• KOREAN POULTRY JOURNAL
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• v.19 no.10 s.216
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• pp.160-160
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• 1987

• KOREAN POULTRY JOURNAL
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• v.19 no.12 s.218
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• pp.164-165
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• 1987

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.405-414
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• 2012

In a stratified sample, the sampling frame is divided into non-overlapping groups or strata (e.g. geographical areas, age-groups, and genders). A sample is taken from each stratum, if this sample is a simple random sample it is referred to as stratified random sampling. In this paper, we study the bootstrap inference (including confidence interval) and test for a stratified population mean. We also introduce the bootstrap consistency based on limiting distribution related to the plug-in estimator of the population mean. We suggest three bootstrap confidence intervals such as standard bootstrap method, percentile bootstrap method and studentized bootstrap method. We also suggest a bootstrap test method computing the $ASL_{boot}$(Achieved Significance Level). The results of estimation are verified using simulation.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.327-334
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• 2013

Purpose: The purpose of this study was to analyze for resonant frequency, vibration transmissibility and damping ratio of multi-layered corrugated structures using a random vibration test. Methods: The random vibration test was performed by the ASTM D4728 specifications using two paperboards (S120, K180) and two types of flutes (A/F, B/F). Damping ratio of the multi-layered corrugated structures was estimated using a theoretical equation derived from the measured resonant frequency and transmissibility. Results: The resonant frequency and vibration transmissibility of the multi-layered corrugated structures of K180 and B-flute were higher than those of S120 and A-flute, respectively; however, the damping ratio of each sample had the opposite tendency. The resonant frequency was inversely proportional to the sample thickness and static stress; vibration transmissibility and damping ratio were not correlated with sample thickness and static stress. In addition, we developed a mathematical model of the resonant frequency with variables of sample thickness and static stress. Conclusions: Results of this study can be useful for environment-friendly and optimal packaging design since vibration has been a key factor in cushioning packaging design.

• The Journal of Bigdata
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• v.2 no.2
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• pp.95-104
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• 2017

In 2014, Seoul Metropolitan Government launched a response service aimed at responding promptly to civil complaints. The complaints received are categorized based on their content and sent to the department in charge. If this part can be automated, the time and labor costs will be reduced. In this study, we collected 17,700 cases of complaints for 7 years from June 1, 2010 to May 31, 2017. We compared the XGBoost with RandomForest and confirmed the suitability of Korean text classification. As a result, the accuracy of XGBoost compared to RandomForest is generally high. The accuracy of RandomForest was unstable after upsampling and downsampling using the same sample, while XGBoost showed stable overall accuracy.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.41-49
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• 2024

In recent years, China's high-speed railway (HSR) line continues to expand into seismically active regions. Analyzing the features of earthquake rail irregularity is crucial in this situation. This study first established and experimentally validated a finite element (FE) model of bridge-track. The FE model was then combined with earthquake record database to generate the earthquake rail irregularity library. The sample library was used to construct a model of desired earthquake rail irregularity based on signal processing (SFT) and hypothesis principle. Finally, the effects of random pier height and random span number on desired irregularity were analyzed. Herein, an equivalent method of calculating earthquake rail irregularities for random structures was proposed. The results of this study show that the amplitude of desired irregularity is found to increase with increasing pier height. When calculating the desired irregularity of a structure with unequal pier heights, the structure can be regarded as that with equal pier heights (taking the largest pier height). For a structure with the span number large than 9, its desired irregularity can be considered equal to that of a 9-span structure. For the structures with both random pier heights and random span number, their desired irregularities are obtained by equivalent calculations for pier height and span number, respectively.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.11-18
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• 1994

Sample sizes for experiments concerned with inference on R=Pr(X

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.397-405
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• 1998

We develop parametric bootstrap model selection criteria in an example to fit a random sample to either a general normal distribution or a normal distribution with prespecified mean. We apply the bootstrap methods in two ways; one considers the direct substitution of estimated parameter for the unknown parameter, and the other focuses on the bias correction. These bootstrap model selection criteria are compared with AIC. We illustrate that all the selection rules reduce to the one sample t-test, where the cutoff points converge to some certain points as the sample size increases.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.169-185
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• 2000

Given a random sample of size N (unknown) with density f(x│$\theta$), suppose that only n observations which lie outside a region r are recorded. On the basis of n observation, the Bayes estimators of $\theta$ and N are considered and their asymptotic expansions are developed to find the third order asymptotic properties with those of the maximum likelihood estimators and the Bayes modal estimators. The asymptotic m.s.e.'s of these estimators are expressed. An example is given to illustrate the results obtained.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.193-198
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• 1999

The estimation of parameters in regression models with multiplicative errors is usually based on the gamma or log-normal likelihoods. Under reciprocal misspecification, we compare the small sample efficiencies of two sets of estimators via a Monte Carlo study. We further consider the case where the errors are a random sample from a Weibull distribution. We compute the asymptotic relative efficiency of quasi-likelihood estimators on the original scale to least squares estimators on the log-transformed scale and perform a Monte Carlo study to compare the small sample performances of quasi-likelihood and least squares estimators.