• Journal of the Korean Data and Information Science Society
• /
• v.19 no.4
• /
• 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
• /
• v.28 no.4
• /
• pp.927-936
• /
• 2017

To analyze longitudinal count data, Poisson linear mixed models are commonly used. In the models the random effects covariance matrix explains both within-subject variation and serial correlation of repeated count outcomes. When the random effects covariance matrix is assumed to be misspecified, the estimates of covariates effects can be biased. Therefore, we propose reasonable and flexible structures of the covariance matrix using autoregressive and moving average Cholesky decomposition (ARMACD). The ARMACD factors the covariance matrix into generalized autoregressive parameters (GARPs), generalized moving average parameters (GMAPs) and innovation variances (IVs). Positive IVs guarantee the positive-definiteness of the covariance matrix. In this paper, we use the ARMACD to model the random effects covariance matrix in Poisson loglinear mixed models. We analyze epileptic seizure data using our proposed model.

• The Korean Journal of Applied Statistics
• /
• v.28 no.2
• /
• pp.123-136
• /
• 2015

Science has developed with great achievements after Galileo's discovery of the law depicting a relationship between observable variables. However, many natural phenomena have been better explained by models including unobservable random effects. A mixed effect model was the first statistical model that included unobservable random effects. The importance of the mixed effect models is growing along with the advancement of computational technologies to infer complicated phenomena; subsequently mixed effect models have extended to various statistical models such as hierarchical generalized linear models. Hierarchical likelihood has been suggested to estimate unobservable random effects. Our special issue about mixed effect models shows how they can be used in statistical problems as well as discusses important needs for future developments. Frequentist and Bayesian approaches are also investigated.

• Journal of Korean Society of Forest Science
• /
• v.98 no.2
• /
• pp.178-182
• /
• 2009

A new mixed-effects model was developed that predicts individual-tree total height for Pinus densiflora trees in Gangwon province as a function of individual-tree diameter (cm). The mixed-effects model contains two random-effects parameters. Maximum likelihood estimation was used to fit the model to 560 height-diameter observations of individual trees measured throughout Gwangwon province in 2007 as part of the National Forest Inventory Program in Korea. The new model is an improvement over fixed-effects models because it can be calibrated to a local area, such as an inventory plot or individual stand. The new model also appears to be an improvement over the Forest Resources Evaluation and Prediction Program for the ten calibration trees used in this study. An example is provided that describes how to estimate the random-effects parameters using ten calibration trees.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.2
• /
• pp.413-420
• /
• 2008

This paper suggests a marginal logit mixed-effects for analyzing repeated binary response data. Since binary repeated measures are obtained over time from each subject, observations will have a certain covariance structure among them. As a plausible covariance structure, 1st order auto-regressive correlation structure is assumed for analyzing data. Generalized estimating equations(GEE) method is used for estimating fixed effects in the model.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.317-328
• /
• 2002

We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

• Journal of the Korean Wood Science and Technology
• /
• v.27 no.4
• /
• pp.57-64
• /
• 1999

This research was carried out to investigate the effects of density, resin and particle types on the physical and mechanical properties of the composites made from various wood particles mixed with coating paper. The experiment was designed to apply with three particles (flake, chip, and fiber) and three resin types (urea, phenol and PMDI resin). The mixed ratio of coating paper to wood particle was fixed on 50 to 50% in each board making. And also it was designed to apply for four density levels (0.6, 0.7, 0.8 and 0.9 g/$cm^3$) and four mixed formulations of coating paper to wood particle (10:90, 20:80, 30:70, and 40:60 %) to analyze clearly the effects of PMDI resin. Coating paper-wood particle composites have acceptable bending strength (MOR, MOE) though the mixed ratio of coating paper was increased, but have low internal bond strength and poor dimensional stability (WA, TS, LE). Composites with high density had higher mechanical properties but showed lower physical properties than composites with low density. In conclusion, at least up to 20% mixed ratios, coating paper-wood particle composites have acceptable physical and mechanical properties, and PMDI resin has possibility for coating paper-wood particle composite manufacture.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.2
• /
• pp.445-452
• /
• 2009

Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. Many existing credibility models can be expressed as special cases of linear mixed effects models. In this paper we propose a nonlinear credibility regression model by reforming the linear mixed effects model through kernel machine. The proposed model can be seen as prediction method applicable in any setting where repeated measures are made for subjects with different risk levels. Experimental results are then presented which indicate the performance of the proposed estimating procedure.

• The Korean Journal of Applied Statistics
• /
• v.15 no.1
• /
• pp.129-137
• /
• 2002

This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but considered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.9
• /
• pp.853-860
• /
• 2017

To evaluate the effects of mode II on the crack initiation and propagation stages, the effects in the fatigue threshold region under a mixed-mode I+II loading state was experimentally investigated. In the case of mixed-mode I + II, during the crack initiation stage, as the loading application angle (${\theta}$) increased, cracks occurred in the lower load owing to the effects of mode II, while the crack propagation rate decreased. The effects of mode II were experimentally investigated in the crack propagation stage by means of multilevel loading direction variation. Following mixed-mode I+II ($0^{\circ}{\rightarrow}{\theta}{\rightarrow}60^{\circ}$), as the load application angle increased, the fatigue crack propagation rate decreased, as did the fatigue crack propagation rate, which occurred later. Following mixed-mode I + II in case of(${\theta}{\geq}75^{\circ}$), the fatigue crack propagation rate was found to increase, while the fatigue life decreased.