| Analysing point patterns on networks—A review A Baddeley, G Nair, S Rakshit, G McSwiggan, TM Davies Spatial Statistics 42, 100435, 2021 | 70 | 2021 |
| Fast kernel smoothing of point patterns on a large network using two‐dimensional convolution S Rakshit, T Davies, MM Moradi, G McSwiggan, G Nair, J Mateu, ... International Statistical Review 87 (3), 531-556, 2019 | 43 | 2019 |
| “Stationary” point processes are uncommon on linear networks A Baddeley, G Nair, S Rakshit, G McSwiggan Stat 6 (1), 68-78, 2017 | 37 | 2017 |
| Second-order analysis of point patterns on a network using any distance metric S Rakshit, G Nair, A Baddeley Spatial Statistics 22, 129-154, 2017 | 35 | 2017 |
| Efficient code for second order analysis of events on a linear network S Rakshit, A Baddeley, G Nair Journal of Statistical Software 90 (1), 1-37, 2019 | 28 | 2019 |
| On two-stage Monte Carlo tests of composite hypotheses A Baddeley, A Hardegen, T Lawrence, RK Milne, G Nair, S Rakshit Computational Statistics & Data Analysis 114, 75-87, 2017 | 20 | 2017 |
| Assessment of the use of geographically weighted regression for analysis of large on-farm experiments and implications for practical application FH Evans, A Recalde Salas, S Rakshit, CA Scanlan, SE Cook Agronomy 10 (11), 1720, 2020 | 18 | 2020 |
| Hierarchical clustering of MS/MS spectra from the firefly metabolome identifies new lucibufagin compounds C Rawlinson, D Jones, S Rakshit, S Meka, CS Moffat, P Moolhuijzen Scientific Reports 10 (1), 6043, 2020 | 15 | 2020 |
| Novel approach to the analysis of spatially-varying treatment effects in on-farm experiments S Rakshit, A Baddeley, K Stefanova, K Reeves, K Chen, Z Cao, F Evans, ... Field crops research 255, 107783, 2020 | 14 | 2020 |
| Fundamental problems in fitting spatial cluster process models A Baddeley, TM Davies, ML Hazelton, S Rakshit, R Turner Spatial Statistics 52, 100709, 2022 | 7 | 2022 |
| Variable selection using penalised likelihoods for point patterns on a linear network S Rakshit, G McSwiggan, G Nair, A Baddeley Australian & New Zealand Journal of Statistics 63 (3), 417-454, 2021 | 5 | 2021 |
| Optimal thresholding of predictors in mineral prospectivity analysis A Baddeley, W Brown, RK Milne, G Nair, S Rakshit, T Lawrence, A Phatak, ... Natural Resources Research 30 (2), 923-969, 2021 | 5 | 2021 |
| Diffusion smoothing for spatial point patterns A Baddeley, TM Davies, S Rakshit, G Nair, G McSwiggan Statistical Science 37 (1), 123-142, 2022 | 2 | 2022 |
| Bayesian inference of spatially correlated random parameters for on-farm experiment Z Cao, K Stefanova, M Gibberd, S Rakshit Field Crops Research 281, 108477, 2022 | 1 | 2022 |
| Spatial Dependency in Stubble-Borne Pyrenophora teres f. teres and Influence of Sample Support Size on DNA Concentration and Fungicide Resistance Frequency LM Hodgson, S Rakshit, FJ Lopez-Ruiz, MR Gibberd, GJ Thomas, ... Phytopathology® 114 (1), 269-281, 2024 | | 2024 |
| Package ‘spatstat. linnet’ MA Baddeley | | 2024 |
| Probabilistic approaches for investigating species co-occurrence from presence-absence maps YM Chang, S Rakshit, CH Huang, WH Wu PeerJ 11, e15907, 2023 | | 2023 |
| Statistical analysis of comparative experiments based on large strip on-farm trials KT Stefanova, J Brown, A Grose, Z Cao, K Chen, M Gibberd, S Rakshit Field Crops Research 297, 108945, 2023 | | 2023 |
| Optimal design for on-farm strip trials--systematic or randomised? Z Cao, A Grose, J Brown, S Rakshit arXiv preprint arXiv:2206.09528, 2022 | | 2022 |
| Fitting and simulating Neyman-Scott cluster process models A Baddeley, YM Chang, TM Davies, ML Hazelton, S Rakshit, TR Turner METMA X, 7, 0 | | |
