Methods for estimating population density in data-limited areas: Evaluating regression and tree-based models in Peru

PLoS ONE

Volumn 9, Issue 7, 2014, Pages

  Anderson, Weston ^a,c   Guikema, Seth ^a   Zaitchik, Ben ^b   Pan, William ^d  

^a Johns Hopkins University   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE   (United States)

^d DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYESIAN ADDITIVE REGRESSION TREE; GENERALIZED ADDITIVE MODEL; LINEAR MIXED MODEL; MEASUREMENT ACCURACY; MULTIVARIATE ADAPTIVE REGRESSION SPLINE; PERU; POPULATION DENSITY; PREDICTION; RANDOM FOREST; REGRESSION ANALYSIS; STATISTICAL MODEL; BAYES THEOREM; EVALUATION STUDY; HUMAN; POPULATION RESEARCH; UNITED STATES;

BAYES THEOREM; CENSUSES; HUMANS; MODELS, STATISTICAL; PERU; POPULATION DENSITY; REGRESSION ANALYSIS; UNITED STATES;

EID: 84903779092     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0100037     Document Type: Article

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