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Functional generalized linear models with images as predictors
Philip T. Reiss
, R. Todd Ogden
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peer-review
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Dive into the research topics of 'Functional generalized linear models with images as predictors'. Together they form a unique fingerprint.
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Mathematics
Functional Linear Model
100%
Generalized Linear Model
70%
Predictors
61%
Principal Component Regression
46%
Positron Emission Tomography
25%
Regression
25%
Neuroimaging
23%
Simultaneous Confidence Bands
23%
Generalized Additive Models
23%
High Resolution
20%
Principal Components
18%
Brain
18%
Likelihood Ratio
17%
Justification
16%
Coefficient
16%
Null hypothesis
15%
Univariate
14%
Scalar
12%
Methodology
12%
Testing
11%
Modeling
10%
Simulation
10%
Context
10%
Performance
9%
Chemical Compounds
Positron
78%
Additive
44%
Simulation
42%
Reaction Yield
27%
Application
20%
Medicine & Life Sciences
Linear Models
52%
Positron-Emission Tomography
31%
Neuroimaging
30%
Data Analysis
25%
Direction compound
24%
Technology
21%
Brain
16%
Engineering & Materials Science
Positron emission tomography
46%
Neuroimaging
43%
Image resolution
35%
Brain
27%
Testing
17%
Agriculture & Biology
linear models
68%
positron-emission tomography
26%
methodology
18%
brain
11%
testing
6%