• Communications for Statistical Applications and Methods
• /
• v.25 no.1
• /
• pp.15-27
• /
• 2018

Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

• Communications for Statistical Applications and Methods
• /
• v.26 no.5
• /
• pp.445-461
• /
• 2019

It is possible that data are not always fitted with sufficient precision by the existing distributions; therefore this article presents a methodology that enables the use of families of asymmetric distributions as alternative probabilistic models for survival analysis, with censorship on the right, different from those usually studied (the Exponential, Gamma, Weibull, and Lognormal distributions). We use a more flexible parametric model in terms of density behavior, assuming that data can be fit by a distribution of stable distribution families considered unconventional in the analyses of survival data that are appropriate when extreme values occur, with small probabilities that should not be ignored. In the methodology, the determination of the analytical expression of the risk function h(t) of the $L{\acute{e}}vy$ distribution is included, as it is not usually reported in the literature. A simulation was conducted to evaluate the performance of the candidate distribution when modeling survival times, including the estimation of parameters via the maximum likelihood method, survival function ${\hat{S}}$(t) and Kaplan-Meier estimator. The obtained estimates did not exhibit significant changes for different sample sizes and censorship fractions in the sample. To illustrate the usefulness of the proposed methodology, an application with real data, regarding the survival times of patients with colon cancer, was considered.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.5
• /
• pp.1017-1025
• /
• 2012

We consider estimations for the reliability in two independent variables with Pareto and uniform or exponential distributions. And then we compare the mean squared errors of two reliability estimators for each case. We also observe the skewness of densities of the ratio for each case.

• Communications for Statistical Applications and Methods
• /
• v.15 no.5
• /
• pp.775-781
• /
• 2008

It is developed that a family of the semicircular Laplace distributions for modeling semicircular data by simple projection method. Mathematically it is simple to simulate observations from a semicircular Laplace distribution. We extend it to the l-axial Laplace distribution by a simple transformation for modeling any arc of arbitrary length. Similarly we develop the l-axial log-Laplace distribution based on the log-Laplace distribution. A bivariate version of l-axial Laplace distribution is also developed.

• 한국데이터정보과학회:학술대회논문집
• /
• 2003.10a
• /
• pp.49-56
• /
• 2003

When X and Y have independent normal distributions, we develop a Bayesian testing procedure for the equality of two coefficients of variation. Under the reference prior of the coefficient of variation, we propose a Bayesian test procedure for the equality of two coefficients of variation using fractional Bayes factor. A real data example is provided.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.1
• /
• pp.119-127
• /
• 1996

The concepy of positive aging describles the adverse effects of age on the lifetime of units. Various aspects of this concepts are described in terms of conditional probability distribution of residual life times, failure rates, equilibrium distributions, etc. In this paper we will consider some partial ordering relations of life distribution under residual life functions and equilibrium distributions.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.1
• /
• pp.87-92
• /
• 1996

A regression model with nested erroe structure is considered. The regression model includes two error terms that are independent and normally distributed with zero means and constant variances. This error structure of the model gives correlated response variables. The distributions of variance components in the regression model with nested error structure are dervied by using theorems for quadratic forms.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.317-328
• /
• 2002

We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

• Journal of applied mathematics & informatics
• /
• v.2 no.1
• /
• pp.25-32
• /
• 1995

Due to the complexity of many of the existing statistical problems found in working with envirommental copmuter simulations (Monte Carlo)have proved to be very informative. However, due to the various types of environmental data(thus the different type of distributions) one can no longer perform simulations based solely upon normal data. So in anticipating this problem, this paper outlines the computer software to generate variates from the various specified dis-tributions.

• Journal of the Korea Safety Management & Science
• /
• v.17 no.1
• /
• pp.169-177
• /
• 2015

We develop a model to predict typhoons in Korea. We collect data for typhoons and classify those depending on the severity level. Following a Bayesian approach, we develop a model that explains the relationship between different levels of typhoons. Through the analysis of the model, we can predict the rate of typhoons, the probability of approaching Korean peninsular, and the probability of striking Korean peninsular. We show that the uncertainty for the occurrence of various types of typhoons reduces dramatically by adaptively updating model parameters as we acquire data.