S. Richards
Nature and Landscape Conservation · with Abrams · 2002–2014
A researcher in the Science corpus: 5 papers; trusts 28 researchers and is trusted by 64 researchers here, as inferred from the citation graph.
Subfields
- Nature and Landscape Conservation — 35 citations into it; #135 of 6,941 by trust here, #1,227 by citations
- Ecological Modeling — 28 citations into it; #62 of 2,530 by trust here, #707 by citations
- Ecology — 27 citations into it
- Ecology, Evolution, Behavior and Systematics — 14 citations into it; #2,352 of 6,648 by trust here, #1,975 by citations
- Statistics and Probability — 14 citations into it
- Artificial Intelligence — 9 citations into it
- Genetics — 8 citations into it
- Global and Planetary Change — 7 citations into it
Whom S. Richards trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- K. Burnham
- David R. Anderson
- Hirotogu Akaike
- Shinichi Nakagawa
- Huaiyu Zhu
- R. Freckleton
- Hirotugu Akaike
- L. Garamszegi
- Jennifer A. Hoeting
- Jerald B. Johnson
Who trusts S. Richards overall
- Matthew Symonds
- M. Galipaud
- Shinichi Nakagawa
- C. Grueber
- Harlan Campbell
- Eric J. Ward
- B. Coleman
- Mark A. F. Gillingham
- A. Moussalli
- Roger Mundry
Papers from S. Richards's perspective
Ordered by how strongly the researchers S. Richards trusts endorse each paper. Same corpus, a different order for every researcher.
- Null Hypothesis Testing: Problems, Prevalence, and an Alternative
- Why do we still use stepwise modelling in ecology and behaviour? (Journal of Animal Ecology)
- Dealing with collinearity in behavioural and ecological data: model averaging and the problems of measurement error (Behavioral Ecology and Sociobiology)
- Information Theory and an Extension of the Maximum Likelihood Principle
- Effect size, confidence interval and statistical significance: a practical guide for biologists (Biological Reviews of The Cambridge Philosophical Society)
- Information theory and hypothesis testing: a call for pluralism
- Ecological Models and Data in R
- Missing inaction: the dangers of ignoring missing data. (Trends in Ecology & Evolution)
- Kullback-Leibler information as a basis for strong inference in ecological studies
- Zero tolerance ecology: improving ecological inference by modelling the source of zero observations. (Ecology Letters)
Their papers
- Prevalence, thresholds and the performance of presence–absence models (2014) — 175 citations
- Model selection and model averaging in behavioural ecology: the utility of the IT-AIC framework (2010) — 522 citations
- Dealing with overdispersed count data in applied ecology (2007) — 648 citations
- TESTING ECOLOGICAL THEORY USING THE INFORMATION‐THEORETIC APPROACH: EXAMPLES AND CAUTIONARY RESULTS (2005) — 573 citations
- The interaction between predation and competition: a review and synthesis (2002) — 735 citations