• Journal of the Korean Data and Information Science Society
• /
• 제8권2호
• /
• pp.247-260
• /
• 1997

The quasi-likelihood models which greatly widened the scope of generalized linear models are widely used in data analysis where a likelihood is not available. Since a quasi-likelihood may not appear to be an ordinary likelihood for any known distribution in the natural exponential family, to fit the quasi-likelihood models the standard statistical packages such as GLIM, GENSTAT, S-PLUS and so on may not directly applied. SAS/IML is very useful for fitting of such models. In this paper, we present simple SAS/IML(version 6.11) program which helps to fit and analyze the quasi-likelihood models applied to the leaf-blotch data introduced by Wedderburn(1974), and the problem with deviance useful generally to model checking is pointed out, and then its solution method is mention through the data analysis based on this quasi-likelihood models checking.

• Journal of the Korean Data and Information Science Society
• /
• 제17권3호
• /
• pp.999-1007
• /
• 2006

The semiparametric gamma frailty models have been often used for multivariate survival analysis because they give an explicit marginal likelihood. The commonly used estimation procedure is the profile likelihood method based on marginal likelihood, which provides the same parameter estimates as the EM algorithm. In this paper we show in finite samples the standard profile-likelihood method can lead to an underestimation of parameters, particularly for the frailty parameter. To overcome this problem, we propose an adjusted profile-likelihood method. For the illustration a numerical example and a small-sample simulation study are presented.

• 한국지형학회지
• /
• 제25권2호
• /
• pp.1-14
• /
• 2018

The main objective of this paper is to classify properties of the locational environment for each debris type by calculating likelihood ratio based on the correlation between the distributions for each type of debris landform. A total of 8 thematic maps, like as elevation, slope, aspect, curvature, topographic wetness index (TWI), soil drainage, geology, and landcover including with GIS spatial information generally used in this type of debris landform analysis. The results of this study showed that the block stream had a high likelihood ratio compared to talus in areas with relatively high elevation; and concerning slope, the block stream had a high likelihood ratio in a relatively low region than talus. Concerning aspect, a clear correlation could not be analyzed for each debristype, and concerning curvature, the block stream displayed a developed slope on the more concave valley than the talus. Analysis concerning TWI, the block stream displayed a higher likelihood ratio in wider sections than talus, and concerning soil drainage, the talus and block stream both displayed a high likelihood ratio in regions with well-drained soil. The talus displayed a high likelihood ratio in the order of metamorphic rocks, sedimentary rocks, and granite, while the block stream displayed a high likelihood ratio in the order of volcanic rocks, granite, and sedimentary rocks. In addition, concerning landcover, the likelihood ratio had the most concentrated distributed compared to natural bare land only concerning talus. Based on the likelihood ratio result, it can be used as basic data for extracting the possible areas of distribution for each debris type through the GIS spatial integration method.

• Communications for Statistical Applications and Methods
• /
• 제14권1호
• /
• pp.229-239
• /
• 2007

We present a diagnostic method for the quasi-likelihood estimators in generalized linear models. Since these estimators can be usually obtained by iteratively reweighted least squares which are well known to be very sensitive to unusual data, a diagnostic step is indispensable to analysis of data. We extend the local influence approach based on the maximum likelihood function to that on the quasi-likelihood function. Under several perturbation schemes local influence diagnostics are derived. An illustrative example is given and we compare the results provided by local influence and deletion.

• Journal of the Korean Statistical Society
• /
• 제9권1호
• /
• pp.13-29
• /
• 1980

The statistical theory of factor analysis is briefly reviewed with emphasis on the maximum-likelihood method. A modified version of Joreskog(1975) is used for the implementation of the maximum-likelihood method. For the minimization of the conditional minimum function, an adaptive Newton-Raphson method is applied.

• 한국가스학회지
• /
• 제11권4호
• /
• pp.98-103
• /
• 2007

발생가능성 분석은 염소공정의 염소투입설비에서 누출 가능성을 교정하는데 자주 사용되고 있다. 그리고 이러한 시설은 전형적으로 압력용기, 기화기, 배관, 측량장비, 안전장치로 등으로 구성되어 있다. 이 논문에서는 가능성 분석절차와 기계적 요소들의 고장률에 대하여 사건 시나리오를 만들 인적오류도 고려하였다. 논문의 주된 목적은 결정된 각각의 시나리오의 발생가능성을 계산하는 것으로 발생가능성분석 방법에 근거하여 기계요소의 고장률과 인적오류를 포함하여 계산하였다. 그 결과, 주요 $Cl_2$ 취급공정에서 누출이 발생할 가능성이 $5.73{\times}10^{-5}$로 예측되었으며 세정시스템의 고장확률은 $4.11{\times}10^{-2}$로 나타났다.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제55권2호
• /
• pp.193-208
• /
• 2016

This study analyzes the likelihood principle and elicits an educational implication. As a result of analysis, this study shows that Frequentist and Bayesian interpret the principle differently by assigning different role to that principle from each other. While frequentist regards the principle as 'the principle forming a basis for statistical inference using the likelihood ratio' through considering the likelihood as a direct tool for statistical inference, Bayesian looks upon the principle as 'the principle providing a basis for statistical inference using the posterior probability' by looking at the likelihood as a means for updating. Despite this distinction between two methods of statistical inference, two statistics schools get clues to compromise in a regard of using frequency prior probability. According to this result, this study suggests the statistics education that is a help to building of students' critical eye by their comparing inferences based on likelihood and posterior probability in the learning and teaching of updating process from frequency prior probability to posterior probability.

• Communications for Statistical Applications and Methods
• /
• 제16권6호
• /
• pp.971-978
• /
• 2009

Poisson generalized linear mixed models(GLMMs) have been widely used for the analysis of clustered or correlated count data. For the inference marginal likelihood, which is obtained by integrating out random effects is often used. It gives maximum likelihood(ML) estimator, but the integration is usually intractable. In this paper, we propose how to obtain the ML estimator via Laplace approximation based on hierarchical-likelihood (h-likelihood) approach under the Poisson GLMMs. In particular, the h-likelihood avoids the integration itself and gives a statistically efficient procedure for various random-effect models including GLMMs. The proposed method is illustrated using two practical examples and simulation studies.

• 수산해양기술연구
• /
• 제46권3호
• /
• pp.223-231
• /
• 2010

This paper showed the difference between the selectivity of gill net by least square method with polynomials in Kitahara's and that by maximum likelihood analysis for Japanese sandfish and Korean flounder. Catch experiments for Japanese sandfish using commercial vessels off the eastern coast of Korea were conducted with six different mesh sizes between October and December 2007 and those for Korean flounder with five different mesh sizes between 2008 and 2009. The mesh size of 50% probability of catch corresponding to biological maturity length of fish was not different between that by least square method and that by maximum likelihood analysis for Japanese sandfish, however, a little different for Korean flounder, that is, those mesh sizes of 50% probability of catch for biological maturity length of Korean flounder were 10.6cm and 10.1cm by least square method and maximum likelihood analysis, respectively.

• Journal of the Korean Data and Information Science Society
• /
• 제17권3호
• /
• pp.919-925
• /
• 2006

Maximum likelihood estimate(MLE) is obtained from the partial log-likelihood function for the cell probabilities of two way incomplete contingency tables proposed by Chen and Fienberg(1974). The partial log-likelihood function is modified by adding lagrangian multiplier that constraints can be incorporated with. Variances of MLE estimators of population proportions are derived from the matrix of second derivatives of the loglikelihood with respect to cell probabilities. Simulation results, when data are missing at random, reveal that Complete-case(CC) analysis produces biased estimates of joint probabilities under MAR and less efficient than either MLE or MI. MLE and MI provides consistent results under either the MAR situation. MLE provides more efficient estimates of population proportions than either multiple imputation(MI) based on data augmentation or complete case analysis. The standard errors of MLE from the proposed method using lagrangian multiplier are valid and have less variation than the standard errors from MI and CC.