• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.71-77
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• 1997

S independent sample 0,1,2, $\cdots$, s-1 (or stages 0,1,2, $\cdots$, s-1) are available from the Raleigh population. Procedure for predicting any order statistic in the $(s+1)^{th}$ sample is developed by obtaining the predictive distribution at stage s. Bounds for the sample size at stage S, in order to have the variance at stage S less than that at stage (s-1), are obtained.

• Journal of Ecology and Environment
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• v.31 no.1
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• pp.83-87
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• 2008

The small-scale dynamic of moth populations in spring was examined in a coniferous forest of southwestern Korea. Moths were collected with one 22-watt light trap for 29 days in April 2007. A total of 450 individuals of 38 species in 5 families were collected. The most abundant species was an epiplemid moth, Epiplema plagifera. The relationship between these dominant moths and their host plants is briefly discussed. We also examined influence of weather factors on the number of species and individuals collected. Multiple regression analyses showed that the two-day temperature difference explained 18% of the variance in the number of species collected, while air and ground temperatures explained 51% of the variance in the log-transformed number of individuals collected. This suggests that temperature affects local population sizes in spring, but variables other than weather may also affect the diversity of local moth populations.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.12
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• pp.1686-1689
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• 2002

Genetic gains and inbreeding coefficients in a Holstein MOET breeding population were predicted under different conditions relating to the distribution of the number of transferable embryos collected per flush using Monte Carlo simulation. The numbers of transferable embryos collected per flush were determined using five distributions (distributions 1, 3, 5, 7 and 9) with different aspects and similar means. Distributions 1, 3, 5, 7 and 9 were assumed to have gamma distribution's parameters ($\alpha$ and $\beta$) of (1 and 4.4), (3 and 1.47), (5 and 0.88), (7 and 0.63) and (9 and 0.49), respectively. Inbreeding rates were statistically significantly different among distributions but genetic gains were not. Relationships between inbreeding rates and variances of family size could be were clearly distinguished. The highest inbreeding coefficients were predicted in distribution 1 with the largest variance of family size, while distributions 5, 7 and 9 with smaller variance of family size had lower inbreeding coefficients.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.417-429
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• 1998

This paper compares powers of the two nonparametric tests under a variety of population distributions through a simulation study. Both tests require that the two underlying populations have the same variance, but this assumption is relaxed in some of the comparisons.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.407-417
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• 1995

The h-plot is a graphical technique for displaying the structure of one population's variance-covariance matrix. This follows the mathematical algorithem of the principle component biplot based on the singular value decomposition. But it is known that the singular value decomposition is not resistant, i.e., it is very sensitive to small changes in the input data. In this article, since the mathematical algorithm of the h-plot is equivalent to that of principal component biplot of Choi and Huh (1994), we derive the resistant h-plot.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.23-32
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• 2012

This paper deals with the bias and variance of regression coefficient estimators in a finite population. We derive approximate formulas for the bias, variance and mean square error of two estimators when we select a fixed-size inclusion probability proportional to the size sample and then estimate regression coefficients by the ordinary least square estimator as well as the weighted least square estimator based on the selected sample data. Necessary and sufficient conditions for the comparison of the two estimators in terms of variance and mean square error are suggested. In addition, a simple example is introduced to numerically compare the variance and mean square error of the two estimators.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.3
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• pp.115-126
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• 2023

Understanding the carrying capacity of a habitat is crucial for effectively managing populations of wild boars (Sus scrofa), which are designated as harmful wild animal species in national parks. Carrying capacity refers to the maximum population size supported by a park's environmental conditions. This study aimed to estimate the appropriate wild boar population size by integrating population characteristics and habitat suitability for wild boars in the Bukhansan National Park using the HexSim program. Population characteristics included age, survival, reproduction, and movement. Habitat suitability, which reflects prospecting and resource acquisition, was determined using the Maximum Entropy model. This study found that the optimal population size for wild boar ranged from 217 to 254 individuals. The population size varied depending on the amount of resources available within the home range, indicating fewer individuals in a larger home range. The estimated wild boar population size was 217 individuals for the minimum amount of resources (50% minimum convex polygon [MCP] home range), 225 individuals for the average amount of resources (95% MCP home range), and 254 individuals for the maximum amount of resources (100% MCP home range). The results of one-way analysis of variance revealed a significant difference in wild boar population size based on the amount of resources within the home range. These findings provide a basis for the development and implementation of effective management strategies for wild boar populations.