• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.147-156
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• 2002

In this paper, we study the properties of the modified winsorized mean to estimate the mean of a two-truncation parameter population. Under some mild conditions, the estimator is found to be strongly consistent and asymptotically unbiased even though the sample is doubly type II censored.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.851-859
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• 2006

The family income distributions of NLSY97 and CPS youth data are compared by using the generalized beta distribution of the second kind. The null hypothesis that the two data sets represent the same underlying population is rejected. The ML estimation suggests that NLSY97 data are oversampled in an income group of $11,308 or less, by about 15.7% compared to CPS data.

• Bulletin of the Korean Mathematical Society
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• v.53 no.2
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• pp.351-363
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• 2016

In this paper, we consider the entropy-based goodness of fit test (Vasicek's test) for a composite hypothesis. The test measures the discrepancy between the nonparametric entropy estimate and the parametric entropy estimate obtained from an assumed parametric family of distributions. It is shown that the proposed test is asymptotically normal under regularity conditions, but is affected by parameter estimates. As a remedy, a bootstrap version of Vasicek's test is proposed. Simulation results are provided for illustration.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.531-542
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• 2015

In this survey, we use the normal linear model to demonstrate the use of the linear Bayes method. The superiorities of linear Bayes estimator (LBE) over the classical UMVUE and MLE are established in terms of the mean squared error matrix (MSEM) criterion. Compared with the usual Bayes estimator (obtained by the MCMC method) the proposed LBE is simple and easy to use with numerical results presented to illustrate its performance. We also examine the applications of linear Bayes method to some other distributions including two-parameter exponential family, uniform distribution and inverse Gaussian distribution, and finally make some remarks.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.603-613
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• 2011

Exponentiated distribution has been used in reliability and survival analysis especially when the data is censored. In this paper, we derive Bayesian estimation of the shape parameter, reliability function and failure rate function in the exponentiated distribution family based on Type-II right censored data. We here consider conjugate prior and noninformative prior and corresponding posterior distributions are obtained. As an illustration, the mean square errors of the estimates are computed. Comparisons are made between these estimators using Monte Carlo simulation study.

• Journal of Korean Society for Quality Management
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• v.14 no.2
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• pp.47-54
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• 1986

A different kind of approximation has been developed in connection with calculation of the normal family distributions in digital computer. These approximations usually employ polynomial expressions. They give quite high accuracy, sometimes only within definite limits on the values of the variable. Outside these limits they may give quite poor approximations. In this paper we compare these approximations by criteria of C.P.U. time and accuracy using micro computer. Approximation formulas given by Zelen and Severo (1984) are proven to give the most accurate results within allowable C.P.U. time.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.641-653
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• 2022

Penalized least squares methods are important tools to simultaneously select variables and estimate parameters in linear regression. The penalized maximum likelihood can also be used for the same purpose assuming that the error distribution falls in a certain parametric family of distributions. However, the use of a certain parametric family can suffer a misspecification problem which undermines the estimation accuracy. To give sufficient flexibility to the error distribution, we propose to use the symmetric log-concave error distribution with LASSO penalty. A feasible algorithm to estimate both nonparametric and parametric components in the proposed model is provided. Some numerical studies are also presented showing that the proposed method produces more efficient estimators than some existing methods with similar variable selection performance.

• Genomics & Informatics
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• v.20 no.2
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• pp.19.1-19.15
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• 2022

Alfalfa (Medicago sativa) is an important food and feed crop which rich in mineral sources. The WUSCHEL-related homeobox (WOX) gene family plays important roles in plant development and identification of putative gene families, their structure, and potential functions is a primary step for not only understanding the genetic mechanisms behind various biological process but also for genetic improvement. A variety of computational tools, including MAFFT, HMMER, hidden Markov models, Pfam, SMART, MEGA, ProtTest, BLASTn, and BRAD, among others, were used. We identified 34 MsWOX genes based on a systematic analysis of the alfalfa plant genome spread in eight chromosomes. This is an expansion of the gene family which we attribute to observed chromosomal duplications. Sequence alignment analysis revealed 61 conserved proteins containing a homeodomain. Phylogenetic study sung reveal five evolutionary clades with 15 motif distributions. Gene structure analysis reveals various exon, intron, and untranslated structures which are consistent in genes from similar clades. Functional analysis prediction of promoter regions reveals various transcription binding sites containing key growth, development, and stress-responsive transcription factor families such as MYB, ERF, AP2, and NAC which are spread across the genes. Most of the genes are predicted to be in the nucleus. Also, there are duplication events in some genes which explain the expansion of the family. The present research provides a clue on the potential roles of MsWOX family genes that will be useful for further understanding their functional roles in alfalfa plants.

• Health Policy and Management
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• v.21 no.1
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• pp.93-114
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• 2011

This study was conducted to identify college students' supportive attitude toward the elderly and their awareness of the socialization of care for the elderly, since they will have the responsibility for and the support of the aged society in the near future. This study was also conducted to analyze the factors which affect the socialization of elderly care, and to contribute to building a care system which promotes ahealthy and happy lifestyle for the elderly. After conducting a survey of 1,100 students from13 universities around the entire country, I have analyzed 1,089 data forms, and omitted 11 data entries which had errors or were not answered. 1. Those surveyed are 1,089 students from 13 universities around the entire country. Regional distributions are as follows : 263 students from 4 universities in Daegu and Kyongsangbuk Do(24.2%), 291 students from 3 universities in Busan and Kyongsangnam Do(26.7%), 272 students from 2 universities in Jeolla Do(25.0%), 263 students from 4 universities in Seoul and Gyeonggi Do. Males are 51.7% and females are 48.3% of these students. 2. Instrumental supportive sense level is high in men and emotional supportive sense level is higher in women. Also emotional supportive sense is higher in groups of those having more family members and coming from agricultural regions. 3. The sense of living with aged parents is higher in those living with grandparents than those living separate. The sense of living with sons and daughters after aging is stronger in the students from the Science and Engineering Departments than in the Social and Human Sciences Departments; also higher for men than women. 4. Recognition of elderly care socialization is higher in those from Social and Human Sciences Departments than from Science and Engineering Departments; higher in the case of upper classmenand aged groups, groups having fewer family members than more family members, and in the case of living separated from grandparents. 5. The factors affecting the sense of living with grandparents were family cohesion and instrumental supportive sense. The factors affecting the sense of elderly care socialization were family cohesion, instrumental supportive sense, and emotional supportive sense. From the results it is concluded that to insure a healthy and happy lifestyle for aged people, elderly care socialization offered by society and the country must provide desirable, appropriate care services based on the centralized support system of the family. In order to do this, we propose that elderly care needs inter-family and inter-generational fusion programs to improve family cohesion and care recognition. Also, elderly care is in urgent need to build a strong Family and Health Welfare System for care socialization.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8221-8226
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• 2016

Background: Misreporting self-reported family history may lead to biased estimations. We used Bayesian methods to adjust for exposure misclassification. Materials and Methods: A hospital-based case-control study was used to identify breast cancer risk factors among Iranian women. Three models were jointly considered; an outcome, an exposure and a measurement model. All models were fitted using Bayesian methods, run to achieve convergence. Results: Bayesian analysis in the model without misclassification showed that the odds ratios for the relationship between breast cancer and a family history in different prior distributions were 2.98 (95% CRI: 2.41, 3.71), 2.57 (95% CRI: 1.95, 3.41) and 2.53 (95% CRI: 1.93, 3.31). In the misclassified model, adjusted odds ratios for misclassification in the different situations were 2.64 (95% CRI: 2.02, 3.47), 2.64 (95% CRI: 2.02, 3.46), 1.60 (95% CRI: 1.07, 2.38), 1.61 (95% CRI: 1.07, 2.40), 1.57 (95% CRI: 1.05, 2.35), 1.58 (95% CRI: 1.06, 2.34) and 1.57 (95% CRI: 1.06, 2.33). Conclusions: It was concluded that self-reported family history may be misclassified in different scenarios. Due to the lack of validation studies in Iran, more attention to this matter in future research is suggested, especially while obtaining results in accordance with sensitivity and specificity values.