A design-based individual prediction approach is developed based on the
...
Node embedding is a central topic in graph representation learning.
Comp...
We develop lagged Metropolis-Hastings walk for sampling from simple
undi...
Census 2021 may well be the last of its kind in the UK. For provision of...
We propose a family of lagged random walk sampling methods in simple
und...
Intuitively, sampling is likely to be more efficient for prevalence
esti...
By record linkage one joins records residing in separate files which are...
Generalised regression estimation allows one to make use of available
au...
Bipartite incidence graph sampling provides a unified representation of ...
Design-consistent model-assisted estimation has become the standard prac...
Graph sampling is a statistical approach to study real graphs, which
rep...
Purchase data from retail chains provide proxy measures of private house...
Using social media data for statistical analysis of general population f...
We examine the conditions under which descriptive inference can be based...
Estimates based on 2x2 tables of frequencies are widely used in statisti...