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2009, 2nd ed., Use R!, ISBN 9780387922973, xii, 298
.... This book introduces Bayesian modeling by the use of computation using the R language. The new edition contains changes in the R code illustrations. 
Bayesian statistical decision theory | Data processing | R (Computer program language) | Mathematical Software | Visualization | Computational Mathematics and Numerical Analysis | Probability Theory and Stochastic Processes | Statistical Theory and Methods | Simulation and Modeling | Mathematics
Book
Journal of the Royal Statistical Society. Series B, Statistical methodology, ISSN 1369-7412, 2012, Volume 74, Issue 3, pp. 419 - 474
Journal Article
Journal Article
2009, 2nd ed., Use R., ISBN 9780387922973, xii, 300
Book
Annual review of ecology, evolution, and systematics, ISSN 1543-592X, 12/2010, Volume 41, Issue 1, pp. 379 - 406
In the past 10years a statistical technique, approximate Bayesian computation (ABC), has been developed that can be used to infer parameters and choose... 
Monte Carlo | Bayesian inference | simulation | Ecological modeling | Approximation | Demography | Evolutionary genetics | Inference | Descriptive statistics | Parametric models | Population genetics | Modeling | Human genetics | Bayesian statistical decision theory | Satellite DNA | Usage | Research | Human ecology | Environmental sciences | Genetic research | Analysis
Journal Article
Water Resources Research, ISSN 0043-1397, 07/2013, Volume 49, Issue 7, pp. 4335 - 4345
The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has... 
computational statistics | rainfall‐runoff transformation | approximate Bayesian computation | hydrologic modeling | rainfall-runoff transformation | ENVIRONMENTAL SCIENCES | PARAMETER-ESTIMATION | EQUIFINALITY | INPUT UNCERTAINTY | WATER RESOURCES | LIMNOLOGY | BASEFLOW | CHAIN MONTE-CARLO | Bayesian analysis | Models
Journal Article
2007, Oxford Series in Cognitive Development, ISBN 0195176804, x, 358
The world has a causal structure, in the sense that some events make other events happen. Although understanding causal structure is essential for predicting... 
Causation | Learning, Psychology of | Philosophy | developmental psychology | Causal knowledge | Concepts | Statistical learning | Bayes nets | Folk theories | Probabilistic models | Cognitive development | Bayesian inference | Causal learning | Causal models
Book
Current Opinion in Neurobiology, ISSN 0959-4388, 2009, Volume 19, Issue 4, pp. 452 - 458
Journal Article