• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.291-293
• /
• 2004

The aim of this study was to cross-validate a spatial probabilistic model of landslide likelihood ratios at Boun, Janghung and Yongin, in Korea, using a Geographic Information System (GIS). Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. Maps of the topography, soil type, forest cover, lineaments and land cover were constructed from the spatial data sets. The 14 factors that influence landslide occurrence were extracted from the database and the likelihood ratio of each factor was computed. 'Landslide susceptibility maps were drawn for these three areas using likelihood ratios derived not only from the data for that area but also using the likelihood ratios calculated from each of the other two areas (nine maps in all) as a cross-check of the validity of the method For validation and cross-validation, the results of the analyses were compared, in each study area, with actual landslide locations. The validation and cross-validation of the results showed satisfactory agreement between the susceptibility map and the existing landslide locations.

• 한국통계학회:학술대회논문집
• /
• 한국통계학회 2005년도 춘계 학술발표회 논문집
• /
• pp.215-219
• /
• 2005

We consider penalized likelihood regression with exponential family responses. Parallel to recent development in Gaussian regression, the fast computation through asymptotically efficient low-dimensional approximations is explored, yielding algorithm that scales much better than the O($n^3$) algorithm for the exact solution. Also customizations of the direct cross-validation strategy for smoothing parameter selection in various distribution families are explored and evaluated.

• Journal of the Korean Data and Information Science Society
• /
• 제23권4호
• /
• pp.765-775
• /
• 2012

교차타당성은 커널추정량의 평활모수인 띠폭의 선택 방법으로 흔히 활용되고 있다. 연속인 확률밀도함수의 커널추정량의 띠폭 선택으로 널리 쓰이는 교차타당성 방법으로는 최대가능도교차타당성과 더불어 최소제곱교차타당성과 편의교차타당성이 있다. 확률밀도함수가 하나의 불연속점을 가질 때, Huh (2012)는 불연속점 추정을 위한 커널추정량의 띠폭 선택으로 최대가능도교차타당성을 이용한 방법을 제시하였다. 본 연구에서는 Huh (2012)에 의해 최대가능도교차타당성으로 제안된 띠폭선택의 방법과 같이 한쪽방향커널함수를 이용한 최소제곱교차타당성과 편의교차타당성으로 띠폭 선택 방법을 제시하고, 이들 띠폭 선택 방법들과 Huh (2012)의 최대가능도교차타당성을 이용한 띠폭 선택 방법을 모의실험을 통하여 비교연구 하고자 한다.

• Communications for Statistical Applications and Methods
• /
• 제12권3호
• /
• pp.743-758
• /
• 2005

This paper consider penalized likelihood regression with data from exponential family. The fast computation method applied to Gaussian data(Kim and Gu, 2004) is extended to non Gaussian data through asymptotically efficient low dimensional approximations and corresponding algorithm is proposed. Also smoothing parameter selection is explored for various exponential families, which extends the existing cross validation method of Xiang and Wahba evaluated only with Bernoulli data.

• Journal of the Korean Data and Information Science Society
• /
• 제22권3호
• /
• pp.613-618
• /
• 2011

The proposed method is based on a penalized log partial likelihood of Cox proportional hazard model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log partial likelihood function of Cox proportional hazard model. It provide the ecient computation including variable selection and leads to the generalized cross validation function for the model selection. Experimental results are then presented to indicate the performance of the proposed procedure.

• Journal of the Korean Data and Information Science Society
• /
• 제19권4호
• /
• pp.1327-1334
• /
• 2008

Mixed effect binomial regression models are widely used for analysis of correlated count data in which the response is the result of a series of one of two possible disjoint outcomes. In this paper, we consider kernel extensions with nonparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.

• Journal of the Korean Data and Information Science Society
• /
• 제18권3호
• /
• pp.767-772
• /
• 2007

A kernel machine is proposed as an estimating procedure for the linear and nonlinear Poisson regression, which is based on the penalized negative log-likelihood. The proposed kernel machine provides the estimate of the mean function of the response variable, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation(GCV) function of MSE-type is introduced to determine hyperparameters which affect the performance of the machine. Experimental results are then presented which indicate the performance of the proposed machine.

• Journal of the Korean Data and Information Science Society
• /
• 제23권1호
• /
• pp.79-87
• /
• 2012

Huh (2002)는 확률밀도함수가 하나의 불연속점을 가질 때, 한쪽방향커널함수를 이용하여 확률 밀도함수의 오른쪽과 왼쪽 커널추정량을 제시하여 그 차를 최대로 하는 점을 불연속점의 위치추정량으로 제안하였다. 커널추정량의 평활모수인 띠폭의 선택의 중요함은 익히 알려져 있다. 최대가능도 교차타당성은 확률밀도함수의 커널추정량에서 띠폭 선택의 기준으로 널리 쓰여지고 있다. 본 연구에서는 한쪽방향커널함수를 이용한 확률밀도함수의 오른쪽과 왼쪽 커널추정량들의 띠폭의 선택 방법을 Hart와 Yi (1998)의 한쪽방향교차타당성의 방법론을 최대가능도교차타당성에 적용하여 제안하고자 한다. 소표본 모의실험을 통하여 연구결과를 제시하고자 한다.

• Communications for Statistical Applications and Methods
• /
• 제15권6호
• /
• pp.1003-1011
• /
• 2008

Mixed-effect Poisson regression models are widely used for analysis of correlated count data such as those found in longitudinal studies. In this paper, we consider kernel extensions with semiparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.

• 응용통계연구
• /
• 제24권5호
• /
• pp.871-881
• /
• 2011

In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.