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1981
In Chapter 3 and 4 the method of maximum likelihood was introduced as a general method by which a model could be fitted to data. In Chapter 5 we specialized by restricting ourselves to normally distributed random variables, and to cases where the model is linear in the unknown parameters.
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In Chapter 3 and 4 the method of maximum likelihood was introduced as a general method by which a model could be fitted to data. In Chapter 5 we specialized by restricting ourselves to normally distributed random variables, and to cases where the model is linear in the unknown parameters.
openaire +1 more source
2020
Second-level analyses allow researchers to make inferences about properties of groups or populations, by generalizing from the observations of only a subset of subjects in a study. This chapter describes the mathematics behind the General Linear Model (GLM), the approach used in CONN for all second-level analyses of functional connectivity measures ...
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Second-level analyses allow researchers to make inferences about properties of groups or populations, by generalizing from the observations of only a subset of subjects in a study. This chapter describes the mathematics behind the General Linear Model (GLM), the approach used in CONN for all second-level analyses of functional connectivity measures ...
openaire +1 more source
Generalized Partially Linear Single-Index Models
Journal of the American Statistical Association, 1997Raymond J Carroll +2 more
exaly +2 more sources
Reliable Estimation of Generalized Linear Mixed Models using Adaptive Quadrature
The Stata Journal, 2002Sophia Rabe-Hesketh +2 more
exaly
Generalized model for linear referencing
Proceedings of the 7th ACM international symposium on Advances in geographic information systems, 1999openaire +1 more source
A general and simple method for obtaining R 2 from generalized linear mixed‐effects models
Methods in Ecology and Evolution, 2013Shinichi Nakagawa, Holger Schielzeth
exaly

