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Mathematics

Regression
Estimator
Predictors
High-dimensional
Variable Selection
Sufficient Dimension Reduction
Dimension Reduction
Model Selection
Covariates
Quantile Regression
Model
Estimate
Linear regression
Covariance matrix
Sliced Inverse Regression
Regression Model
Penalized Regression
Outlier
Sample Size
Diagnostics
Lasso
Inverse Regression
Penalty
Central Subspace
Markov Chain Monte Carlo
Testing
Envelope
Simulation
Bootstrap
Methodology
Support Vector Machine
Alternatives
Likelihood
Higher Dimensions
Sliced Average Variance Estimation
Simulation Study
High-dimensional Data
Discriminant Analysis
Prediction
Change Point
Quantile
Demonstrate
Cumulative Sum
Elastic Net
Regression Function
Regularization
Gaussian distribution
Margin
Nonparametric Regression
Generalized Linear Model
Multiple Regression
Cross-validation
Nonlinear Regression
Approximation
Test Statistic
Central limit theorem
Data analysis
Finite Population Sampling
Correlation Matrix
Minimax Rate
Regression Coefficient
Penalized Likelihood
Statistic
Maximum Likelihood Estimator
Gaussian Random Field
Asymptotic distribution
Statistics
Least Median of Squares
Random variable
Admissibility
Principal Components
Maximum Likelihood
Non-parametric test
Markov chain
Oracle Property
Bayes
Unknown
Graphical Models
Screening
Exponential Family
Feature Selection
Model-based Clustering
Likelihood Ratio Test
Linear Model
Reduction Method
Random Matrices
Rate of Convergence
Regression Estimator
Subset
Coordinate Descent
Clustering
Pursuit
Partial
Conditional Distribution
Posterior distribution
Microarray Data
Selection Procedures
Normality
Control Charts
Maximum Likelihood Estimation

Business & Economics

Estimator
Predictors
Dimension reduction
Simulation