• Journal of Veterinary Clinics
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• v.30 no.4
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• pp.258-263
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• 2013

The primary goal of this study was to compute sample sizes required to achieve the each aim of a variety of foot-and-mouth disease (FMD) surveillance programs, using a statistically valid technique that takes the following factors into account: sensitivity (Se) and specificity (Sp) of diagnostic test system, desired minimum detectable prevalence, precision, population size, and desired power of the survey. In addition, sample sizes to detect FMD if the disease is present and also as proof of freedom were computed. The current FMD active surveillance programs consist of clinical, virological, and serological surveillance. For the 2012 serological surveillance, annual sample sizes (n = 265,065) are planned at four separate levels: statistical (n = 60,884) and targeted (n = 115,232) at breeding pig farms and slaughter house, in together with the detection of structural proteins (SP) antibodies against FMD (n = 88,949). Overall, the sample size was not designed taking the specific aims of each surveillance stream into account. The sample sizes for statistical surveillance, assuming stratified two-stage sampling technique, was based to detect at least one FMD-infected case in the general population. The resulting sample size can be used to obtain evidence of freedom from FMD infection, not for detecting animals that have antibodies against FMD virus non-structural proteins (NSP). Additionally, sample sizes for targeted surveillance were not aimed for the population at risk, and also without consideration of statistical point of view. To at least the author's knowledge, sampling plan for targeted, breeding pig farms and slaughter house is not necessary and need to be included in the part of statistical surveillance. Assuming design prevalence of 10% in an infinite population, a total of 29 animals are required to detect at least one positive with probability of 95%, using perfect diagnostic test system (Se = Sp = 100%). A total of 57,211 animals needed to be sampled to give 95% confidence of estimating SP prevalence of 80% at the individual animal-level with a precision of ${\pm}5%$, assuming 800 herds with an average 200 heads per farm, within-farm variance of 0.2, between-farm variance of 0.05, cost ratio of 100:1 of farm against animals. Furthermore, 779,736 animals were required to demonstrate FMD freedom, and the sample size can further be reduced depending on the parameters assumed.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.603-613
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• 2001

A test based on score statistic is derived for detecting homoscedasticity of errors in unbalanced random effects linear model. A small simulation study is performed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.815-824
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• 2013

Traditional Pearson chi-squared test is not appropriate for the data collected by the complex sample design. When one uses the traditional Pearson chi-squared test to the complex sample categorical data, it may give wrong test results, and the error may occur not only due to the biased variance estimators but also due to the biased point estimators of cell proportions. In this study, the design based consistent Wald test statistics was derived for k-population homogeneity test, and the traditional Pearson chi-squared test statistics was partitioned into three parts according to the causes of error; the error due to the bias of variance estimator, the error due to the bias of cell proportion estimator, and the unseparated error due to the both bias of variance estimator and bias of cell proportion estimator. An analysis was conducted for empirical results of the relative size of each error component to the Pearson chi-squared test statistics. The second year data from the fourth Korean national health and nutrition examination survey (KNHANES, IV-2) was used for the analysis. The empirical results show that the relative size of error from the bias of variance estimator was relatively larger than the size of error from the bias of cell proportion estimator, but its degrees were different variable by variable.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.9
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• pp.828-836
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• 2015

In this paper, the assessment technique for track accuracy in the phased array radar is proposed. It is assumed that ${\alpha}-{\beta}$ tracking filter to track the target is established in the phased array radar. In order to assess the track accuracy strictly, we should use the real target position data acquired from the special instrument, ACMI(Air Combat Maneuvering Instrument) pod or DGPS(Differential Global Positioning System). However, this method leads to increase the experiment cost and test time. We derive the relationship between the residuals of tracking filter and the standard deviations of range and angle tracking errors which are assigned as track assessment index. The theory of sample variance is introduced in this assessment because track accuracy has to be calculated with many residual samples.

• Journal of Pharmaceutical Investigation
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• v.37 no.1
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• pp.27-37
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• 2007

Proficiency test is an essential tool far ensuring analytical ability of analytical chemists and analytical institutes. Usually, the standard protocol for proficiency test is focused on acceptability of reported analytical results of participants by calculating z-scores and related diagnostic parameters. The ultimate goal of this process is to reveal the sources of variability of analytical results and to find the way to reduce their influence. In this study, the method of analysis of variance (ANOVA) was applied to the analytical data collected from qualify control departments of pharmaceutical companies in KyungIn province in Korea in the year of 2000. As influencing factors of variability of analytical results, the use of internal standards for liquid and gas chromatograpy, the educational and professional background of participants, geological locations and yearly production sizes of participating companies were evaluated. To evaluate the variability in accuracy of analytical results, absolute differences from sample mean and sample median were used and to evaluate variability in precision of individual participants, the reported standard deviation of each participant was used. As a result, the use of internal standards in gas chromatographic analysis, participants' academic background and the yearly production sizes of pharmaceutical companies showed statistically significant influence to the accuracy and the precision of the reported analytical results used in this study.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.111-120
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• 2016

In usual, the discontinuous variance function was estimated nonparametrically using a kernel type estimator with data sets split by an estimated location of the change point. Kang et al. (2000) proposed the Gasser-$M{\ddot{u}}ller$ type kernel estimator of the discontinuous regression function using the adjusted observations of response variable by the estimated jump size of the change point in $M{\ddot{u}}ller$ (1992). The adjusted observations might be a random sample coming from a continuous regression function. In this paper, we estimate the variance function using the Nadaraya-Watson kernel type estimator using the adjusted squared residuals by the estimated location of the change point in the discontinuous variance function like Kang et al. (2000) did. The rate of convergence of integrated squared error of the proposed variance estimator is derived and numerical work demonstrates the improved performance of the method over the exist one with simulated examples.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.1035-1046
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• 2015

Variance components models incorporate various random factors in the form of linear models. There are two experimental Layouts for the classification of factors under variance components models: nested classification and crossed classification. We consider two-way variance components models and investigate the effect of experimental Layout on the performance of model selection criteria AIC and BIC. The effect of experimental Layout is studied through a simulation study with various combinations of parameters in a systematic fashion. The simulation study shows differences in performance of model selection methods between the two classification. There is a particular tendency to prefer the smaller model than the true model when the variance component of a nested factor becomes relatively larger than a nesting factor that is persistent even when the sample size is not small.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.387-402
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• 2009

In this paper we have considered the problem of estimating the population mean $\bar{Y}$ of the study variable y using auxiliary information in presence of non-response. Classes of estimators for $\bar{Y}$ in the presence of non-response on the study variable y only and complete response on the auxiliary variable x is available, have been proposed in different situations viz., (i) population mean $\bar{X}$ is known, (ii) when population mean $\bar{X}$ and variance $S^2_x$ are known; (iii) when population mean $\bar{X}$ is not known: and (iv) when both population mean $\bar{X}$ and variance $S^2_x$ are not known: single and two-phase (or double) sampling. It has been shown that various estimators including usual unbiased estimator and the estimators reported by Rao (1986), Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) are members of the proposed classes of estimators. The optimum values of the first phase sample size n', second phase sample size n and the sub sampling fraction 1/k have been obtained for the fixed cost and the fixed precision. To illustrate foregoing, we have carried out an empirical investigation to reflect the relative performance of all the potentially competing estimators including the one due to Hansen and Hurwitz (1946) estimator, Rao (1986) estimator, Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) estimator.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.659-668
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• 2006

The uncertainty of the risk of failure of hydraulic structures can be determined by estimating the variance of the risk of failure based on the methods of moments, probability weighted moments, and maximum likelihood assuming that the underlying model is the Gumbel distribution. In this paper, the variance of the risk of failure was derived. Monte Carlo simulation was peformed to verify the characteristics of the derived formulas for various sample size, design life, nonexceedance probability, and variation coefficient. As the results, PWM showed the smallest relative bias and root mean square error than the others while ML showed the smallest ones for relatively large sample siBes regardless of design life and nonexceedance probability. Also, it was found that variation coefficient does not effect on the relative bias and relative root mean square error.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.167-170
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• 2010

잡음 분산 값은 SNR(signal-to-noise ratio) 추정이나 MMSE(minimum mean square error) 계산, 채널 임펄스 응답의 추정 등에 사용되는 중요한 파라미터이다. 채널이 시간에 따라 변하는 무선 통신 환경에서, 신호와 섞여 있는 잡음과 간섭 신호의 정확한 추정에는 그 한계가 있으며 이로 인해 발생하는 추정 오차는 수신기의 데이터 검출 성능을 저하시킨다. 훈련열을 이용하여 채널을 추정하였을 경우 추정된 채널 임펄스 응답 신호 중 다중 경로 신호는 소수에 불과하고 나머지 대부분의 계수는 잡음 성분만을 포함하는 신호이다. 이러한 특징을 이용하여 채널의 추정 계수로 잡음 분산을 추정하는 방법이 기존에 제시되어 있다. 여기서 제안하는 알고리즘은 기존 알고리즘인 PSA(partial sample average)와 비교해 연산량에서 차이가 거의 없이 구현되며, 3GPP TDD[1]에서의 모의 실험을 통하여 기존 알고리즘보다 더 정확한 분산 값을 찾아냄을 확인하였다.