Mathematics
Regression Analysis
100%
Covariance
75%
Cox Transformation
56%
Proportional Hazards Model
50%
Least Square Estimation
50%
Bayesian Information Criterion
50%
Model Selection
50%
Parameter Estimation
50%
Convolutional Neural Network
50%
Covariance Function
50%
Moderate Sample Size
25%
Type Estimator
25%
Rejection Region
25%
Tailed Test
25%
Binary Response
25%
Likelihood Estimator
25%
Maximum Likelihood Estimator
25%
Selection Mechanism
25%
Gaussian Distribution
25%
Gaussian Process
25%
Covariance Model
20%
Least Square
16%
Missing Observation
16%
Response Variable
16%
Residuals
16%
Numerical Example
16%
Linear Models
16%
Confidence Interval
16%
Nonlinear Case
16%
Regression Model
16%
Composite Likelihood
10%
Explanatory Variable
10%
Degree of Belief
10%
Computer Science
Large Data Set
100%
Approximation (Algorithm)
70%
maximum-likelihood
70%
Likelihood Estimation
60%
Rank Approximation
50%
Spatial Prediction
50%
Covariance Function
50%
Convolutional Neural Network
50%
Cox Regression Model
26%
Partitioning Technique
25%
Driven Approach
25%
Parameter Estimation
25%
Prediction Error
20%
Supplementary Material
10%
Numerical Example
10%
Missing Observation
10%
Logistic Regression Model
10%
Uniform Distribution
10%
Simulation Study
10%
Data Characteristic
10%
Likelihood Estimate
10%
Estimation Accuracy
10%
Continuous Model
10%
Research Community
10%
Model Uncertainty
10%
Execution Time
10%
Spatial Configuration
10%
Synthetic Datasets
10%
Validation Method
10%
Prediction Interval
10%
Prediction Accuracy
10%
Information Loss
10%
