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Bayesian predictive inference for linear regression models with t-errors
Azizur Rahman
Data Science Research Unit
DaMRG - Data Mining Research Group
Machine Vision and Digital Health (MaViDH) Research Group
Cyber Security Research Group (CSRG)
Imaging and Sensing Research Group
Health Services Research Group
Computing, Mathematics and Engineering
Research output
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Abstract
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peer-review
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Dive into the research topics of 'Bayesian predictive inference for linear regression models with t-errors'. Together they form a unique fingerprint.
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Mathematics
Linear Regression Model
100%
Inference
50%
Future Response
50%
Matrix
37%
Shape Parameter
25%
Multiple Regression Model
25%
Bayesian Approach
25%
Scale Parameter
12%
Error Distribution
12%
Univariate
12%
Bayesian
12%
Conditionals
12%
Statistical Approach
12%
Simple Regression Model
12%
T-Distribution
12%
Regression Parameter
12%
Classical Method
12%
Degrees of Freedom
12%
Prediction
12%
Statistical Method
12%
Social Sciences
Regression Model
75%
Distribution
75%
Approach
37%
Parameter
37%
Statistics
12%
Illustrations
12%
Civil and Political Rights
12%
Students
12%
Application
12%
Location
12%
Size
12%
Regression
12%
Psychology
Multiple Regression
75%
Assumptions
25%
Regression
12%
Chemistry
Error
62%
Dimension
12%
Application
12%
Particle Size
12%
Point Group T
12%
Economics, Econometrics and Finance
Bayesian
37%
Robustness
12%
Location
12%