Jakub Stoklosa
Jakub Stoklosa
School of Mathematics and Statistics, University of New South Wales
Verified email at unsw.edu.au
Cited by
Cited by
Model-based thinking for community ecology
DI Warton, SD Foster, G De’ath, J Stoklosa, PK Dunstan
Plant Ecology 216 (5), 669-682, 2015
Small population size and extremely low levels of genetic diversity in island populations of the platypus, Ornithorhynchus anatinus
E Furlan, J Stoklosa, J Griffiths, N Gust, R Ellis, RM Huggins, AR Weeks
Ecology and Evolution 2 (4), 844-857, 2012
Three points to consider when choosing a LM or GLM test for count data
DI Warton, M Lyons, J Stoklosa, AR Ives
Methods in Ecology and Evolution 7 (8), 882-890, 2016
Does morphology predict trophic position and habitat use of ant species and assemblages?
H Gibb, J Stoklosa, DI Warton, AM Brown, NR Andrew, SA Cunningham
Oecologia 177 (2), 519-531, 2015
A climate of uncertainty: accounting for error in climate variables for species distribution models
J Stoklosa, C Daly, SD Foster, MB Ashcroft, DI Warton
Methods in Ecology and Evolution 6 (4), 412-423, 2015
Conservation of genetic uniqueness of populations may increase extinction likelihood of endangered species: the case of Australian mammals
AR Weeks, J Stoklosa, AA Hoffmann
Frontiers in Zoology 13 (1), 31, 2016
Genetic rescue increases fitness and aids rapid recovery of an endangered marsupial population
AR Weeks, D Heinze, L Perrin, J Stoklosa, AA Hoffmann, A van Rooyen, ...
Nature Communications 8 (1), 1-6, 2017
Bat communities respond positively to large‐scale thinning of forest regrowth
RV Blakey, BS Law, RT Kingsford, J Stoklosa, P Tap, K Williamson
Journal of Applied Ecology 53 (6), 1694-1703, 2016
The VGAM package for capture–recapture data using the conditional likelihood
TW Yee, J Stoklosa, RM Huggins
J. Statist. Soft 65 (5), 1-33, 2015
Graphical diagnostics for occupancy models with imperfect detection
DI Warton, J Stoklosa, G Guillera‐Arroita, DI MacKenzie, AH Welsh
Methods in Ecology and Evolution 8 (4), 408-419, 2017
A robust P-spline approach to closed population capture–recapture models with time dependence and heterogeneity
J Stoklosa, RM Huggins
Computational Statistics & Data Analysis 56 (2), 408-417, 2012
Heterogeneous capture–recapture models with covariates: A partial likelihood approach for closed populations
J Stoklosa, WH Hwang, SH Wu, R Huggins
Biometrics 67 (4), 1659-1665, 2011
Terrestrial laser scanning reveals below-canopy bat trait relationships with forest structure
RV Blakey, BS Law, RT Kingsford, J Stoklosa
Remote Sensing of Environment 198, 40-51, 2017
Fast forward selection for generalized estimating equations with a large number of predictor variables
J Stoklosa, H Gibb, DI Warton
Biometrics 70 (4), 110-120, 2014
Floodplain habitat is disproportionately important for bats in a large river basin
RV Blakey, RT Kingsford, BS Law, J Stoklosa
Biological Conservation 215, 1-10, 2017
Studies of barrier options and their sensitivities
J Stoklosa
The University of Melbourne, 2007
Contrasting influences of inundation and land use on the rate of floodplain restoration
SK Dawson, RT Kingsford, P Berney, JA Catford, DA Keith, J Stoklosa, ...
Aquatic Conservation: Marine and Freshwater Ecosystems 27 (3), 663-674, 2017
A probabilistic scenario approach for developing improved Reduced Emissions from Deforestation and Degradation (REDD+) baselines
M Virah-Sawmy, J Stoklosa, J Ebeling
Global Ecology and Conservation 4, 602-613, 2015
On quadratic logistic regression models when predictor variables are subject to measurement error
J Stoklosa, YH Huang, E Furlan, WH Hwang
Computational Statistics & Data Analysis 95, 109-121, 2016
Semiparametric inference for open populations using the Jolly–Seber model: A penalized spline approach
R Huggins, J Stoklosa
Journal of Statistical Computation and Simulation 83 (9), 1741-1755, 2013
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