Results 221 to 230 of about 136,511 (258)
Some of the next articles are maybe not open access.
2004
In this chapter we study log-linear models which are useful for modeling multivariate discrete data. There is a strong connection between log-linear models and undirected graphs.
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In this chapter we study log-linear models which are useful for modeling multivariate discrete data. There is a strong connection between log-linear models and undirected graphs.
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Bayesian selection of log‐linear models
Canadian Journal of Statistics, 1996AbstractA general methodology is presented for finding suitable Poisson log‐linear models with applications to multiway contingency tables. Mixtures of multivariate normal distributions are used to model prior opinion when a subset of the regression vector is believed to be nonzero.
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On the Log-Linear Inversion-Charge Relation for MOSFET Modeling
IEEE Transactions on Electron Devices, 2022Yuan Taur
exaly
Contingency Tables and Log-Linear Models
1983This chapter is about the analysis of data in which the response and explanatory variables are all categorical, i.e. they are measured on nominal or possibly ordinal scales. Each scale may have more than two categories. Unlike the methods described in previous chapters, generalized linear models for categorical data can readily be defined when there is
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Distribution-free multivariate process control based on log-linear modeling
IIE Transactions, 2008exaly
Log-linear and logistic modeling of dependence among diagnostic tests
Preventive Veterinary Medicine, 2000Wesley Johnson +2 more
exaly