• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1271-1277
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• 2012

In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.140-148
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• 2000

This paper presents a fault detection and isolation(FDI) method based on Generalized Likelihood Ratio(GLR) test for the tightly coupled SDINS/CPS system. The GLR test is known to have the capability of detecting an assumed change while estimating its occurrence time and magnitude, and isolating the changing part. Once a fault is detected even if we don't know if the fault occurrs at either INS or GPS, multi-hypothesized GLR scheme performs the fault isolation between INS and GPS, and find which satellite malfunctions. However, in the INS faulty case, it turned out to fail to accomodate the fault isolation between accelerometer and gyroscope due to the coupling effects and a poor observability of the system. Hence, to isolate the INS fault, it needs to change the attitude of the vehicle resulting in enhancing the degree of observability.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.247-264
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• 2008

This paper considers the integrated process control procedure for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. It is assumed that a special cause can change the process mean and the process variance. We derive expressions for the process deviation from target for a variety of different process parameter changes, and introduce a control chart, based on the generalized likelihood ratio, for detecting special causes. We also propose the integrated process control scheme bases on the future loss. The future loss denotes the cost that will be incurred in a process remaining interval from a true out-of-control signal.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.563-571
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• 2001

In this paper, we study selecting a transformation so that the transformed variable is nearly symmetrically distributed. The large sample properties of an M-estimator of transformation parameter that is obtained by minimizing the integrated square of the imaginary part of the empirical characteristic function are investigated when a random sample is selected from some unspecified distribution. According to influence function calculations and Monte Carlo simulations, these estimates are less sensitive, than the normal model maximum likelihood estimates, to a few outliers.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.05a
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• pp.94-95
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• 2018

• Clinical and Experimental Reproductive Medicine
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• v.49 no.4
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• pp.285-288
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• 2022

Mesenchymal chondrosarcoma is a rare tumor that is more common in young people; it is an uncommon type of chondrosarcoma with a poor prognosis. In two-thirds of cases, it affects the bone, especially the spine. However, parts of the body other than the skeletal system are occasionally involved. These rarer types have a worse prognosis, with a high likelihood of metastasis and death. Due to the possible misdiagnosis of mesenchymal chondrosarcoma, the integrated use of imaging, immunohistochemistry, and pathology can be helpful.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.502-508
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• 2005

In order to assess the environmental risk of pesticides, information is usually required on the likelihood of exposure of organisms to the constituents of pesticides, expressed as a predicted environmental concentrations (PECs) and the likely effects of the constituents of pesticides on aquatic and terrestrial organisms, expressed as a predicted no-effect concentrations (PNECs). In this paper, the pesticide fate model, RICEWQ alone and coupled with the pesticide movement model, RIVWQ was used to simulate the potential for predicting the environmental concentrations of pesticides in paddy fields and adjacent surface water systems. The RICEWQ model was successfully calibrated against field data in poinding depth for paddy field. For the assessment of importance for water and pesticide management conditions and field scales, the integrated RICEWQ-RIVWQ model was simulated by the scenario analysis. The results of this study can be used as a basic information for assessing the environmental risk of pesticides.

• KDI Journal of Economic Policy
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• v.40 no.4
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• pp.1-22
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• 2018

We estimate three continuous-time stochastic volatility models following the approach by Aït-Sahalia and Kimmel (2007) to compare the Korean and US stock markets. To do this, the Heston, GARCH, and CEV models are applied to the KOSPI 200 and S&P 500 Index. For the latent volatility variable, we generate and use the integrated volatility proxy using the implied volatility of short-dated at-the-money option prices. We conduct MLE in order to estimate the parameters of the stochastic volatility models. To do this we need the transition probability density function (TPDF), but the true TPDF is not available for any of the models in this paper. Therefore, the TPDFs are approximated using the irreducible method introduced in Aït-Sahalia (2008). Among three stochastic volatility models, the Heston model and the CEV model are found to be best for the Korean and US stock markets, respectively. There exist relatively strong leverage effects in both countries. Despite the fact that the long-run mean level of the integrated volatility proxy (IV) was not statistically significant in either market, the speeds of the mean reversion parameters are statistically significant and meaningful in both markets. The IV is found to return to its long-run mean value more rapidly in Korea than in the US. All parameters related to the volatility function of the IV are statistically significant. Although the volatility of the IV is more elastic in the US stock market, the volatility itself is greater in Korea than in the US over the range of the observed IV.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.217-236
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• 2015

The purpose of this study is to propose the effective location-based IoT service acceptance model by integrating ELM (Elaboration Likelihood Model) with UTAUT (Unified Theory of Acceptance and Use of Technology). The Partial Least Squares was used to analyze the causal relationships with respect to the effects of central route and peripheral route on acceptance intention. The results shows that central route has more significant impacts on perceived usefulness than peripheral route and CFIP (Concern for Information Privacy) weaken the relationship of acceptance intention and perceived usefulness. Our findings indicate some meaningful implications in the acceptance research of IOT services. First, we noted that the easy of use significantly affects the adoption of location-based IoT service. Furthermore, it is important to build the secured mechanism of privacy protection to adopt of location-based IoT service. Second, we tried to attempt the newly integrated approach to technical acceptance using UTAUT's variables and ELM by Petty and Cacioppo (1986). Finally this research empirically analyzed the adoption case of location-based IoT service which is not well-known yet within our country.

• Spatial Information Research
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• v.5 no.2
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• pp.177-183
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• 1997

S1he concept of a class in the land-use classification system can be equally applied to a class in the land-use-change classification. The maximum likelihood method using linear discriminant function and Markov transition matrix method were integrated to a synthetic modeling effort in order to project spatial allocation of land-use-change and quantitative assignment of that prediction as a whole. The algorithm of both the multivariate discriminant function and the Markov chain matrix were discussed and the test of synthetic model on the study area was resulted in the projection of '90 year as well as '95 year land -use classification. The accuracy and the issue of modeling improvement were discussed eventually.