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초록보기

Test statistics using cumulative sums of residuals have been widely used in various regression models including generalized linear models(GLM). Recently, Pan and Lin (2005) extended this testing procedure to the generalized linear mixed models(GLMM) having random effects, in which we encounter difficulties in computing the marginal likelihood that is expressed as an integral of random effects distribution. The Gaussian quadrature algorithm is commonly used to approximate the marginal likelihood. Many commercial statistical packages provide an option to apply this type of goodness-of-fit test in GLMs but available programs are very rare for GLMMs. We suggest a computational algorithm to implement the testing procedure in GLMMs by a freely accessible R package, and also illustrate through practical examples.

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권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
Estimation of Median in the Presence of Three Known Quartiles of an Auxiliary Variable Housila P. Singh, Ramalingam Shanmugam, Sarjinder Singh, Jong-Min Kim pp.363-386

Dual Generalized Maximum Entropy Estimation for Panel Data Regression Models 이재준, 전수영 pp.395-409

Cumulative Sums of Residuals in GLMM and Its Implementation 최도연, 정광모 pp.423-433

The Bandwidth from the Density Power Divergence 박노진 pp.435-444

Double-Bagging Ensemble Using WAVE 김아연, 김민지, 김현중 pp.411-422

Analysis of Recurrent Gap Time Data with a Binary Time-Varying Covariate 김양진 pp.387-393

Dependence Structure of Korean Financial Markets Using Copula-GARCH Model 김우환 pp.445-459

Further Results on Characteristic Functions Without Contour Integration 송대건, 강슬기, 김형문 pp.461-469

참고문헌 (16건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 Chen, N. W. (2011). Goodness-of-Fit Test Issues In Generalized Linear Mixed Models, Unpublished Ph.D. Thesis, Graduate Studies of Texas A&M University. 미소장
2 Cook, D. R. and Weisberg, S. (1994). An Introduction to Regression Graphics, Wiley. 미소장
3 Hansen, A. M. (2012). Goodness-of-Fit Tests for Autoregressive Logistic Regression Models and Gen- eralized Linear Mixed Models, Unpublished Ph.D. Thesis, University of California Riverside. 미소장
4 Modelling count responses with overdispersion 소장
5 Lin, K. C. and Chen, Y. J. (2012). Assessing generalized linear mixed models using residual analysis, International Journal of Innovative Computing, Information and Control, 8, 5693–5701. 미소장
6 Model‐Checking Techniques Based on Cumulative Residuals 네이버 미소장
7 A likelihood reformulation method in non‐normal random effects models 네이버 미소장
8 McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models, Second edition, London: Chap- man and Hall. 미소장
9 Pan, Z. and Lin, D. Y. (2005). Goodness-of-fit methods for generalized linear mixed models, Biomet- rics, 61, 1000–1009. 미소장
10 Residuals in Generalized Linear Models 네이버 미소장
11 Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model 네이버 미소장
12 Nonparametric Model Checks for Regression 네이버 미소장
13 A Lack-of-Fit Test for the Mean Function in a Generalized Linear Model 네이버 미소장
14 Tang, M. (2010). Goodness of Fit Tests for Generalized Linear Mixed Models, Unpublished Ph.D. Thesis, Graduate School of the University of Maryland. 미소장
15 Thall, P. F. and Vail, S. C. (1990). Some covariance models for longitudinal count data with overdis- persion, Biometrika, 46, 657–671. 미소장
16 A Simulation‐based Goodness‐of‐fit Test for Random Effects in Generalized Linear Mixed Models 네이버 미소장

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