• Journal of the Korean Mathematical Society
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• v.47 no.6
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• pp.1299-1316
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• 2010

We derive estimates for the truncation, amplitude and jitter type errors associated with Hermite-type interpolations at equidistant nodes of functions in Paley-Wiener spaces. We give pointwise and uniform estimates. Some examples and comparisons which indicate that applying Hermite interpolations would improve the methods that use the classical sampling theorem are given.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.120-120
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• 2000

In this study, in order to control real system under the environment of graphic user interface, study on the technique which can control real system without additional hardware drivers using virtual machine driver operated on the windows operating system. Consider the problem which is the error and the delay of a sampling time on the multi task processing through the load test of the experiment using graphic user interface.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.637-644
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• 2001

We investigated two kinds of mean square error (MSE) estimator of homogeneous linear estimator (HLE) for the population total under stratified multi-stage sampling. One is studied when the second stage variance component is estimable and the other is found in cafe it is not estimable. The proposed estimators are necessary forms of non-negative unbiased MSE estimators of HLE.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.391-411
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• 2010

For estimating the mean of a finite population, three classes of estimators using multi-auxiliary information with unknown means using two phase sampling in presence of non-response have been proposed with their properties. Asymptotically optimum estimator(AOE) in each class has been identified along with their mean squared error formulae. An empirical study is also given.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.23-32
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• 2012

This paper deals with the bias and variance of regression coefficient estimators in a finite population. We derive approximate formulas for the bias, variance and mean square error of two estimators when we select a fixed-size inclusion probability proportional to the size sample and then estimate regression coefficients by the ordinary least square estimator as well as the weighted least square estimator based on the selected sample data. Necessary and sufficient conditions for the comparison of the two estimators in terms of variance and mean square error are suggested. In addition, a simple example is introduced to numerically compare the variance and mean square error of the two estimators.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.79-85
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• 2010

The uncertainty in WindCube LIDAR measurements, which are specific to wind profiling at less than 200m above ground levelin wind resource assessments, was analyzed focusing on the error caused by its volume sampling principle. A two-month SODAR measurement campaign conducted in an urban environment was adopted as the reference wind profile assuming that various atmospheric boundary layer shapes had been captured. The measurement error of LIDAR at a height z was defined as the difference in the wind speeds between the SODAR reference data, which was assumed to be a virtually true value, and the numerically averaged wind speed for a sampling volume height interval of $z{\pm}12.5m$. The pattern of uncertainty in the measurement was found to have a maximum in the lower part of the atmospheric boundary layer and decreased with increasing height. It was also found that the relative standard deviations of the wind speed error ratios were 6.98, 2.70 and 1.12% at the heights of 50, 100 and 150m above ground level, respectively.

• Ocean and Polar Research
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• v.39 no.2
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• pp.73-84
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• 2017

The probability distribution of ichthyoplankton is important for enhancing the precision of sampling while reducing unnecessary surveys. To estimate the ichthyoplankton detection proportion (IDP) and its margin of error (ME), the monitoring information of the chub mackerel's (Scomber japonicus) ichthyoplankton presence-absence sampling data has been were collected over approximately 30 years (from 1982 to 2011) in the Korean coastal seas. Based on the computed spatial distributions of the mackerel's IDP and ME, the confidence interval (CI) range, defined as 2 ME, decreases from approximately 80% to 40% as the sample size n increases from 4 to 24 and the ME is approximately 40% in the typical (seasonal survey) case n = 4 per year. The IDP and ME off Jeju Island are relatively high at the 0.5-degree smoothing level. After increasing the spatial smoothing level to 1.0-degree, the ME decreased, and the spatial distribution pattern also changed due to the over-smoothing effects. In this study, the 0.5-degree smoothing is more suitable for the distribution pattern than the 1.0-degree smoothing level. The area of the high IDP and the low ME on the mackerel's ichthyoplankton was similar to the estimated spawning ground in the Korean peninsula. This information could contribute to enhancing for the spawning ecology surveys.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.153-160
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• 2022

A greedy algorithm is proposed to select a subset of nodes of a graph for bandlimited graph signals in which each signal value is generated with its weight. Since graph signals are weighted, we seek to minimize the weighted reconstruction error which is formulated by using the QR factorization and derive an analytic result to find iteratively the node minimizing the weighted reconstruction error, leading to a simplified iterative selection process. Experiments show that the proposed method achieves a significant performance gain for graph signals with weights on various graphs as compared with the previous novel selection techniques.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.657-662
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• 2005

The Non-Sampling Error can happen any time by means of the intended or unintended error by the interviewer or respondent, but it is very difficult to find the error in survey database because it can hardly be computed mathematically and systematically. Until now, we have found it accidentally through the simple relation between the items or through the inspection from the random field. Therefore we introduced an heuristic methodology that can detect the interviewer's error by statistical decision-making or data mining techniques with a case study. It will be helpful so as to improve the statistical duality and provide efficient field management for the supervisor.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.