By Dr Jakub Stoklosa

Journal articles

Hwang WH; Chen LF; Stoklosa J, 2024, 'Counting the Unseen: Estimation of Susceptibility Proportions in Zero-Inflated Models Using a Conditional Likelihood Approach', American Statistician, 78, pp. 161 - 170, http://dx.doi.org/10.1080/00031305.2023.2249529

Dovers E; Stoklosa J; Warton DI, 2024, 'Fitting Log-Gaussian Cox Processes Using Generalized Additive Model Software', American Statistician, 78, pp. 418 - 425, http://dx.doi.org/10.1080/00031305.2024.2316725

Stoklosa J; Hwang WH; Warton DI, 2023, 'A general algorithm for error-in-variables regression modelling using Monte Carlo expectation maximization', PLoS ONE, 18, http://dx.doi.org/10.1371/journal.pone.0283798

Hwang WH; Huggins R; Stoklosa J, 2022, 'A model for analyzing clustered occurrence data', Biometrics, 78, pp. 598 - 611, http://dx.doi.org/10.1111/biom.13435

Hwang WH; Stoklosa J; Wang CY, 2022, 'Population Size Estimation Using Zero-Truncated Poisson Regression with Measurement Error', Journal of Agricultural, Biological, and Environmental Statistics, 27, pp. 303 - 320, http://dx.doi.org/10.1007/s13253-021-00481-z

Stoklosa J; Blakey RV; Hui FKC, 2022, 'An Overview of Modern Applications of Negative Binomial Modelling in Ecology and Biodiversity', Diversity, 14, http://dx.doi.org/10.3390/d14050320

Noghrehchi F; Stoklosa J; Penev S; Warton DI, 2021, 'Selecting the model for multiple imputation of missing data: Just use an IC!', Statistics in Medicine, 40, pp. 2467 - 2497, http://dx.doi.org/10.1002/sim.8915

Noghrehchi F; Stoklosa J; Penev S, 2020, 'Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables', Computational Statistics, 35, pp. 1291 - 1317, http://dx.doi.org/10.1007/s00180-020-00976-2

Hwang WH; Blakey RV; Stoklosa J, 2020, 'Right-Censored Mixed Poisson Count Models with Detection Times', Journal of Agricultural, Biological, and Environmental Statistics, 25, pp. 112 - 132, http://dx.doi.org/10.1007/s13253-019-00381-3

Hwang WH; Heinze D; Stoklosa J, 2019, 'A weighted partial likelihood approach for zero-truncated models', Biometrical Journal, 61, pp. 1073 - 1087, http://dx.doi.org/10.1002/bimj.201800328

Stoklosa J; Lee SM; Hwang WH, 2019, 'Closed population capture–recapture models with measurement error and missing observations in covariates', Statistica Sinica, 29, pp. 589 - 610, http://dx.doi.org/10.5705/ss.202017.0088

Huggins R; Hwang WH; Stoklosa J, 2018, 'Estimation of abundance from presence–absence maps using cluster models', Environmental and Ecological Statistics, 25, pp. 495 - 522, http://dx.doi.org/10.1007/s10651-018-0415-5

Huggins R; Stoklosa J; Roach C; Yip P, 2018, 'Estimating the size of an open population using sparse capture–recapture data', Biometrics, 74, pp. 280 - 288, http://dx.doi.org/10.1111/biom.12718

Stoklosa J; Warton DI, 2018, 'A Generalized Estimating Equation Approach to Multivariate Adaptive Regression Splines', Journal of Computational and Graphical Statistics, 27, pp. 245 - 253, http://dx.doi.org/10.1080/10618600.2017.1360780

Weeks AR; Heinze D; Perrin L; Stoklosa J; Hoffmann AA; Van Rooyen A; Kelly T; Mansergh I, 2017, 'Genetic rescue increases fitness and AIDS rapid recovery of an endangered marsupial population', Nature Communications, 8, http://dx.doi.org/10.1038/s41467-017-01182-3

Blakey RV; Kingsford RT; Law BS; Stoklosa J, 2017, 'Floodplain habitat is disproportionately important for bats in a large river basin', Biological Conservation, 215, pp. 1 - 10, http://dx.doi.org/10.1016/j.biocon.2017.08.030

Blakey RV; Law BS; Kingsford RT; Stoklosa J, 2017, 'Terrestrial laser scanning reveals below-canopy bat trait relationships with forest structure', Remote Sensing of Environment, 198, pp. 40 - 51, http://dx.doi.org/10.1016/j.rse.2017.05.038

Dawson SK; Kingsford RT; Berney P; Catford JA; Keith DA; Stoklosa J; Hemmings FA, 2017, 'Contrasting influences of inundation and land use on the rate of floodplain restoration', Aquatic Conservation: Marine and Freshwater Ecosystems, 27, pp. 663 - 674, http://dx.doi.org/10.1002/aqc.2749

Warton DI; Stoklosa J; Guillera-Arroita G; MacKenzie DI; Welsh AH, 2017, 'Graphical diagnostics for occupancy models with imperfect detection', Methods in Ecology and Evolution, 8, pp. 408 - 419, http://dx.doi.org/10.1111/2041-210X.12761

Stoklosa J, 2017, 'Book Review', Australian & New Zealand Journal of Statistics, 59, pp. 151 - 152, http://dx.doi.org/10.1111/anzs.12174

Blakey RV; Law BS; Kingsford RT; Stoklosa J; Tap P; Williamson K, 2016, 'Bat communities respond positively to large-scale thinning of forest regrowth', Journal of Applied Ecology, 53, pp. 1694 - 1703, http://dx.doi.org/10.1111/1365-2664.12691

Hwang WH; Huggins R; Stoklosa J, 2016, 'Estimating negative binomial parameters from occurrence data with detection times', Biometrical Journal, 58, pp. 1409 - 1427, http://dx.doi.org/10.1002/bimj.201500239

Stoklosa J; Hwang WH; Yip PSF; Huggins RM, 2016, 'Accounting for contamination and outliers in covariates for open population capture-recapture models', Journal of Statistical Planning and Inference, 176, pp. 52 - 63, http://dx.doi.org/10.1016/j.jspi.2016.03.004

Warton DI; Lyons M; Stoklosa J; Ives AR, 2016, 'Three points to consider when choosing a LM or GLM test for count data', Methods in Ecology and Evolution, 7, pp. 882 - 890, http://dx.doi.org/10.1111/2041-210X.12552

Stoklosa J; Dann P; Huggins RM; Hwang WH, 2016, 'Estimation of survival and capture probabilities in open population capture-recapture models when covariates are subject to measurement error', Computational Statistics and Data Analysis, 96, pp. 74 - 86, http://dx.doi.org/10.1016/j.csda.2015.10.010

Huggins RM; Yip PSF; Stoklosa J, 2016, 'Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists', Australian and New Zealand Journal of Statistics, 58, pp. 1 - 13, http://dx.doi.org/10.1111/anzs.12149

Stoklosa J; Huang YH; Furlan E; Hwang WH, 2016, 'On quadratic logistic regression models when predictor variables are subject to measurement error', Computational Statistics and Data Analysis, 95, pp. 109 - 121, http://dx.doi.org/10.1016/j.csda.2015.09.012

Weeks AR; Stoklosa J; Hoffmann AA, 2016, 'Conservation of genetic uniqueness of populations may increase extinction likelihood of endangered species: The case of Australian mammals', Frontiers in Zoology, 13, http://dx.doi.org/10.1186/s12983-016-0163-z

Virah Sawmy M; Stoklosa J; Ebeling J, 2015, 'A probabilistic scenario approach for developing improved Reduced Emissions from Deforestation and Degradation (REDD+) baselines', Global Ecology and Conservation, 4, pp. 602 - 613, http://dx.doi.org/10.1016/j.gecco.2015.10.001

Warton DI; Foster SD; De’ath G; Stoklosa J; Dunstan PK, 2015, 'Model-based thinking for community ecology', Plant Ecology, 216, pp. 669 - 682, http://dx.doi.org/10.1007/s11258-014-0366-3

Yee TW; Stoklosa J; Huggins RM, 2015, 'The VGAM package for capture-recapture data using the conditional likelihood', Journal of Statistical Software, 65, pp. 1 - 33, http://dx.doi.org/10.18637/jss.v065.i05

Stoklosa J; Daly C; Foster SD; Ashcroft MB; Warton DI, 2015, 'A climate of uncertainty: Accounting for error in climate variables for species distribution models', Methods in Ecology and Evolution, 6, pp. 412 - 423, http://dx.doi.org/10.1111/2041-210X.12217

Gibb H; Stoklosa J; Warton DI; Brown AM; Andrew NR; Cunningham SA, 2015, 'Does morphology predict trophic position and habitat use of ant species and assemblages?', Oecologia, 177, pp. 519 - 531, http://dx.doi.org/10.1007/s00442-014-3101-9

Stoklosa J, 2015, 'Analysis of Capture–Recapture Data By R.S.McCreaB.J.T.MorganLondonChapman & Hall/CRC2014292 pages. UK £49.99 (hardback). ISBN 978‐1‐4398‐3659‐0', Australian & New Zealand Journal of Statistics, 57, pp. 572 - 574, http://dx.doi.org/10.1111/anzs.12134

Stoklosa J; Gibb H; Warton DI, 2014, 'Fast forward selection for generalized estimating equations with a large number of predictor variables', Biometrics, 70, pp. 110 - 120, http://dx.doi.org/10.1111/biom.12118

Stoklosa J; Dann P; Huggins R, 2014, 'Semivarying coefficient models for capture-recapture data: Colony size estimation for the little penguin Eudyptula minor', Mathematical Biosciences, 255, pp. 43 - 51, http://dx.doi.org/10.1016/j.mbs.2014.06.014

Huggins R; Stoklosa J, 2013, 'Semiparametric inference for open populations using the Jolly-Seber model: A penalized spline approach', Journal of Statistical Computation and Simulation, 83, pp. 1741 - 1755, http://dx.doi.org/10.1080/00949655.2012.668908

Stoklosa J; Dann P; Huggins R, 2012, 'Inference on Partially Observed Quasi-stationary Markov Chains With Applications to Multistate Population Models', Journal of Agricultural, Biological, and Environmental Statistics, 17, pp. 52 - 67, http://dx.doi.org/10.1007/s13253-011-0065-7

Furlan E; Stoklosa J; Griffiths J; Gust N; Ellis R; Huggins RM; Weeks AR, 2012, 'Small population size and extremely low levels of genetic diversity in island populations of the platypus, Ornithorhynchus anatinus', Ecology and Evolution, 2, pp. 844 - 857, http://dx.doi.org/10.1002/ece3.195

Stoklosa J; Huggins RM, 2012, 'A robust P-spline approach to closed population capture-recapture models with time dependence and heterogeneity', Computational Statistics and Data Analysis, 56, pp. 408 - 417, http://dx.doi.org/10.1016/j.csda.2011.08.004

Stoklosa J; Huggins RM, 2012, 'Cormack-Jolly-Seber model with environmental covariates: A P-spline approach', Biometrical Journal, 54, pp. 861 - 874, http://dx.doi.org/10.1002/bimj.201100215

Stoklosa J; Hwang WH; Wu SH; Huggins R, 2011, 'Heterogeneous capture-recapture models with covariates: A partial likelihood approach for closed populations', Biometrics, 67, pp. 1659 - 1665, http://dx.doi.org/10.1111/j.1541-0420.2011.01596.x

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