• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.59-74
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• 1996

The properties of the residuals are investigated when K-consecutive observations are interpolated. The central limit theorem is also proved for the LSE for autoregressive parameters when $\kappa4--consecutive observations are contaminated. The performance of the interpolated LSE in small samples is investigated by simulation. And the interpolated with the Yule-Walker type estimator.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.43-52
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• 1999

The local influence method is adapted to quadratic discriminant analysis for the identification of influential observations affecting the estimation of probability density function probabilities and log odds. The method allows a simultaneous perturbation on all observations so that it can identify multiple influential observations. The proposed method is applied to a real data set and satisfactory result is obtained.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.385-386
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• 1996

A wide-field CCD detector for solar eclipse observations is discussed. The CCD is supposed to be of a moderate size, and the image of the corona is obtained by scanning the field of view. Results of the 1995 solar eclipse observation are shown which have been made with a prototype of the scanning CCD detector.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.18-33
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• 1988

A new diagnostic statistic for detecting outliers and influential observations in linear models is suggested and studied in this paper. The proposed statistic is a weighted sum of two measures ; one is for detecting outliers and the other is for detecting influential ovservations. The merit of this statistic is that it is possible to distinguish outliers from influential observations. This statistic can be used for not only regression models but also factorial design models. A Monte Carlo simulation study is reported to suggest critical values for detecting outliers and influential observations for simple regression models when the number of observations is 11. 21, 31, 41 or 51.

• Publications of The Korean Astronomical Society
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• v.14 no.1
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• pp.9-22
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• 1999

Current searches for gravitational microlensing events are being carried out only by a photometric method. In this review paper, we demonstrate that the nature of Galactic lenses can be significantly better constrained with the additional astrometric observations of microlensng events. First, by astromerically observing lensing events, one can resolve the lens parameter degeneracy, and thus the lens mass can be determined with improved precision. Second, by being free from the blending problem, astrometric observations of lensing events will allow one to improve the uncertainties in the determined Einstein time scales. Third, the lens brightness, which could not be measured photometrically, can be measured from the astrometric observations of lensing events, and thus the nature of lens matter can be better constrained. Finally, with the help of astrometric followup observations of a binary-lens event, one can uniquely determine the solution of lens parameters, allowing one to obtain important astronomical information about the source star and the lens itself.

• Journal of The Korean Astronomical Society
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• v.23 no.2
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• pp.85-96
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• 1990

High resolution $^{12}CO$ observations of the region containing the planetary nebula Hb12 were made with the Nobeyama Radio Telescope. These observations reveal that there is no significant CO emission from Hb 12 itself. Near Hb 12, however, the observed regions show a structure of clustered dark clouds whose physical parameters suggest that these clumps would be further fragmented or collapesed. Also found with the high resolution observations is that a few isolated clumps are located away from the main CO feature extended possibly from the galactic plane. For more detail morphologies and velocity structures of the clumps, especially in relation to the large CO complex to which these are likely to be associated, more observations are substantiated.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.44.2-44.2
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• 2013

We probe the feasibility of high-frequency radio observations of very rapid flux variations in compact active galactic nuclei (AGN). Our study assumes observations at 230 GHz with a small 6-meter class observatory, using the SNU Radio Astronomical Observatory (SRAO) as example. We find that 33 radio-bright sources are observable with signal-to-noise ratios larger than ten. We derive statistical detection limits via exhaustive Monte Carlo simulations assuming (a) periodic, and (b) episodic flaring flux variations on time-scales as small as tens of minutes. We conclude that a wide range of flux variations is observable. This makes high-frequency radio observations - even with small observatories - a powerful probe of AGN intra-day variability; especially, those observations complement observations at lower radio frequencies with larger observatories like the Korean VLBI Network (KVN).

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.511-520
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• 2021

Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.110-117
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• 2022

This paper describes a localization algorithm utilizing relative observations for multiple autonomous underwater vehicles (Multiple-AUVs). In order to maximize the efficiency of operation and mission accomplishment and to prevent problems such as collision and interference, the locations and directions of Multiple-AUVs must be precisely estimated. To estimate the locations and directions, we designed a localization algorithm utilizing relative observations and verified it with simulations based on sensor data sets acquired through real sea experiments. Also, an optimal combination of relative observation information for efficient localization is figured out through combining various relative observations. The proposed method shows improved localization results compared to those only using the navigation algorithm. The performance of localization is improved up to 58% depending on the combination of relative observations.