• Tunnel and Underground Space
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• v.12 no.1
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• pp.19-30
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• 2002

Rock joint orientation is one of important geometric attributes that have an influence on the stability of rock structures such as rock slopes and tunnels. Especially, statistical models of the geometric attributes of rock joints can provide a probabilistic approach of rock engineering problems. The result from probabilistic modeling relies on the choice of statistical model. Therefore, it is critical to define a representative statistical model for joint orientation data as well as joint size and intensity and build up a series of modeling procedure including analytical validation. In this paper, we have examined a theoretical methodology for the statistical estimate and hypothesis analysis based upon Fisher distribution and bivariate normal distribution. In addition, we have proposed the algorithms of random number generator which is applied to the simulation of rock joint networks and risk analysis.

• Korean Journal of Child Studies
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• v.11 no.1
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• pp.87-99
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• 1990

The present study was designed to investigate the effect of altruistic TV viewing and verbal training on the altruistic behavior of preschoolers. The subjects of this study were a total of 56 boys and 57 girls from a kindergarten in Kwachon, Kyung-gi do. The subjects were assigned to one of three conditions: in the first condition subjects were shown video tapes designed to portray prosocial themes (TV modeling group) ; in the second condition subjects saw the video tapes in addition to verbal training (TV modeling plus verbal training group); in the third condition subjects received neither TV modeling nor verbal training (control group). Statistical analysis was by ANOVA and $Scherr\acute{e}$ test. Significant differences were found in altruistic behavior between the TV modeling and the TV modeling with verbal training groups.

• Knowledge Management Research
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• v.20 no.1
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• pp.1-26
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. For this, we present the whole process of analyzing the structural equations model from the confirmatory factor analysis to the path diagram generation using the lavaan package, which is relatively well evaluated among the R packages supporting the structural equation modeling, together with the R program codes. Considering that research applying structural equation modeling techniques is the mainstream in a variety of social sciences, including business administration, and that there is growing interest in open source R, this tutorial focuses on researchers who are looking for alternatives to traditional commercial statistical packages and is expected that it will be a useful guidebook for them.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• Computers and Concrete
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• v.15 no.6
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• pp.989-999
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• 2015

An advanced continuum-based multi-physical single particle model was recently introduce for the hydration of tricalcium silicate ($C_3S$). In this model, the dissolution and the precipitation events are modeled as two different yet simultaneous chemical reactions. Product precipitation involves a nucleation and growth mechanism wherein nucleation is assumed to happen only at the surface of the unreacted core and product growth is characterized via a two-step densification mechanism having rapid growth of a low density initial product followed by slow densification. Although this modeling strategy has been shown to nicely mimic all stages of $C_3S$ hydration - dissolution, dormancy (induction), the onset of rapid hydration, the transition to slow hydration and prolonged reaction - the major criticism is that many adjustable parameters are required. If formulated correctly, however, the model parameters are shown here to be statistically independent and significant.

• Computers and Concrete
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• v.21 no.2
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• pp.111-116
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• 2018

Establishment of test methods to assess the fresh properties of self-compacting concrete (SCC) are required to ensure the homogeneity in fresh and hardened states. This paper discusses the suitability of a simple test method for assessing the slump flow and stability of SCC by testing on self-compacting mortar (SCM) fraction. The proposed test method aims at investigating slump flow diameter test and sieve stability test of SCC by testing SCM fraction with a plunger penetration apparatus. A central composite modeling design was performed to evaluate the effects of water/cement ratio (W/C), superplasticizer dosage (SP) and powder marble content (MP) on slump flow diameter, stability and plunger penetration test of fresh SCC. The responses of the derived statistical models are slump flow (Sf), sieve stability (S) and plunger penetration (P). Relationships obtained in this study show acceptable correlations between plunger penetration test value and slump flow diameter test results and stability. It should note that the developed relationships are very useful to predict slump flow diameter and stability of studied SCC mixtures by carrying out a simple plunger penetration test on its mortar, which can save labour and time in laboratory experiments.

• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.409-417
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• 2006

This article is concerned with threshold modeling of the bifurcating autoregressive model (BAR) originally suggested by Cowan and Staudte (1986) for tree structured data of cell lineage study where each individual $(X_t)$ gives rise to two off-spring $(X_{2t},\;X_{2t+1})$ in the next generation. The triplet $(X_t,\;X_{2t},\;X_{2t+1})$ refers to mother-daughter relationship. In this paper we propose a threshold model incorporating the difference of 'fertility' of the mother for the first and second off-springs, and thereby extending BAR to threshold-BAR (TBAR, for short). We derive a sufficient condition of stationarity for the suggested TBAR model. Also various inferential methods such as least squares (LS), maximum likelihood (ML) and quasi-likelihood (QL) methods are discussed and relevant limiting distributions are obtained.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.371-387
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• 1999

For possibly nonstationary autoregressive moving average, modeling based on the original observations rather than the differenced observations is considered. Under this scheme, sample autocorrelation functions, parameter estimates, model diagnostic statistics, and prediction are all computed from the original data instead of the differenced data. The methods and results established under stationarity of data are shown to naturally extend to the nonstationarity of one autoregressive unit root. The sample ACF and PACF can be used for ARMA order determination. The BIC order is strongly consistent. The parameter estimates are asymptotically normal. The portmanteau statistic has chi-square distribution. The predictor is asymptotically equivalent to that based on the differenced data.

• 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.