• Asian-Australasian Journal of Animal Sciences
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• v.21 no.6
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• pp.784-788
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• 2008

Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.

• Asia-Pacific Journal of Business
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• v.6 no.2
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• pp.1-17
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• 2015

This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.733-745
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• 2017

Local composite quantile regression is a useful non-parametric regression method widely used for its high efficiency. Data smoothing methods using kernel are typically used in the estimation process with performances that rely largely on the smoothing parameter rather than the kernel. However, $L_2$-norm is generally used as criterion to estimate the performance of the regression function. In addition, many studies have been conducted on the selection of smoothing parameters that minimize mean square error (MSE) or mean integrated square error (MISE). In this paper, we explored the optimality of selecting smoothing parameters that determine the performance of non-parametric regression models using local linear composite quantile regression. As evaluation criteria for the choice of smoothing parameter, we used mean absolute error (MAE) and mean integrated absolute error (MIAE), which have not been researched extensively due to mathematical difficulties. We proved the uniqueness of the optimal smoothing parameter based on MAE and MIAE. Furthermore, we compared the optimal smoothing parameter based on the proposed criteria (MAE and MIAE) with existing criteria (MSE and MISE). In this process, the properties of the proposed method were investigated through simulation studies in various situations.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.923-932
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• 2008

We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.

• Korean Journal of Acupuncture
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• v.30 no.1
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• pp.1-8
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• 2013

Objectives : The purpose of the present study was to examine statistical methods used in articles published on the Korean Journal of Acupuncture from 2007 through 2012. Methods : Statistical methods and statistical packages used in original articles applied with descriptive statistics or inferential statistics were organized. Results : Out of a total of 195 original articles, 18 articles used descriptive statistics only and 177 articles used inferential statistics. 142 articles used 12 types of statistical packages. SPSS was used most at 97 times(63.4%). The number of descriptive statistical methods used was a total of 417 and among them 193 were presented as tables(46.3%) and 224 were presented as graphs(53.7%). The number of inferential statistics applied was a total of 256 and analysis of variance was used most at 90 times(35.2%). The number of parametric statistical methods used was a total of 170(75.6%) and that of nonparametric statistical methods used was a total of 55(24.4%). Analysis of variance and two sample t-test were most employed in both clinical and non-clinical research. The number of multiple comparison methods applied was a total of 67 and the number of Scheffe methods among them was most at 26 times(37.7%). Conclusions : In the present study, statistical methods used in the journal over the last six years were examined. The result of this study is considered to be a basic material to be referred to when evaluating the quality of the medical journal.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.439-447
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• 2021

Due to the frequent emergence of global abnormal climates, related studies on meteorological change is being actively proceed. However, the research on trend analysis using weather data accumulated over a long period of time was insufficient. In this study, the trend of temperature time series data accumulated from automated surface observing system (ASOS) for 40 years was analyzed by using a non-parametric analysis method. As a result of the Mann-Kendall test on the annual average temperature and seasonal average temperature time series data in South Korea, it has shown that an upward trend exists. In addition, the result of calculating the Sen's slope, which can determine the degree of tendency before and after the searched change point by applying the Pettitt test, recent data after the fluctuation point confirmed that the tendency of temperature rise was even greater.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.283-287
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• 2010

Stochastic simulation of hydrologic data has been widely developed for several decades. However, despite the several advances made in literature still a number of limitations and problems remain. In the current study, some stochastic simulation approaches tackling some of the existing problems are discussed. The presented models are based on nonparametric techniques such as block bootstrapping, and K-nearest neighbor resampling (KNNR), and kernel density estimate (KDE). Three different types of the presented stochastic simulation models are (1) Pilot Gamma Kernel estimate with KNNR (a single site case) and (2) Enhanced Nonparametric Disaggregation with Genetic Algorithm (a disaggregation case). We applied these models to one of the most challenging and critical river basins in USA, the Colorado River. These models are embedded into the hydrological software package, Pros and cons of the models compared with existing models are presented through basic statistics and drought and storage-related statistics.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.1
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• pp.105-111
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• 2010

In the field of 'Human Vibration', it has been interested subjects to make equal sensation curves related to translational and rotational direction of whole-body, hand-transmitted and head-transmitted vibration, etc. When we consider the vibration of a vehicle, the main factor is vertical whole-body vibration. Until now, most of equal sensation curves used to derive frequency weighting function had been made using Western people. However, because of the inherent differences (for example, characteristic and shape of body parts, muscular and cellular tissue) between the Western people and the Oriental people, equal sensation curves based on Oriental people might be required. Also, the weight differences between the samples which consist of average-weighted and over-weighted group might cause the difference of equal sensation curves. So, in this study, 20 male Korean people were used to find equal sensation curves subject to vertical whole-body vibration on seated posture. Among 20 males, an over weighted group consisted of 10 male persons and an average weighted group was the others. Integrating and analyzing the data of two groups, some of non-parametric tests such as 'The Wilcoxon Signed Rank Test' and 'The Mann Whitney U test' were used.

• The Journal of Korean Academy of Prosthodontics
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• v.40 no.2
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• pp.131-139
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• 2002

There have been many studies about marginal discrepancy of single restorations made by various systems and materials. But many of statistical inferences are not definite because of sample size, measurement number, measuring instruments. etc. The purpose of this study was to compare the marginal adaptations of the anterior single restorations made by different systems and to consider more desirable statistical methods in analysing the marginal fit. The in vitro marginal discrepancies of three different all-ceramic crown systems (Celay In-Ceram. Conventional In-Ceram. IPS Empress 2 layering technique) and one control group (PFM) were evaluated and compared. The crowns were made from one extracted maxillary central incisor prepared with a 1mm shoulder margin and $6^{\circ}$ taper walls by milling machine. 10 crowns per each system were fabricated. Measurements or a crown were recorded at 50 points that were randomly selected for marginal gap evaluation. Non-parametric statistical analysis was performed for the results. Within the limits of this study, the following conclusions were drawn: 1 Mean gap dimensions and standard deviations at the marginal opening for the maxillary incisor crowns were $98.2{\pm}40.6{\mu}m$ for PFM, $83.5{\pm}18.7{\mu}m$ for Celay In-Ceram, $104.9{\pm}44.1{\mu}m$ for conventional In-Ceram, and $45.5{\pm}11.5{\mu}m$ for IPS Empress 2 layering technique. The IPS Empress 2 system showed the smallest marginal gap (P<0.05). The marginal openings of the other three groups were not significantly different (P<0.05). 2 The marginal discrepancies found in this study were all within clinically acceptable standards ($100\sim150{\mu}m$). 3. When the variable is so controlled that the system may be the only one, mean value is interpreted to be the marginal discrepancy of a restoration which is made by each system and standard deviation is to be technique-sensitivity of each one. 4. From the standard deviations. the copy-milling technique (Celay/In-Ceram) was not considered to be technique-sensitive in comparison with other methods. 5. Parametric analysis is more reliable than non-parametric one in interpretation of the mean and standard deviation. The sample size of each group has to be more than 30 to use parametric statistics. The level of clinically acceptable marginal fit has not been established. Further studies are needed.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.355-364
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• 2009

A simple method is proposed for constructing nonparametric confidence intervals for the difference or ratio of two median failure times. The method applies when clustered survival data with censoring is randomized either (I) under cluster randomization or (II) subunit randomization. This method is simple to calculate and is based on non-parametric density estimation. The proposed method is illustrated with the otology study data and HL-A antigen study data. Moreover, the simulation results are reported for practical sample sizes.