Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Paige, John"'
Anonymizing the GPS locations of observations can bias a spatial model's parameter estimates and attenuate spatial predictions when improperly accounted for, and is relevant in applications from public health to paleoseismology. In this work, we demo
Externí odkaz:
http://arxiv.org/abs/2405.04928
Producing subnational estimates of the under-five mortality rate (U5MR) is a vital goal for the United Nations to reduce inequalities in mortality and well-being across the globe. There is a great disparity in U5MR between high-income and Low-and-Mid
Externí odkaz:
http://arxiv.org/abs/2309.02093
The R-package GeoAdjust https://github.com/umut-altay/GeoAdjust-package implements fast empirical Bayesian geostatistical inference for household survey data from the Demographic and Health Surveys Program (DHS) using Template Model Builder (TMB). DH
Externí odkaz:
http://arxiv.org/abs/2303.12668
Fine-scale covariate rasters are routinely used in geostatistical models for mapping demographic and health indicators based on household surveys from the Demographic and Health Surveys (DHS) program. However, the geostatistical analyses ignore the f
Externí odkaz:
http://arxiv.org/abs/2211.07442
Spatial aggregation with respect to a population distribution involves estimating aggregate quantities for a population based on an observation of individuals in a subpopulation. In this context, a geostatistical workflow must account for three major
Externí odkaz:
http://arxiv.org/abs/2207.06700
Household survey data from the Demographic and Health Surveys (DHS) Program is published with GPS coordinates. However, almost all geostatistical analyses of such data ignore that the published GPS coordinates are randomly displaced (jittered). In th
Externí odkaz:
http://arxiv.org/abs/2202.11035
Autor:
Li, Zehang Richard, Martin, Bryan D, Dong, Tracy Qi, Fuglstad, Geir-Arne, Paige, John, Riebler, Andrea, Clark, Samuel, Wakefield, Jon
The increasing availability of complex survey data, and the continued need for estimates of demographic and health indicators at a fine spatial and temporal scale, which leads to issues of data sparsity, has led to the need for spatio-temporal smooth
Externí odkaz:
http://arxiv.org/abs/2007.05117
Current implementations of multiresolution methods are limited in terms of possible types of responses and approaches to inference. We provide a multiresolution approach for spatial analysis of non-Gaussian responses using latent Gaussian models and
Externí odkaz:
http://arxiv.org/abs/2005.11805