• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.5
• /
• pp.541-547
• /
• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.

• Communications for Statistical Applications and Methods
• /
• v.9 no.2
• /
• pp.479-489
• /
• 2002

The case which applies two-phase sampling to stratification and nonresponse problem, it is a poweful and effective technique. In this paper we study the calibration estimator and its variance estimator for the population total using two-phase sampling method according to the of auxiliary information for population and sample having strong correlation with an interested variable in unit nonresponse situation. The auxiliary information that available both at first-phase and second-phase sampling can be used to improve weights by the calibration procedure. A weight which corresponds to the product of sampling weights and response probability is calculated at each phase of sampling.

• Communications for Statistical Applications and Methods
• /
• v.9 no.2
• /
• pp.305-313
• /
• 2002

Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.

• Journal of Applied Reliability
• /
• v.18 no.2
• /
• pp.122-129
• /
• 2018

Purpose: This article develops an optimal reliability acceptance sampling plan for the case where the degradation quantity of the performance characteristic follows Weibull distribution. Method: For developing reliability acceptance sampling plans, the sample size and the acceptance constant are determined based on the accelerated characteristic of the test condition and the product. Results: The sample size and the acceptance constant are provided such that the constraints of the producer and the consumer risks are satisfied. Conclusion: Reliability acceptance sampling plans based on the accelerated degradation test method can be used for the quality control within a resonable amount of cost and time. In this article. an optimal reliability sampling plans are newly developed for this purpose.

• Research in Plant Disease
• /
• v.21 no.4
• /
• pp.268-272
• /
• 2015

Bacterial leaf blight caused by Pseudomonas syringae pv. porri is one of the major bacterial diseases of garlic (Allium sativum). In South Korea, the disease has only been observed in garlic-growing regions of Jeju island. The spatial distribution pattern of the disease was analyzed by binary power law, in which the natural logarithm of the observed variance is regressed on the natural logarithm of the binomial variance. The estimated slope (b=1.361) of the regression was greater than 1 which meant that the diseased plants were aggregated. The sequential sampling plans were developed for estimating the mean incidence rate ($p_m$) and classifying the mean incidence as being below or above the critical incidence rate ($p_t$). These results could be used on more efficient and higher precisive sampling for bacterial blight of garlic compared to fixed sample sized sampling.

• Survey Research
• /
• v.6 no.2
• /
• pp.1-32
• /
• 2005

The accuracy of exit poll mainly depends on the sampling method of voting places. For exit poll, we propose a probability sampling method of selecting voting places as an alternative to the bellwether polling place sampling. Through an empirical study based on the 2004 general election data, the efficiency of the suggested systematic sampling from ordered voting places was evaluated in terms of mean prediction error and it turns out that the proposed sampling method outperformed the bellwether polling places sampling. We also calculated the variance of estimator from the proposed sampling, and considered the sample size problem to guarantee the target precision using the design effect of the proposed sample design.

• Asian-Australasian Journal of Animal Sciences
• /
• v.13 no.3
• /
• pp.413-422
• /
• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Communications for Statistical Applications and Methods
• /
• v.12 no.2
• /
• pp.365-379
• /
• 2005

Balanced Repeated Replication(BRR) is widely used to estimate the variance of linear or nonlinear estimators from complex sampling surveys. Most of survey data sets include imputed missing values and treat the imputed values as observed data. But applying the standard BRR variance estimation formula for imputed data does not produce valid variance estimators. Shao, Chen and Chen(1998) proposed an adjusted BRR method by adjusting the imputed data to produce more accurate variance estimators. In this paper, another adjusted BRR method is proposed with examples of real data.

• Journal of the Korean Statistical Society
• /
• v.29 no.1
• /
• pp.45-62
• /
• 2000

Rotation design is a sampling technique to reduce response burden and to estimate the population characteristics varying in time. Park and Kim(1999) discussed a generation of one-level rotation design which is called as {{{{r_1^m ~-r_2^m-1}}}} design has more applicable form than existing before. In the structure of {{{{r_1^m ~-r_2^m-1}}}} design, we derive the exact variances of generalized composite estimators for level, change and aggregate level characteristics of interest, and optimal coefficients minimizing their variances. Finally numerical examples are shown by the efficiency of alternative designs relative to widely used 4-8-4 rotation design. This is continuous work of Part Ⅰ studied by Park and Kim(1999).

• Communications for Statistical Applications and Methods
• /
• v.10 no.1
• /
• pp.247-256
• /
• 2003

In this study, we systemize the theoretical validity for applying RRM to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the costs are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them. We apply the three-stage cluster RRM to field survey and suggest some necessary points for practical use.