Zobrazeno 1 - 10
of 794
pro vyhledávání: '"Raftery, A. E."'
Autor:
Susmann, Herbert, Raftery, Adrian E.
Estimates of future migration patterns are a crucial input to world population projections. Forced migration, including refugee and asylum seekers, plays an important role in overall migration patterns, but is notoriously difficult to forecast. We pr
Externí odkaz:
http://arxiv.org/abs/2405.06857
The link between age and migration propensity is long established, but existing models of country-level net migration ignore the effect of population age distribution on past and projected migration rates. We propose a method to estimate and forecast
Externí odkaz:
http://arxiv.org/abs/2403.05566
Autor:
Liu, Daphne H., Raftery, Adrian E.
International comparisons of hierarchical time series data sets based on survey data, such as annual country-level estimates of school enrollment rates, can suffer from large amounts of missing data due to differing coverage of surveys across countri
Externí odkaz:
http://arxiv.org/abs/2401.01872
Professor Adrian E. Raftery is the Boeing International Professor of Statistics and Sociology, and an adjunct professor of Atmospheric Sciences, at the University of Washington in Seattle. He was born in Dublin, Ireland, and obtained a B.A. in Mathem
Externí odkaz:
http://arxiv.org/abs/2310.11095
Autor:
Metodiev, Martin, Perrot-Dockès, Marie, Ouadah, Sarah, Irons, Nicholas J., Raftery, Adrian E.
We propose an easily computed estimator of marginal likelihoods from posterior simulation output, via reciprocal importance sampling, combining earlier proposals of DiCiccio et al (1997) and Robert and Wraith (2009). This involves only the unnormaliz
Externí odkaz:
http://arxiv.org/abs/2305.08952
In this chapter, we present a review of latent position models for networks. We review the recent literature in this area and illustrate the basic aspects and properties of this modeling framework. Through several illustrative examples we highlight h
Externí odkaz:
http://arxiv.org/abs/2304.02979
Multidimensional scaling (MDS) is a widely used approach to representing high-dimensional, dependent data. MDS works by assigning each observation a location on a low-dimensional geometric manifold, with distance on the manifold representing similari
Externí odkaz:
http://arxiv.org/abs/2210.15081
The bayesTFR package for R provides a set of functions to produce probabilistic projections of the total fertility rates (TFR) for all countries, and is widely used, including as part of the basis for the UN's official population projections for all
Externí odkaz:
http://arxiv.org/abs/2207.06593
Publikováno v:
Demography, 2023 Jun 01. 60(3), 915-937.
Externí odkaz:
https://www.jstor.org/stable/48728449
Autor:
Irons, Nicholas J., Raftery, Adrian E.
There are many sources of data giving information about the number of SARS-CoV-2 infections in the population, but all have major drawbacks, including biases and delayed reporting. For example, the number of confirmed cases largely underestimates the
Externí odkaz:
http://arxiv.org/abs/2102.10741