R. M. Lark

Environmental Engineering · with Marchant · 2000–2021

A researcher in the Science corpus: 16 papers; trusts 34 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 46 citations into it; #151 of 5,479 by trust here, #560 by citations
• Artificial Intelligence — 18 citations into it; #7,670 of 35,345 by trust here, #13,163 by citations
• Statistics and Probability — 15 citations into it
• Ecology — 11 citations into it
• Economics and Econometrics — 11 citations into it; #9,763 of 23,481 by trust here, #10,133 by citations
• Civil and Structural Engineering — 10 citations into it; #784 of 6,160 by trust here, #3,655 by citations
• Global and Planetary Change — 10 citations into it
• Management, Monitoring, Policy and Law — 5 citations into it; #222 of 2,821 by trust here, #1,579 by citations

Whom R. M. Lark trusts overall

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

1. D. Higdon
2. Montserrat Fuentes
3. Peter J. Diggle
4. Budiman Minasny
5. Michael L. Stein
6. Michael E. Hohn
7. Richard Webster
8. Peter Guttorp
9. Ricardo A. Olea
10. Sue J. Welham

Who trusts R. M. Lark overall

1. Michael L. Stein
2. B. P. Marchant
3. Margaret A. Oliver
4. Hao Zhang
5. Richard Webster
6. Gerard B. M. Heuvelink
7. Budiman Minasny
8. Jin Li
9. M. Chipeta
10. Tomislav Hengl

Papers from R. M. Lark's perspective

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

1. Geostatistics for Natural Resources Evaluation
2. Modern Spatiotemporal Geostatistics
3. Nonparametric Estimation of Nonstationary Spatial Covariance Structure
4. A process-convolution approach to modelling temperatures in the North Atlantic Ocean
5. Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood
6. Applied Regression Including Computing and Graphics
7. Estimating variograms of soil properties by the method‐of‐moments and maximum likelihood
8. Ten Lectures on Wavelets
9. Spectral methods for nonstationary spatial processes
10. Approximating likelihoods for large spatial data sets

Their papers

• Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood (2002) — 164 citations
• On spatial prediction of soil properties in the presence of a spatial trend: the empirical best linear unbiased predictor (E‐BLUP) with REML (2006) — 268 citations
• Performance of linear mixed models and random forests for spatial prediction of soil pH (2021) — 50 citations
• Towards soil geostatistics (2012) — 67 citations
• Spatial prediction of soil properties with copulas (2011) — 54 citations
• Kriging a soil variable with a simple nonstationary variance model (2009) — 65 citations
• The Matérn variogram model: Implications for uncertainty propagation and sampling in geostatistical surveys (2007) — 56 citations
• Robust estimation of the variogram by residual maximum likelihood (2007) — 65 citations
• Cokriging particle size fractions of the soil (2007) — 88 citations
• Optimized Sample Schemes for Geostatistical Surveys (2007) — 83 citations
• The geostatistical analysis of experiments at the landscape-scale (2006) — 63 citations
• Carbon losses from all soils across England and Wales 1978–2003 (2005) — 1,189 citations
• Mapping risk of soil nutrient deficiency or excess by disjunctive and indicator kriging (2004) — 88 citations
• Estimating Variogram Uncertainty (2004) — 68 citations
• Changes in variance and correlation of soil properties with scale and location: analysis using an adapted maximal overlap discrete wavelet transform (2001) — 92 citations
• Estimating variograms of soil properties by the method‐of‐moments and maximum likelihood (2000) — 187 citations