R. Chandler

Ecology · 2011–2015

A researcher in the Science corpus: 9 papers; trusts 24 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Ecology — 79 citations into it; #687 of 10,717 by trust here, #2,548 by citations
• Nature and Landscape Conservation — 39 citations into it; #686 of 6,941 by trust here, #1,729 by citations
• Statistics and Probability — 39 citations into it; #11,815 of 12,932 by trust here, #6,552 by citations
• Ecological Modeling — 32 citations into it; #252 of 2,530 by trust here, #644 by citations
• Global and Planetary Change — 16 citations into it
• Artificial Intelligence — 10 citations into it
• Genetics — 8 citations into it
• Epidemiology — 7 citations into it

Whom R. Chandler trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. J. Andrew Royle
2. M. Efford
3. D. MacKenzie
4. D. Higdon
5. James D. Nichols
6. David L. Borchers
7. Andrew Gelman
8. Donald B. Rubin
9. Steven J. Phillips
10. Marc Kéry

Who trusts R. Chandler overall

1. G. Guillera‐Arroita
2. Jonas Knape
3. B. Augustine
4. J. Andrew Royle
5. Elise F. Zipkin
6. Marconi Campos‐Cerqueira
7. J. Ibarra
8. M. Merrick
9. Emad Kaky
10. Marc Kéry

Papers from R. Chandler's perspective

Ordered by how strongly the researchers R. Chandler trusts endorse each paper. Same corpus, a different order for every researcher.

1. Introduction to distance sampling : estimating abundance of biological populations
2. Generalized Linear Models
3. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence
4. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
5. Modelling distribution and abundance with presence‐only data
6. Density estimation in live‐trapping studies
7. Regression Shrinkage and Selection via the Lasso
8. A statistical explanation of MaxEnt for ecologists
9. Spatially Explicit Maximum Likelihood Methods for Capture–Recapture Studies (Biometrics)
10. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. (Ecological Applications)

Their papers

• Spatially explicit models for inference about density in unmarked or partially marked populations (2011) — 299 citations
• Spatial occupancy models for predicting metapopulation dynamics and viability following reintroduction (2015) — 98 citations
• Improved state-space models for inference about spatial and temporal variation in abundance from count data (2015) — 132 citations
• Spatially explicit integrated population models (2014) — 145 citations
• Using multiple data sources provides density estimates for endangered Florida panther (2013) — 89 citations
• Presence‐only modelling using MAXENT: when can we trust the inferences? (2013) — 762 citations
• Likelihood analysis of species occurrence probability from presence‐only data for modelling species distributions (2012) — 433 citations
• unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance (2011) — 2,252 citations
• Habitat quality and habitat selection of golden-winged warblers in Costa Rica: an application of hierarchical models for open populations (2011) — 85 citations