• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.465-474
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• 2015

In this paper, we study the local influence analysis of LIU type estimator in the linear mixed models. Using the method proposed by Shi (1997), the local influence of LIU type estimator in three disturbance models are investigated respectively. Furthermore, we give the generalized Cook's distance to assess the influence, and illustrate the efficiency of the proposed method by example.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.587-595
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• 2008

Parallel coordinate plot of Inselberg (1985) is useful for visualizing dozens of variables, but so far the plot's applicability is limited to the variables of numerical type. The aim of this study is to extend the parallel coordinate plot so that it can accommodate both numerical and categorical variables. We combine Hayashi's (1950, 1952) quantification method of categorical variables and Hurley's (2004) endlink algorithm of ordering variables for the parallel coordinate plot. In line with our former study (Kwak and Huh, 2008), we develop Andrews' type modification of conventional straight-lines parallel coordinate plot to visualize the mixed-type data.

• Food Science and Biotechnology
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• v.16 no.2
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• pp.183-186
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• 2007

The type of mixed gel network of $\kappa$-carrageenan/agar was determined by applying rheological principles. Apparent Young's modulus of the mixed gels was mathematically analyzed with (a) simply adding the moduli of two component gels, (b) phase-separated type's upper and lower bound models, (c) interpenetrating type's logarithmic model. The experimental data fitted the estimates from the operation (a). Whereas, as for the models (b), the experimental values in the agar-rich region fitted the estimates of the upper bound model, but in the $\kappa$-carrageenan-rich region slightly deviated from those of the lower bound model. It reflected an evidence of a phase-separated type, although it was not typical, that there must be data good-fit in the agar-rich and $\kappa$-carrageenan-rich regions with the upper and lower bound models, respectively. Experimental values disagreed with estimates of the model (c). Gel time was analyzed to evince the phase-separated type. As agar concentrations increased at a fixed amount of $\kappa$-carrageenan, gel time gradually decreased and then sharply increased and decreased again. The pattern of such change in gel time also represented a typical behavior of phase-separated type's mixed gels.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1147-1161
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• 2015

Nowadays we are considering and analyzing not only classical data expressed by points in the p-dimensional Euclidean space but also new types of data such as signals, functions, images, and shapes, etc. Symbolic data also can be considered as one of those new types of data. Symbolic data can have various formats such as intervals, histograms, lists, tables, distributions, models, and the like. Up to date, symbolic data studies have mainly focused on individual formats of symbolic data. In this study, it is extended into datasets with both histogram and multimodal-valued data and a divisive clustering method for the mixed feature-type symbolic data is introduced and it is applied to the analysis of industrial accident data.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.12
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• pp.1729-1737
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• 2002

A mathematical model for the prediction of carbon-dioxide absorption rate during the transient state of rotary type absorber is developed. The rotary type absorber operates using a fast rotating porous structure and clean water. The model for the transient state rotary type absorbers is based on the steady state model of packed tower absorber. The paper manipulates the operating data of an arbitrary quasi-steady state condition of rotary type absorber for the determination of the coefficients involved in the model developed. The prediction accuracy is evaluated from the measured data of rotary type absorber operated under fast transient state. The measured data include the mole fraction of carbon dioxide in mixed gas and the pressure of absorber. The relative error in carbon dioxide prediction is estimated to be 20% at maximum. The model is successfully applied for the prediction of the behavior of a closed cycle diesel engine.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.117-120
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• 2006

Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.211-223
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• 1999

We propose a simple estimation procedure in the mixed linear models with censored normal data, using both Buckly and James(1979) type pseudo random variables and Lee and Nelder's(1996) estimation procedure. The proposed method is illustrated with the matched pairs data in Pettitt(1986).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.467-469
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• 2003

This research aimed to develop forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data. QuickBird data was used as satellite data. The method of this research was to extract satellite data for every single tree crown using image segmentation technique, then to evaluate the accuracy of classification by changing grouping criteria such as tree species, families, coniferous or broad-leaved species, and timber prices. As a result, the classification of tree species and families level was inaccurate, on the other hand, coniferous or broad-leaved species and timber price level was high accurate.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.719-732
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• 2006

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.