Computational Techniques for Spatial Logistic Regression with Large Datasets
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Bayesian Smoothing with Gaussian Processes Using Fourier Basis Functions in the spectralGP PackageHierarchical factor models for large spatially misaligned data: a low-rank predictive process approach.Hierarchical Multiresolution Approaches for Dense Point-Level Breast Cancer Treatment DataGaussian predictive process models for large spatial data sets.HIERARCHICAL SPATIAL MODELS FOR PREDICTING TREE SPECIES ASSEMBLAGES ACROSS LARGE DOMAINSMixtures of GAMs for habitat suitability analysis with overdispersed presence / absence data.Semiparametric regression during 2003-2007.Bayesian variable selection for multivariate spatially varying coefficient regression.The basis function approach for modeling autocorrelation in ecological data.Spatial Modelling Using a New Class of Nonstationary Covariance Functions.A cross-sectional and spatial analysis of the prevalence of multimorbidity and its association with socioeconomic disadvantage in South Africa: A comparison between 2008 and 2012Measurement error caused by spatial misalignment in environmental epidemiology.High Resolution Space-Time Ozone Modeling for Assessing Trends.Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets.Bayesian Modeling for Large Spatial Datasets.Approximate inference for disease mapping with sparse Gaussian processes.
P2860
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P2860
Computational Techniques for Spatial Logistic Regression with Large Datasets
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Computational Techniques for Spatial Logistic Regression with Large Datasets
@ast
Computational Techniques for Spatial Logistic Regression with Large Datasets
@en
type
label
Computational Techniques for Spatial Logistic Regression with Large Datasets
@ast
Computational Techniques for Spatial Logistic Regression with Large Datasets
@en
prefLabel
Computational Techniques for Spatial Logistic Regression with Large Datasets
@ast
Computational Techniques for Spatial Logistic Regression with Large Datasets
@en
P2860
P1476
Computational Techniques for Spatial Logistic Regression with Large Datasets
@en
P2093
Christopher J Paciorek
P2860
P304
P356
10.1016/J.CSDA.2006.11.008
P577
2007-05-01T00:00:00Z