Keyphrases
Actual Error
12%
Adaptive Kernel
50%
Almost Surely
12%
Anisotropic Gaussian Kernel
12%
Asymptotic Approach
16%
Asymptotic Efficiency
16%
Asymptotic Size
16%
Bootstrap Sampling
16%
Boundary Value Problem
25%
Checking Test
10%
Clustering Coefficient
16%
Collocation Formulation
25%
Component-wise
12%
Constrained Maximum Likelihood
50%
Degree Distribution
16%
Distance-based
10%
Double Precision
25%
Finite Mixture
16%
Finite Sample
16%
Free-running Test
16%
Fully Adaptive
50%
Fully-automatic
25%
Gaussian Interpolation
50%
Generating Shape
25%
Geometric Conditions
16%
Giant Component
16%
Global Smoothing
50%
Global-local
50%
Healthy Tissue
16%
High-order
16%
Ill-conditioning
25%
Independence Assumption
16%
Integrated Conditional Moment Test
20%
Interpolation Matrix
25%
Interpolation Method
12%
Invertibility
12%
Invertible
12%
Kernel Estimation
10%
Kernel Methods
50%
Kernel-based Collocation Methods
25%
Least-squares Collocation
25%
Likelihood Function
16%
Linear Systems
25%
Local Alternatives
10%
Local Smoothing
50%
Local Smoothing Test
40%
Low-discrepancy
25%
Low-discrepancy Sequences
12%
Mark Correlation
16%
Marked Point Process
33%
Maximum Likelihood Estimator
33%
Mean Clustering
16%
Meshless
25%
Monte Carlo Test
50%
Multivariate Point Process
33%
Nationality
16%
New Characteristics
16%
Nominal Level
12%
Nonparametric Estimation
16%
Null Distribution
16%
Numerical Accuracy
12%
Numerical Examples
25%
Numerical Recipes
25%
Numerical Simulation
16%
Order of Magnitude
25%
Parameter Estimation
16%
Parameter Identification
25%
Parameter-free
12%
Percolation Threshold
16%
Point Process
33%
Potential Problems
25%
Projection-based Test
10%
Pseudorandom numbers
12%
Quasi-Monte Carlo
50%
Quasi-random Points
25%
Random Distribution
12%
Random Graphs
50%
Random Point Set
25%
Random Shape
50%
Random Variables
16%
Randomized quasi-Monte Carlo
12%
Real Application
12%
Regression Model
10%
Relaxed Constraints
16%
Scale Parameter
50%
Separation Distance
25%
Shape Parameter
100%
Shortest Path
16%
Six Degrees of Separation
16%
Skew Normal Mixtures
50%
Skew-normal Distribution
16%
Skewness Parameter
50%
Small-word
16%
Smoothing Methods
50%
Spatial Point Pattern
50%
Spatial Point Process
16%
Spatially Variable
12%
Test Construction
10%
Test Statistic
33%
Theoretical Convergence
12%
Tree Species
33%
Two-person
16%
Unboundedness
16%
User Input
12%
User Needs
12%
Value Function Approximation
50%
Variable Precision
12%
Variable Shape
50%
Weight Function
10%
Well-defined
16%
Mathematics
Asymmetric
25%
Asymptotic Approach
12%
Asymptotics
12%
Bootstrap Sample
12%
Boundary Value Problems
25%
Closed Form
25%
Clustering Coefficient
12%
Conditionals
50%
Data Point
50%
Degree Distribution
12%
Double Precision
25%
Edge
12%
Finite Mixture
16%
Free Parameter
12%
Free Test
12%
Gaussian Distribution
50%
Independence Assumption
12%
Intertype
12%
Invertibility
12%
Least Square
25%
Likelihood Function
16%
Linear System
25%
Local Test
25%
Marked Point Process
25%
Matrix (Mathematics)
25%
Maximum Likelihood
50%
Maximum Likelihood Estimator
50%
Monte Carlo
50%
Nominal Level
10%
Nonparametric Estimation
12%
Null
12%
Numerical Example
25%
Parameter Estimate
16%
Point Process
50%
Pseudo-Random Number
10%
Random Graph
37%
Random Point
25%
Random Variable
12%
Real Data
25%
Regression Model
25%
Sample Case
16%
Scale Parameter
33%
Set Point
25%
Shape Parameter
100%
Skew-Normal Distribution
16%
Skewness
50%
Spatial Point Process
12%
Statistical Distribution
12%
Sufficient Condition
12%
Test Statistic
25%
Variance
12%
Weight Function
25%
Engineering
Anisotropic
12%
Boundary Value
25%
Bridging
50%
Broader Class
10%
Closed Form
10%
Data Point
50%
Double Precision
25%
Free Parameter
12%
Gaussian Kernel
12%
Gaussian Shape
12%
Gaussians
50%
Global Smoothing
50%
Invertibility
12%
Least Square
25%
Numerical Accuracy
12%
Numerical Example
25%
Random Shape
50%
Real Data
10%
Separation Distance
25%
Set Point
50%
Shape Parameter
100%
Simulation Result
10%
Statistical Distribution
12%
Sufficient Condition
12%
Weight Function
10%