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Robustness of Minimum Norm Quadratic Unbiased Estimator of Variance Under the General Linear Model
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作者 张宝学 罗季 李馨 《Journal of Beijing Institute of Technology》 EI CAS 2002年第1期97-100,共4页
Necessary and sufficient conditions for equalities between a 2 y′(I-P Xx)y and minimum norm quadratic unbiased estimator of variance under the general linear model, where a 2 is a known positive number, are... Necessary and sufficient conditions for equalities between a 2 y′(I-P Xx)y and minimum norm quadratic unbiased estimator of variance under the general linear model, where a 2 is a known positive number, are derived. Further, when the Gauss? Markov estimators and the ordinary least squares estimator are identical, a relative simply equivalent condition is obtained. At last, this condition is applied to an interesting example. 展开更多
关键词 general linear model orthogonal projector minimum norm quadratic unbiased estimator
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A New General Linear Convolution Model for fMRI Data Process 被引量:1
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作者 袁宏 陈华富 尧德中 《Journal of Electronic Science and Technology of China》 2005年第1期68-71,共4页
General linear model (GLM) is the most popular method for functional magnetic resource imaging (fMRI) data analysis . However, its theory is imperfect. The key of this model is how to constitute the design-matrix to m... General linear model (GLM) is the most popular method for functional magnetic resource imaging (fMRI) data analysis . However, its theory is imperfect. The key of this model is how to constitute the design-matrix to model the interesting effects better and separate noises better. For the purpose of detecting brain function activation , according to the principle of GLM,a new convolution model is presented by a new dynamic function convolving with design-matrix,which combining with t-test can be used to detect brain active signal. The fMRI imaging result of visual stimulus experiment indicates that brain activities mainly concentrate among v1and v2 areas of visual cortex, and also verified the validity of this technique. 展开更多
关键词 FMRI general linear model T-TEST hemodynamic response function
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