• The Korean Journal of Applied Statistics
• /
• v.22 no.6
• /
• pp.1289-1300
• /
• 2009

The double sampling scheme is effective in reducing the sampling cost. However, the doubly sampled data is contaminated by two types of error, namely false-positive and false-negative errors. These would make the statistical analysis more difficult, and it would require more sophisticate analysis tools. For instance, the Wald method for the interval estimation of a proportion would not work well. In fact, it is well known that the Wald confidence interval behaves very poorly in many sampling schemes. In this note, the property of the Wald interval is investigated in terms of the coverage probability and the expected width. An alternative confidence interval based on the Agresti-Coull's approach is recommended.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.12
• /
• pp.125-132
• /
• 2010

In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.

• Journal of the Korean Statistical Society
• /
• v.28 no.3
• /
• pp.297-309
• /
• 1999

A sequential procedure of fixed-width confidence intervals for quantiles satisfying a condition of coverage probability is provided based on recursive density estimators. It is shown that the proposed sequential procedure is asymptotically efficient. In addition, the asymptotic normality for the proposed stopping time is derived.

• Communications for Statistical Applications and Methods
• /
• v.4 no.2
• /
• pp.523-532
• /
• 1997

We propose several estimators of the reliability function R of the two-parameter exponential distribution, and then compare those estimator in terms of the mean square error (MSE) through Monte Carlo method. We also consider the parametric bootstrap estimation. Using the parametric bootstrap estimator, we obtain the bootstrap confidence intervals for reliability function and compare the proposed bootstrap confidence intervals in terms of the length and the coverage probability through Monte Carlo method.

• Journal of applied mathematics & informatics
• /
• v.23 no.1_2
• /
• pp.479-488
• /
• 2007

A sequential procedure is proposed in order to construct one-sided confidence intervals for a normal mean with guaranteed coverage probability and ${\beta}-protection$ when the normal mean and variance are identical. First-order asymptotic properties on the sequential sample size are found. The derived results hold with uniformity in the total parameter space or its subsets.

• The Mathematical Education
• /
• v.51 no.3
• /
• pp.301-321
• /
• 2012

Since research has barely been done on the minority with low-achievement & low-SES in probability, this research attempted to search the change of their thinking level in the classes of probability and motivate them on the mathematical learning to feel confident in mathematics. We can say that the problems of the educational discriminations are due to the overlook on the individual conditions, situations, and environments. Therefore, in order to resolve some discrimination, 4 students who belonged to the minority group, engaged in the research, based on 10 units of the instructional materials designed for the research. As a result, for the student's thinking level, it was observed that they were improved from the 1st to the 3rd level in probability. Also, the researcher found that the adequate use of the encouragement, the praise, the direct explanation, and the scaffolding enabled them to prompt their learning motives and the increased responsibility on the learning. As time passed, the participants could share their mathematical knowledge and its concept with others, in the increased confidence.

• Journal of Information Processing Systems
• /
• v.15 no.2
• /
• pp.331-343
• /
• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.20 no.5
• /
• pp.341-349
• /
• 2016

Currently, researches are being actively conducted in assessing seismic performance of nuclear facilities in USA and Europe. In particular, applying this technique of assessing seismic performance to design of isolation systems in nuclear power plants is being performed and then ASCE 4 Draft (2013) is being revised accordingly in the United States. In order to satisfy the probabilistic performance objectives described by seismic responses with certain confidence levels (ASCE 43, 2005), the probability distributions of these responses have to be defined. What is the minimum number of input ground-motions to obtain the probability distribution precise enough to represent the unknown actual distribution? Theoretical basis, for how to determine the minimum number of input ground-motions for given a logarithmic standard deviation to approximate the unknown actual median of the log-normal distribution within a range of error at a certain level of confidence, is introduced by Huang et al. (2008). However, the relationship between the level of confidence and the range of error is not stated in the previous study. In this paper, based on careful reviews on the previous work, the relationship between the level of confidence and the range of error is logically and explicitly stated. Furthermore, this relationship is also applied to derive the minimum number of input ground-motions in order to approximate the unknown actual logarithmic standard deviation. Several recommendations are made for determining the minimum number of input ground-motions in probabilistic assessment on seismic performance of facilities in nuclear power plants.

• Communications for Statistical Applications and Methods
• /
• v.17 no.5
• /
• pp.679-688
• /
• 2010

Lee (2010) developed a confidence interval for the difference of binomial proportions in two doubly sampled data subject to false-positive errors. The confidence interval seems to be adequate for a general double sampling model subject to false-positive misclassification. However, in many applications, the false-positive error rates could be the same. On this note, the construction of asymptotic confidence interval is considered when the false-positive error rates are common. The coverage behaviors of nine likelihood based confidence intervals are examined. It is shown that the confidence interval based Rao score with the expected information has good performance in terms of coverage probability and expected width.

• Communications for Statistical Applications and Methods
• /
• v.18 no.5
• /
• pp.615-623
• /
• 2011

Several methods are used in interval estimation for binomial proportion; however the coverage probabilities of most confidence intervals depart from the confidence level when the binomial population proportion closes to 0 or 1 due to the extreme value. Vollset (1993), Agresti and Coull (1998), Newcombe (1998), and Brown et al. (2001) suggested methods to adjust the extreme value. This paper discusses the influence of extreme value in a binomial confidence interval through the numerical comparison of 6 confidence intervals.