Skip to main navigation
Skip to search
Skip to main content
Nazarbayev University Home
Home
Profiles
Research units
Projects
Research output
Activities
Search by expertise, name or affiliation
Enhanced conditional Co-Gibbs sampling algorithm for data imputation
Nasser Madani
, Talgatbek Bazarbekov
Nazarbayev University
Research output
:
Contribution to journal
›
Article
›
peer-review
4
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Enhanced conditional Co-Gibbs sampling algorithm for data imputation'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Cokriging
100%
Data Imputation
100%
Gibbs Sampling
100%
Gibbs Sampler
100%
Simple Kriging
75%
Auxiliary Variable
50%
Bivariate
50%
Variables of Interest
25%
Sampling Location
25%
Covariance Matrix
25%
Computer Software
25%
Spatial Correlation
25%
Zero Mean
25%
Random Vector
25%
Iterative Algorithm
25%
Collocated Cokriging
25%
Correlation Structure
25%
Executable File
25%
Gaussian Random Vector
25%
Vector Distribution
25%
Homotopic
25%
INIS
data
100%
algorithms
100%
sampling
100%
samplers
66%
kriging
50%
values
33%
vectors
33%
randomness
33%
performance
16%
simulation
16%
computers
16%
distribution
16%
computer codes
16%
correlations
16%
iterative methods
16%
matrices
16%
datasets
16%
Mathematics
Conditionals
100%
Gibbs Sampler
100%
Data Imputation
100%
Kriging
75%
Random Vector
50%
Auxiliary Variable
50%
Covariance Matrix
25%
Gaussian Distribution
25%
Bivariate
25%
Crosscorrelation
25%
Correlation Structure
25%
Bivariate Case
25%
Homotopic
25%