, an aging deformation statistical model for a unique high and steep rock slope was proposed, and the aging characteristic of the slope deformation was better reflected. The slope displacement was affected by multiple-environmental factors in multiple scales and displayed the same tendency with a rising water level. The statistical model of the high and steep rock including non-aging factors was set up based on previous analyses and the study of the deformation and residual tendency. The rule and importance of the water level factor as a non-aging unit was analyzed. A partitioned statistical model and mutation model were established for the comprehensive cumulative displacement velocity with the monitoring study under multiple factors and multiple parameters. A spatial model was also developed to reflect and predict the whole and sectional deformation character by combining aging, deformation and space coordinates. A neural network model was built to fit and predict the deformation with a high degree of precision by mastering its feature of complexity and randomness. A three-dimensional finite element model of the slope was applied to approach the structure character using numerical simulations. Further, a three-dimensional finite element model of the slope and dam was developed, and the whole deformation state was analyzed. This study is expected to provide a powerful and systematic method to analyze very high, important and dangerous slopes.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.7 s.238
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• pp.846-853
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• 2005

In this paper, mass transfer in turbulent flow around a rotating circular cylinder is investigated by Direct Numerical Simulation for Schmidt numbers Sc=1 and 1670. Correlation between Sherwood and Reynolds number predicted agrees well with other experimental results over both Sc. Reynolds analogy identified at Sc=1 definitely causes a strong correlation between concentration fluctuation and streamwise velocity. For Sc=1670, it is found that positive small values of concentration fluctuations are observed more frequently than the case of Sc=1 particularly out of the range of Nernst diffusion layer in the viscous sub-layer. This fact is fully confirmed by detailed statistical study using a probability density function of concentration fluctuations.

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.54-61
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• 2015

In the present study, a flow solver using a kinetic BGK scheme was developed for the compressible Navier-Stokes equation. The kinetic BGK scheme was used to simulate flow field from the continuum up to the transitional regime, because the kinetic BGK scheme can take into account the statistical properties of the gas particles in a non-equilibrium state. Various numerical simulations were conducted by the present flow solver. The laminar flow around flat plate and the hypersonic flow around hollow cylinder of flare shape in the continuum regime were numerically simulated. The numerical results showed that the flow solver using the kinetic BGK scheme can obtain accurate and robust numerical solutions. Also, the present flow solver was applied to the hypersonic flow problems around circular cylinder in the transitional regime and the results were validated against available numerical results of other researchers. It was found that the kinetic BGK scheme can similarly predict a tendency of the flow variables in the transitional regime.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.363-370
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• 2008

The present study has been performed to investigate the effect of statistical number of droplets on the simulation of the sprinkler spray using fire field model. In order to simulate the sprinkler spray characteristics, the present study uses NIST Fire Dynamics Simulator version 5.2. A group of Lagrangian particle with similar droplet characteristics, such as diameter, velocity, temperature and so on, is represented by parcel concept to decrease the total number of droplets tracked in the simulation. The present study introduces a new parameter to represent the ratio between real number of droplets and computational parcels. The dependency of the number of parcels on the fire suppression characteristics and spray patterns is quantitatively examined for different ratio between the real number of droplets and computational parcels.