• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.10
• /
• pp.2523-2529
• /
• 2014

Location estimation service can be provided outdoors using various location estimation system based on GPS. However, location estimation system is based on existing indoor resources as GPS cannot be used because of insufficient visible satellites and weak signals. The fingerprinting technique that uses WLAN signal, in particular, is good to use indoors because it uses RSSI provided by AP to estimate location. However, its accuracy may vary depending on how accurate data the offline stage used where the fingerprinting map is built. The study sampled various data at the stage that builds the fingerprinting map and suggested a location estimation system that enhances its precision by saving the data of high frequency among them to improve this problem. The suggested location estimation system based on majority sampling data estimates location by filtering RSSI data of the highest frequency at the client and server to be saved at a map, building the map and measuring a similar distance. As a result of the test, the location estimation precision stood at minimum 87.5 % and maximum 90.4% with the margin of error at minimum 0.25 to 2.72m.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.2
• /
• pp.635-644
• /
• 2008

We consider estimation of reliability P(Y

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.39-44
• /
• 2002

We compare MISE of the MLE, UMVUE, invariantly optimal estimator and Jacknife estimator for the reliability function of the Weibull distribution when the sample size is small.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.3
• /
• pp.651-656
• /
• 2005

In this paper the quasi-likelihood function was proposed and the estimators which are the solutions of the estimating equations for estimation of a class of nonlinear time series models. We compare the performances of the proposed estimators with those of the ML estimators under the heavy-railed distributions by simulation.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.1
• /
• pp.259-267
• /
• 2007

We consider parametric estimation in a half-normal variable and a UMVUE of its right-tail probability. Also we consider estimation of reliability in two independent half-normal variables, and derive k-th moment of ratio of two same variables.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2009.06a
• /
• pp.663-664
• /
• 2009

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.3
• /
• pp.783-792
• /
• 2007

We consider estimation of reliability P(Y

• International Journal of Reliability and Applications
• /
• v.1 no.2
• /
• pp.133-143
• /
• 2000

Data from weighted distributions appear, among other situations, when some of the data are missing or are damaged, a case that is important in reliability and life testing. The kernel method for hazard rate estimation is discussed for these data where the basic large sample properties are given. As a by product, the basic properties of the kernel estimate of the distribution function for data from weighted distribution are presented.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.35 no.7
• /
• pp.261-271
• /
• 1986

This paper describes a method for the state estimation considering current measurement component and detection of the bad data. The state values are estimated by weighted least square method in which measurement vector included bus injection current and line current. The bad data are detected using standardized variable of normal distribution and identified using sensitivity coefficients. When the bad data were occured by the bad measurement values. The results of the application to the model power system reveal the effectiveness of the presented algorithms.

• Journal of the Korean Statistical Society
• /
• v.12 no.1
• /
• pp.24-35
• /
• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.