Improving the performance of predictive process modeling for large datasets

Computational Statistics and Data Analysis

Volumn 53, Issue 8, 2009, Pages 2873-2884

  Finley, Andrew O ^a   Sang, Huiyan ^b   Banerjee, Sudipto ^c   Gelfand, Alan E ^b  

^a MICHIGAN STATE UNIVERSITY   (United States)

^b Duke University   (United States)

^c UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GLOBAL POSITIONING SYSTEM; LOCATION; MARKOV PROCESSES;

DATA SETS; GEO CODING; GEOGRAPHICAL INFORMATION SYSTEMS; GLOBAL POSITIONING; KRIGING; LARGE DATA SETS; MARKOV CHAIN MONTE CARLO METHODS; POSITIVE BIAS; PREDICTIVE PROCESS; RANDOM EFFECTS MODELS; SCIENTIFIC DATUM; SPATIAL DATA SETS; SPATIAL DATUM; SPATIAL ERRORS; SPATIAL MODELING; SPATIAL REGRESSIONS; SPATIAL TEMPORALS; STATISTICAL MODELING;

MONTE CARLO METHODS;

EID: 62849106305     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2008.09.008     Document Type: Article

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