City Research Online

Items where Subject is "HA Statistics"

Up a level
Export as [feed] RSS 2.0 [feed] RSS
Group by: Authors | Type
Jump to: A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | R | S | T | V | W | X | Y | Z | Č
Number of items at this level: 165.

A

Aeberhard, W., Cantoni, E., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2021). Robust Fitting for Generalized Additive Models for Location, Scale and Shape. Statistics and Computing, 31, 11. doi: 10.1007/s11222-020-09979-x

Agbeko, T., Hiabu, M., Miranda, M. D. M. , Nielsen, J. P. & Verrall, R. J. (2014). Validating the double chain ladder stochastic claims reserving model. Variance: advancing the science of risk, 8(2), pp. 138-160.

Ahmadi, R. (2011). Stochastic modelling and maintenance optimization of systems subject to deterioration. (Unpublished Doctoral thesis, City University London)

Andersson, Neil (2013). Uncertainties in gender violence epidemiology. (Unpublished Doctoral thesis, City University London)

Argasinski, K. & Broom, M. ORCID: 0000-0002-1698-5495 (2021). Towards a replicator dynamics model of age structured populations. Journal of Mathematical Biology, 82(5), 44.. doi: 10.1007/s00285-021-01592-4

Asimit, A.V., Bignozzi, V., Cheung, K. C. , Hu, J. & Kim, E. (2017). Robust and Pareto Optimality of Insurance Contract. European Journal of Operational Research, 262(2), pp. 720-732. doi: 10.1016/j.ejor.2017.04.029

Asimit, A.V. & Li, J. (2017). Systemic Risk: An Asymptotic Evaluation. .

Asimit, V. ORCID: 0000-0002-7706-0066, Kyriakou, I. ORCID: 0000-0001-9592-596X, Santoni, S. ORCID: 0000-0002-5928-3901 , Scognamiglio, S. & Zhu, R. ORCID: 0000-0002-9944-0369 (2022). Robust Classification via Support Vector Machines. .

B

Beecham, R., Dykes, J. ORCID: 0000-0002-8096-5763, Rooney, C. & Wong, W. (2021). Design Exposition Discussion Documents for Rich Design Discourse in Applied Visualization. IEEE Transactions on Visualization and Computer Graphics, 27(8), pp. 3451-3462. doi: 10.1109/tvcg.2020.2979433

Beecham, R., Slingsby, A., Brunsdon, C. & Radburn, R. (2017). Spatially varying explanations behind the UKs vote to leave the EU. Paper presented at the 25th Geographical Information Science (GIS) Research UK Conference, 18 Apr 2017 - 21 Apr 2017, Manchester, UK.

Bergamelli, M., Bianchi, A., Khalaf, L. & Urga, G. (2019). Combining P-values to Test for Multiple Structural Breaks in Cointegrated Regressions. Journal of Econometrics, 211(2), pp. 461-482. doi: 10.1016/j.jeconom.2019.01.013

Biais, B., Mariotti, T., Rochet, J.C. & Villeneuve, S. (2010). Large risks, limited liability, and dynamic moral hazard. Econometrica, 78(1), pp. 73-118. doi: 10.3982/ECTA7261

Bischofberger, S., Hiabu, M., Mammen, E. & Nielsen, J. P. ORCID: 0000-0002-2798-0817 (2019). A comparison of in-sample forecasting methods. Computational Statistics and Data Analysis, 137, pp. 133-154. doi: 10.1016/j.csda.2019.02.009

Blake, D., Courbage, C., MacMinn, R. & Sherris, M. (2011). Longevity Risk and Capital Markets: The 2010-2011 Update. The Geneva Papers On Risk And Insurance: Issues And Practice, 36(4), doi: 10.1057/gpp.2011.27

Blake, D. & Hunt, A. (2016). Basis Risk and Pension Schemes: A Relative Modelling Approach (PI-1601). London, UK: Pensions Institute.

Bormetti, G., Casarin, R., Corsi, F. ORCID: 0000-0003-2683-4479 & Livieri, G. (2019). A Stochastic Volatility Model With Realized Measures for Option Pricing. Journal of Business & Economic Statistics, doi: 10.1080/07350015.2019.1604371

Bottoni, G. & Fitzgerald, R. (2021). Establishing a Baseline: Bringing Innovation to the Evaluation of Cross-National Probability-Based Online Panels. Survey Research Methods, 15(2), pp. 115-133. doi: 10.18148/srm/2021.v15i2.7457

Boyko, V., Dubrovina, N., Zamyatin, P. , Gerrard, R. J. G., Savvi, S., Lazirskiy, V., Ghydetskyy, V., Sinelnikov, A., Zamiatin, D., Kolesnikova, O. & Shaprynskyy, E. (2015). Epidemiology and Forecast of the Prevalence of Esophageal Cancer in the Countries of Central and Eastern Europe. Procedia Economics and Finance, 24, pp. 93-100. doi: 10.1016/S2212-5671(15)00622-X

Braumoeller, B. F., Marra, G., Radice, R. ORCID: 0000-0002-6316-3961 & Bradshaw, A. E. (2018). Flexible Causal Inference for Political Science. Political Analysis, 26(1), pp. 54-71. doi: 10.1017/pan.2017.29

Broom, M., Borries, C. & Koenig, A. (2004). Infanticide and infant defence by males--modelling the conditions in primate multi-male groups. Journal of Theoretical Biology, 231(2), pp. 261-270. doi: 10.1016/j.jtbi.2004.07.001

Broom, M., Cannings, C. & Vickers, G. T. (2000). Evolution in Knockout Contests: the Variable Strategy Case. Selection, 1, pp. 5-21.

Broom, M., Crowe, M. L., Fitzgerald, M. R. & Rychtar, J. (2010). The stochastic modelling of kleptoparasitism using a Markov process. Journal of Theoretical Biology, 264(2), pp. 266-272. doi: 10.1016/j.jtbi.2010.01.012

Broom, M., Hadjichrysanthou, C. & Rychtar, J. (2010). Evolutionary games on graphs and the speed of the evolutionary process. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 466(2117), pp. 1327-1346. doi: 10.1098/rspa.2009.0487

Broom, M., Hadjichrysanthou, C., Rychtar, J. & Stadler, B. T. (2010). Two results on evolutionary processes on general non-directed graphs. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 466(2121), pp. 2795-2798. doi: 10.1098/rspa.2010.0067

Broom, M. & Ruxton, G. D. (2004). A framework for modelling and analysing conspecific brood parasitism. Journal of Mathematical Biology, 48(5), pp. 529-544. doi: 10.1007/s00285-003-0244-4

Broom, M. & Rychtar, J. (2011). Kleptoparasitic melees--modelling food stealing featuring contests with multiple individuals.. Bulletin of Mathematical Biology, 73(3), pp. 683-699. doi: 10.1007/s11538-010-9546-z

Broom, M. & Rychtar, J. (2008). An analysis of the fixation probability of a mutant on special classes of non-directed graphs. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 464(2098), pp. 2609-2627. doi: 10.1098/rspa.2008.0058

Broom, M., Rychtar, J. & Stadler, B. (2009). Evolutionary Dynamics on Small-Order Graphs. Journal of Interdisciplinary Mathematics, 12, pp. 129-140.

Broom, M., Rychtar, J. & Sykes, C. (2008). The Evolution of Kleptoparasitism under Adaptive Dynamics Without Restriction. Journal of Interdisciplinary Mathematics, 11(4), pp. 479-494.

Broom, M., Speed, M. P. & Ruxton, G. D. (2005). Evolutionarily stable investment in secondary defences. Functional Ecology, 19(5), pp. 836-843. doi: 10.1111/j.1365-2435.2005.01030.x

C

Chawsheen, T.A. & Broom, M. (2017). Seasonal time-series modeling and forecasting of monthly mean temperature for decision making in the Kurdistan Region of Iraq. Journal of Statistical Theory and Practice, doi: 10.1080/15598608.2017.1292484

Ciulla, F., Mocanu, D., Baronchelli, A. , Gonçalves, B., Perra, N. & Vespignani, A. (2012). Beating the news using social media: the case study of American Idol. EPJ Data Science, 1(8), doi: 10.1140/epjds8

Cooper, C., Levay, P., Lorenc, T. & Craig, G. M. (2014). A population search filter for hard-to-reach populations increased search efficiency for a systematic review. Journal of Clinical Epidemiology, 67(5), pp. 554-559. doi: 10.1016/j.jclinepi.2013.12.006

Corte, P. D., Sarno, L. & Thornton, D. (2008). The Expectation Hypothesis of the Term Structure of Very Short-Term Rates: Statistical Tests and Economic Value. Journal of Financial Economics, 89(1), pp. 158-174. doi: 10.1016/j.jfineco.2007.08.002

Cowell, R. & Smith, J. Q. (2014). Causal discovery through MAP selection of stratified chain event graphs. Electronic Journal of Statistics, 8(1), pp. 965-997. doi: 10.1214/14-E4S917

Crook, J., Bellotti, T., Mues, C. & Fuertes, A-M. ORCID: 0000-0001-6468-9845 (2019). Preface to the papers on 'Credit risk modelling'. Journal of the Royal Statistical Society Series A, 182(4), pp. 1139-1142. doi: 10.1111/rssa.12525

D

D'Amato, V., Haberman, S. & Piscopo, G. (2017). The dependency premium based on a multifactor model for dependent mortality data. Communications in Statistics - Theory and Methods, doi: 10.1080/03610926.2017.1366523

Dagg, R.A. (1999). Optimal inspection and maintenance for stochastically deteriorating systems. (Unpublished Doctoral thesis, City University London)

Dash, J., Lankester, T., Hubbard, S. & Curran, P. J. (2008). Signal-to-noise ratio for MTCI and NDVI time series data. Proceedings of the 2nd MERIS/(A)ATSR User Workshop,

Datta-Nemdharry, P., Dattani, N. & Macfarlane, A. J. (2012). Linking maternity data for Wales, 2005-07: methods and data quality. Health Statistics Quarterly, 54, pp. 1-24.

Dattani, N., Datta-Nemdharry, P. & Macfarlane, A. J. (2012). Linking maternity data for England 2007: methods and data quality. Health Statistics Quarterly, 53, pp. 4-21.

Della Corte, P., Sarno, L. & Thornton, D. L. (2007). The Expectation Hypothesis of the Term Structure of Very Short-Term Rates: Statistical Tests and Economic Value (6445). Centre for Economic Policy Research.

Dettoni, R., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2020). Generalized Link-Based Additive Survival Models with Informative Censoring. Journal of Computational and Graphical Statistics, doi: 10.1080/10618600.2020.1724544

Dimitrova, D. S., Ignatov, Z. G. & Kaishev, V. K. (2017). On the First Crossing of Two Boundaries by an Order Statistics Risk Process. Risks, 5(3), 43.. doi: 10.3390/risks5030043

Dimitrova, D. S., Kaishev, V. K. & Haberman, S. (2014). Improved estimation of mortality and life expectancy for each constituent country of the UK and beyond. Research Excellence Framework (REF).

Dimitrova, D. S. ORCID: 0000-0003-3169-2735, Kaishev, V. K. & Ignatov, Z. G. (2018). Ruin and Deficit Under Claim Arrivals with the Order Statistics Property. Methodology and Computing in Applied Probability, doi: 10.1007/s11009-018-9669-5

E

Eletti, A., Marra, G., Quaresma, M. , Radice, R. ORCID: 0000-0002-6316-3961 & Rubio, F. J. (2022). A Unifying Framework for Flexible Excess Hazard Modeling with Applications in Cancer Epidemiology. Journal of the Royal Statistical Society Series C: Applied Statistics, doi: 10.1111/rssc.12566

Endress, A., Slone, L. K. & Johnson, S. P. (2020). Statistical learning and memory. Cognition, 204, 104346.. doi: 10.1016/j.cognition.2020.104346

F

Fanslow, J., Gulliver, P., Hashemi, L. ORCID: 0000-0001-6449-3834 , Malihi, Z. & McIntosh, T. (2021). Methods for the 2019 New Zealand family violence study- a study on the association between violence exposure, health and well-being. Kōtuitui: New Zealand Journal of Social Sciences Online, 16(1), pp. 196-209. doi: 10.1080/1177083x.2020.1862252

Fanslow, J., Malihi, Z., Hashemi, L. ORCID: 0000-0001-6449-3834 , Gulliver, P. & McIntosh, T. (2021). Change in prevalence of psychological and economic abuse, and controlling behaviours against women by an intimate partner in two cross-sectional studies in New Zealand, 2003 and 2019. BMJ Open, 11(3), e044910. doi: 10.1136/bmjopen-2020-044910

Fanslow, J. L., Malihi, Z., Hashemi, L. ORCID: 0000-0001-6449-3834 , Gulliver, P. & McIntosh, T. (2022). Prevalence of interpersonal violence against women and men in New Zealand: results of a cross-sectional study. Australian and New Zealand Journal of Public Health, doi: 10.1111/1753-6405.13206

Fanslow, J. L., Malihi, Z. A,, Hashemi, L. ORCID: 0000-0001-6449-3834 , Gulliver, P. & McIntosh, T. (2021). Lifetime Prevalence of Intimate Partner Violence and Disability: Results From a Population-Based Study in New Zealand. American Journal of Preventive Medicine, 61(3), pp. 320-328. doi: 10.1016/j.amepre.2021.02.022

Filippou, P., Kneib, T., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2018). A trivariate additive regression model with arbitrary link functions and varying correlation matrix. Journal of Statistical Planning and Inference, 199, pp. 236-248. doi: 10.1016/j.jspi.2018.07.002

Filippou, P., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2017). Penalized likelihood estimation of a trivariate additive probit model. Biostatistics, 18(3), pp. 569-585. doi: 10.1093/biostatistics/kxx008

Fitzgerald, R., Widdop, S., Gray, M. & Collins, D. (2011). Identifying sources of error in cross-national questionnaires: Application of an error source typology to cognitive interview data. Journal of Official Statistics, 27(4), pp. 569-599.

Fujiki, M.H. (1994). Pension fund valuation. (Unpublished Doctoral thesis, City University London)

Fusai, G. (2000). Corridor options and arc-sine law. ANNALS OF APPLIED PROBABILITY, 10(2), pp. 634-663.

G

Gallus, C., Blasiak, P. & Pothos, E. M. ORCID: 0000-0003-1919-387X (2022). Quantifying and Interpreting Connection Strength in Macroand Microscopic Systems: Lessons from Bell’s Approach. Entropy, 24, 364. doi: 10.3390/e24030364

Gambaro, A. M., Kyriakou, I. ORCID: 0000-0001-9592-596X & Fusai, G. ORCID: 0000-0001-9215-2586 (2020). General lattice methods for arithmetic Asian options. European Journal of Operational Research, 282(3), pp. 1185-1199. doi: 10.1016/j.ejor.2019.10.026

Gandrud, C. (2015). simPH: An R package for illustrating estimates from cox proportional hazard models including for interactive and nonlinear effects. Journal of Statistical Software, 65(3), doi: 10.18637/jss.v065.i03

Gomes, M., Radice, R., Camarena Brenes, J. & Marra, G. (2019). Copula selection models for non-Gaussian responses that are missing not at random. Statistics in Medicine, 38(3), pp. 480-496. doi: 10.1002/sim.7988

Gong, Y., Zhu, H., Miranda, M. A. , Crabb, D. P. ORCID: 0000-0001-8754-3902, Yang, H., Bi, W. & Garway-Heath, D. F. (2021). Trail-Traced Threshold Test (T4) with a Weighted Binomial Distribution for a Psychophysical Test. IEEE Journal of Biomedical and Health Informatics, 25(7), pp. 2787-2800. doi: 10.1109/JBHI.2021.3057437

Gonzalez-Manteiga, W, Borrajo, MI & Martinez-Miranda, M. D. (2017). Bandwidth selection for kernel density estimation with length-biased data. Journal of Nonparametric Statistics, 29(3), pp. 636-668. doi: 10.1080/10485252.2017.1339309

González-Manteiga, W., Martinez-Miranda, M. D. & Van Keilegom, I. (2016). Goodness-of-fit test in parametric mixed effects models based on estimation of the error distribution. Biometrika, 103(1), pp. 133-146. doi: 10.1093/biomet/asv061

Guilbeault, D., Baronchelli, A. ORCID: 0000-0002-0255-0829 & Centola, D. (2021). Experimental evidence for scale-induced category convergence across populations. Nature Communications, 12(1), 327.. doi: 10.1038/s41467-020-20037-y

Gámiz Pérez, M. L., Mammen, E., Martinez-Miranda, M. D. & Nielsen, J. P. ORCID: 0000-0002-2798-0817 (2022). Missing link survival analysis with applications to available pandemic data. Computational Statistics & Data Analysis, 169, 107405. doi: 10.1016/j.csda.2021.107405

H

Haberman, S., Ntamjokouen, A. & Consigli, G. (2017). Projecting the long run relationship of multi-population life expectancy by race. Journal of Statistical and Econometric Methods, 6(2), pp. 43-68.

Haberman, S. ORCID: 0000-0003-2269-9759 & Shang, H.L. (2018). Model confidence sets and forecast combination: an application to age-specific mortality. Genus, 74(19), doi: 10.1186/s41118-018-0043-9

Hanson, T. (2016). How Should We Adapt Complex Social Research Questionnaires for Mobile Devices? Evidence from UK Surveys and Experiments. Paper presented at the 2016 International Conference on Questionnaire Design, Development, Evaluation, and Testing (QDET2), 9-13 Nov 2016, Miami, USA.

Hanson, T., McGee, A. & Taylor, L. A. (2019). Do we know what to do with "Don't Know"?. Paper presented at the 2019 European Survey Research Association Conference, 15-19 Jul 2019, Zagreb, Croatia.

Hanson, T., McGee, A. & Taylor, L. A. (2019). Do we know what to do with “Don’t Know”?. Paper presented at the 2019 General Online Research Conference, 7-8 Mar 2019, Cologne, Germany.

Harper, G. (2017). A study of the use of linked routinely collected administrative data at the local level to count and profile populations. (Unpublished Doctoral thesis, City, University of London)

Harper, G. & Mayhew, L. (2012). Applications of Population Counts Based on Administrative Data at Local Level. Applied Spatial Analysis and Policy, 5(3), pp. 183-209. doi: 10.1007/s12061-011-9062-z

Harper, G. & Mayhew, L. (2012). Using Administrative Data to Count Local Populations. Applied Spatial Analysis and Policy, 5(2), pp. 97-122. doi: 10.1007/s12061-011-9063-y

Harper, G. & Mayhew, L. (2016). Using Administrative Data to Count and Classify Households with Local Applications. Applied Spatial Analysis and Policy, 9(4), pp. 433-462. doi: 10.1007/s12061-015-9162-2

Harrison, M. D. & Broom, M. (2009). A game-theoretic model of interspecific brood parasitism with sequential decisions. Journal of Theoretical Biology, 256(4), pp. 504-517. doi: 10.1016/j.jtbi.2008.08.033

Hashemi, L. ORCID: 0000-0001-6449-3834, Fanslow, J., Gulliver, P. & McIntosh, T. (2021). Exploring the health burden of cumulative and specific adverse childhood experiences in New Zealand: Results from a population-based study. Child Abuse and Neglect, 122, 105372. doi: 10.1016/j.chiabu.2021.105372

Hashemi, L. ORCID: 0000-0001-6449-3834, Fanslow, J. L., Gulliver, P. & McIntosh, T. (2021). Relational Mobility and Other Contributors to Decline in Intimate Partner Violence. Journal of Interpersonal Violence, doi: 10.1177/08862605211055193

Hashim, N., Scopelliti, I. ORCID: 0000-0001-6712-5332 & Steinmetz, J. ORCID: 0000-0003-3299-4858 (2021). Gamification Can Help Consumers Reach Their Saving Goals. Think Forward Initiative.

Hatzopoulos, P. & Haberman, S. (2013). Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data. Insurance: Mathematics and Economics, 52(2), pp. 320-337. doi: 10.1016/j.insmatheco.2012.12.009

Hiabu, M. (2016). In-sample forecasting: structured models and reserving. (Unpublished Doctoral thesis, City, University of London)

Hiabu, M. (2016). On the relationship between classical chain ladder and granular reserving. Scandinavian Actuarial Journal, 2017(8), pp. 708-729. doi: 10.1080/03461238.2016.1240709

Hiabu, M., Mammen, E., Martinez-Miranda, M. D. & Nielsen, J. P. (2016). In-Sample Forecasting with Local Linear Survival Densities. Biometrika, 103(4), pp. 843-859. doi: 10.1093/biomet/asw038

I

Ieva, F., Marra, G., Paganoni, A. M. & Radice, R. ORCID: 0000-0002-6316-3961 (2014). A Semiparametric Bivariate Probit Model for Joint Modeling of Outcomes in STEMI Patients. Computational and Mathematical Methods in Medicine, 2014, 240435.. doi: 10.1155/2014/240435

J

Jones, P. R. ORCID: 0000-0001-7672-8397 (2016). A note on detecting statistical outliers in psychophysical data (10.1101/074591). .

Jones, P. R. ORCID: 0000-0001-7672-8397 (2019). A note on detecting statistical outliers in psychophysical data. Attention, Perception, and Psychophysics, 81(5), pp. 1189-1196. doi: 10.3758/s13414-019-01726-3

K

Kaiksow, W.A. (1999). Labour supply problems and solutions: econometric model for the State of Bahrain. (Unpublished Doctoral thesis, City University London)

Kaishev, V. K., Dimitrova, D. S., Haberman, S. & Verrall, R. J. (2006). Geometrically Designed, Variable Knot Regression Splines: Asymptotics and Inference (Statistical Research Paper No. 28). Cass Business School, City University, London.

Keogh, B., Daly, L., Sharek, D. , De Vries, J., McCann, E. ORCID: 0000-0003-3548-4204 & Higgins, A. (2016). Sexual health promotion programme: Participants' perspectives on capacity building. Health Education Journal, 75(1), pp. 47-60. doi: 10.1177/0017896914563320

Khadjesari, Z., Boufkhed, S., Vitoratou, S. , Schatte, L., Ziemann, A. ORCID: 0000-0002-5996-8484, Daskalopoulou, C., Uglik-Marucha, E., Sevdalis, N. & Hull, L. (2020). Implementation outcome instruments for use in physical healthcare settings: a systematic review. Implementation Science, 15(1), 66.. doi: 10.1186/s13012-020-01027-6

Klein, N., Kneib, T., Marra, G. , Radice, R., Rokicki, S. R. & McGovern, M. (2019). Mixed Binary-Continuous Copula Regression Models with Application to Adverse Birth Outcomes. Statistics in Medicine, 38(3), pp. 413-436. doi: 10.1002/sim.7985

Kreif, N., Gruber, S., Radice, R. ORCID: 0000-0002-6316-3961 , Grieve, R. & Sekhon, J. S. (2016). Evaluating treatment effectiveness under model misspecification: A comparison of targeted maximum likelihood estimation with bias-corrected matching. Statistical Methods in Medical Research, 25(5), pp. 2315-2336. doi: 10.1177/0962280214521341

Kuha, J., Butt, S., Katsikatsou, M. & Skinner, C. (2017). The Effect of Probing "Don't Know" Responses on Measurement Quality and Nonresponse in Surveys. Journal of the American Statistical Association,

L

Lee, Y. K., Mammen, E., Nielsen, J. P. ORCID: 0000-0002-2798-0817 & Park, B. P. (2018). In-sample forecasting: A brief review and new algorithms. ALEA - Latin American Journal of Probability and Mathematical Statistics, 15, pp. 875-895. doi: 10.30757/ALEA.v15-33

Lee, Y. K., Mammen, E., Nielsen, J. P. ORCID: 0000-0002-2798-0817 & Park, B. U. (2019). Generalised additive dependency inflated models including aggregated covariates. Electronic Journal of Statistics, 13(1), pp. 67-93. doi: 10.1214/18-EJS1515

Lee, Y. K., Mammen, E., Nielsen, J. P. ORCID: 0000-0002-2798-0817 & Park, B. U. (2020). Nonparametric regression with parametric help. Electronic Journal of Statistics, 14(2), pp. 3845-3868. doi: 10.1214/20-EJS1760

Li, F., Rahulamathavan, Y., Conti, M. & Rajarajan, M. (2015). Robust access control framework for mobile cloud computing network. Computer Communications, 68(Sept), pp. 61-72. doi: 10.1016/j.comcom.2015.07.005

Loreto, V., Baronchelli, A., Mukherjee, A. , Puglisi, A. & Tria, F. (2011). Statistical physics of language dynamics. Journal of Statistical Mechanics: Theory and Experiment, 2011(4), P04006. doi: 10.1088/1742-5468/2011/04/P04006

Low, N., Butt, S., Ellis, P. & Davis Smith, J. (2007). Helping out: a national survey of volunteering and charitable giving. London: Cabinet Office.

Lu, X., Qiao, Y., Zhu, R. ORCID: 0000-0002-9944-0369 , Wang, G., Ma, Z. & Xue, J-H. (2021). Generalisations of stochastic supervision models. Pattern Recognition, 109, 107575.. doi: 10.1016/j.patcog.2020.107575

Luciano, E., Spreeuw, J. & Vigna, E. (2008). Modelling stochastic mortality for dependent lives. Insurance: Mathematics and Economics, 43(2), pp. 234-244. doi: 10.1016/j.insmatheco.2008.06.005

López-Montoya, A.J., Gámiz-Pérez, M.L. & Martinez-Miranda, M. D. (2015). Local linear smoothing to estimate accelerated lifetime model with censoring and truncation. Applied Mathematical Modelling, 39(16), doi: 10.1016/j.apm.2015.03.063

M

MacFarlane, A., Dorkenoo, E. & Morison, L. (2007). A statistical study to estimate the prevalence of female genital mutilation in England and Wales. Summary Report. London: Foundation for Women's Health, Research and Development (FORWARD).

Malihi, Z., Fanslow, J. L., Hashemi, L. ORCID: 0000-0001-6449-3834 , Gulliver, P. & McIntosh, T. (2021). Factors influencing help-seeking by those who have experienced intimate partner violence: Results from a New Zealand population-based study. PLoS ONE, 16(12), e0261059. doi: 10.1371/journal.pone.0261059

Malihi, Z. A., Fanslow, J. L., Hashemi, L. ORCID: 0000-0001-6449-3834 , Gulliver, P. J. & McIntosh, T. (2021). Prevalence of Nonpartner Physical and Sexual Violence Against People With Disabilities. American Journal of Preventive Medicine, 61(3), pp. 329-337. doi: 10.1016/j.amepre.2021.03.016

Marra, G & Radice, R. ORCID: 0000-0002-6316-3961 (2013). Estimation of a regression spline sample selection model. Computational Statistics & Data Analysis, 61, pp. 158-173. doi: 10.1016/j.csda.2012.12.010

Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2017). Bivariate copula additive models for location, scale and shape. Computational Statistics & Data Analysis, 112, pp. 99-113. doi: 10.1016/j.csda.2017.03.004

Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2020). Copula Link-Based Additive Models for Right-Censored Event Time Data. Journal of the American Statistical Association, 115, pp. 886-895. doi: 10.1080/01621459.2019.1593178

Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2017). A joint regression modeling framework for analyzing bivariate binary data in R. Dependence Modeling, 5(1), pp. 268-294. doi: 10.1515/demo-2017-0016

Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2013). A penalized likelihood estimation approach to semiparametric sample selection binary response modeling. Electronic Journal of Statistics, 7, pp. 1432-1455. doi: 10.1214/13-EJS814

Marra, G., Radice, R. ORCID: 0000-0002-6316-3961, Bärnighausen, T. , Wood, S. N. & McGovern, M. E. (2017). A Simultaneous Equation Approach to Estimating HIV Prevalence With Nonignorable Missing Responses. Journal of the American Statistical Association, 112(518), pp. 484-496. doi: 10.1080/01621459.2016.1224713

Marra, G., Radice, R. ORCID: 0000-0002-6316-3961 & Missiroli, S. (2014). Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models. Computational Statistics, 29(3-4), doi: 10.1007/s00180-013-0458-x

Marra, G., Radice, R. ORCID: 0000-0002-6316-3961 & Zimmer, D. (2020). Estimating the Binary Endogenous Effect of Insurance on Doctor Visits by Copula-Based Regression Additive Models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 69(4), pp. 953-971. doi: 10.1111/rssc.12419

Martinez-Miranda, M. D., Nielsen, J. P., Verrall, R. J. & Wüthrich, M. V. (2015). Double chain ladder, claims development inflation and zero-claims. Scandinavian Actuarial Journal, 2015(5), pp. 383-405. doi: 10.1080/03461238.2013.823459

Maslovskaya, O., Durrant, G. B., Smith, P. W. F. , Hanson, T. & Villar, A. (2019). What are the Characteristics of Respondents using Different Devices in Mixed-device Online Surveys? Evidence from Six UK Surveys. International Statistical Review, 87(2), pp. 326-346. doi: 10.1111/insr.12311

Mayhew, L. (2000). Health and Elderly Care Expenditure in an Aging World (RR-00-21). International Institute for Applied Systems Analysis (IIASA).

Mayhew, L. (2001). Japan's Longevity Revolution and the Implications for Health Care Finance and Long-term Care (Interim Report) (IR-01-010/February). International Institute for Applied Systems Analysis (IIASA).

Mayhew, L. ORCID: 0000-0002-0380-1757, Harper, G. & Villegas, A. M. (2020). An investigation into the impact of deprivation on demographic inequalities in adults. Annals of Actuarial Science, doi: 10.1017/S1748499520000068

Mayhew, L. & Smith, D. (2016). Decomposition of Life Expectancy at Older Ages and Prospects for Ageing Populations. In: Lombard, J., Stern, E. & Clarke, G. (Eds.), Applied Spatial Modelling and Planning. (pp. 172-188). Routledge.

Mayhew, L. & Smith, D. (2015). A jam-jar model of life expectancy and limits to life. International Longevity Centre - UK (ILC-UK).

McCann, E. ORCID: 0000-0003-3548-4204 & Sharek, D. (2013). Survey of lesbian, gay, bisexual, and transgender people's experiences of mental health services in Ireland. International Journal Of Mental Health Nursing, 23(2), pp. 118-127. doi: 10.1111/inm.12018

McGovern, M. E., Baernighausen, T., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2015). On the Assumption of Bivariate Normality in Selection Models A Copula Approach Applied to Estimating HIV Prevalence. Epidemiology, 26(2), pp. 229-237. doi: 10.1097/EDE.0000000000000218

McGovern, M. E., Marra, G., Radice, R. ORCID: 0000-0002-6316-3961 , Canning, D., Newell, M-L. & Bärnighausen, T. (2015). Adjusting HIV prevalence estimates for non-participation: an application to demographic surveillance. Journal of the International AIDS Society, 18(1), 19954. doi: 10.7448/IAS.18.1.19954

N

Newlands, R., Duncan, E., Presseau, J. , Treweek, S., Lawrie, L., Bower, P., Elliott, J., Francis, J. J. ORCID: 0000-0001-5784-8895, MacLennan, G., Ogden, M., Wells, M., Witham, M. D., Young, B. & Gillies, K. (2021). Why trials lose participants: A multitrial investigation of participants perspectives using the theoretical domains framework. Journal of Clinical Epidemiology, 137, pp. 1-13. doi: 10.1016/j.jclinepi.2021.03.007

Noble, R. ORCID: 0000-0002-8057-4252 & Recker, M. (2012). A statistically rigorous method for determining antigenic switching networks. PLoS One, 7(6), e39335. doi: 10.1371/journal.pone.0039335

O

O'Connor, R.B. (1996). The applicability of statistical techniques to credit portfolios with specific reference to the use of risk theory in banking. (Unpublished Doctoral thesis, City University London)

Owadally, I. & Landsman, Z. (2013). A characterization of optimal portfolios under the tail mean-variance criterion. Insurance: Mathematics and Economics, 52(2), pp. 213-221. doi: 10.1016/j.insmatheco.2012.12.004

Ozaita, J., Baronchelli, A. ORCID: 0000-0002-0255-0829 & Sanchez, A. (2020). Ethnic markers and the emergence of group-specific norms. Scientific Reports, 10(1), 22219. doi: 10.1038/s41598-020-79222-0

P

Popov, P. T. (2013). Bayesian reliability assessment of legacy safety-critical systems upgraded with fault-tolerant off-the-shelf software. Reliability Engineering & System Safety, 117(Sept), pp. 98-113. doi: 10.1016/j.ress.2013.03.017

R

Radice, R. ORCID: 0000-0002-6316-3961, Marra, G. & Wojtys, M. (2016). Copula regression spline models for binary outcomes. Statistics and Computing, 26(5), pp. 981-995. doi: 10.1007/s11222-015-9581-6

Ranjbar, S., Cantoni, E., Chavez-Demoulin, V. , Marra, G., Radice, R. ORCID: 0000-0002-6316-3961 & Jaton-Ogay, K. (2022). Modelling the Extremes of Seasonal Viruses and Hospital Congestion: The Example of Flu in a Swiss Hospital. Journal of the Royal Statistical Society Series C: Applied Statistics, doi: 10.1111/rssc.12559

Rickayzen, B. D. ORCID: 0000-0002-0433-0870, Klohn, F. & Karlsson, M. (2018). The Role of Heterogeneous Parameters for the Detection of Selection in Insurance Contracts. Insurance: Mathematics and Economics, 83, pp. 110-121. doi: 10.1016/j.insmatheco.2018.08.002

Rigoli, F. ORCID: 0000-0003-2233-934X (2021). Masters of suspicion: A Bayesian decision model of motivated political reasoning. Journal for the Theory of Social Behaviour, 51(3), pp. 350-370. doi: 10.1111/jtsb.12274

Ruxton, G. D., Fraser, C. & Broom, M. (2005). An evolutionarily stable joining policy for group foragers. Behavioral Ecology, 16(5), pp. 856-864. doi: 10.1093/beheco/ari063

S

Salako, K. ORCID: 0000-0003-0394-7833, Strigini, L. ORCID: 0000-0002-4246-2866 & Zhao, X. (2021). Conservative Confidence Bounds in Safety, from Generalised Claims of Improvement & Statistical Evidence. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), ISSN 1530-0889 doi: 10.1109/DSN48987.2021.00055

Seng Tang, K., Blake, D. & MacMinn, R. (2015). Longevity Risk and Capital Markets: The 2013-14 Update (PI-1502). London, UK: Pensions Institute.

Shang, H.L. & Haberman, S. (2017). Grouped multivariate and functional time series forecasting: an application to annuity pricing. Insurance: Mathematics and Economics, 75, pp. 166-179. doi: 10.1016/j.insmatheco.2017.05.007

Slingsby, A., Dykes, J. & Wood, J. (2011). Exploring Uncertainty in Geodemographics with Interactive Graphics. IEEE Transactions on Visualization and Computer Graphics, 17(12), pp. 2545-2554. doi: 10.1109/TVCG.2011.197

Slingsby, A., Dykes, J., Wood, J. , Foote, M. & Blom, M. (2008). The Visual Exploration of Insurance Data in Google Earth. Paper presented at the GISRUK08, 2 - 4 Apr 2008, Manchester Metropolitan University, Manchester, UK.

Spreeuw, J. (2010). Relationships Between Archimedean Copulas and Morgenstern Utility Functions. Paper presented at the Copula Theory and Its Applications, 25-26 September 2009, Warsaw.

T

Tian, H., Yim, A. ORCID: 0000-0002-8063-6572 & Newton, D. (2021). Tail-Heaviness, Asymmetry, and Profitability Forecasting by Quantile Regression. Management Science, 67(8), pp. 5209-5233. doi: 10.1287/mnsc.2020.3694

Tsanakas, A. (2012). Modelling: The elephant in the room. The Actuary, 2012,

Tsanakas, A., Beck, M. B. & Thompson, M. (2016). Taming Uncertainty: The Limits to Quantification. Astin Bulletin: The Journal of the ASTIN and AFIR Sections of the International Actuarial Association, 46(1), pp. 1-7.

Tyler, C. ORCID: 0000-0002-1512-4626 (2022). On the Power and Legitimacy of Follow-Up Testing. Perception, pp. 225-229. doi: 10.1177/03010066221081204

V

Verrall, R. J. (1989). Stochastic Models for Triangular Tables with Applications to Cohort Data and Claims Reserving. (Unpublished Doctoral thesis, City University London)

van den Berg, G., anys, L., Mammen, E. & Nielsen, J. P. ORCID: 0000-0002-2798-0817 (2020). A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models. Journal of Econometrics, doi: 10.1016/j.jeconom.2019.05.025

van der Wurp, H., Groll, A., Kneib, T. , Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2020). Generalised joint regression for count data with a focus on modelling football matches. Statistics and Computing, 30, pp. 1419-1432. doi: 10.1007/s11222-020-09953-7

van der Wurp, H., Groll, A., Kneib, T. , Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2020). Generalised joint regression for count data: a penalty extension for competitive settings. Statistics and Computing, doi: 10.1007/s11222-020-09953-7

W

Walby, S. (2016). Ensuring data collection and research on violence against women and domestic violence: Article 11 of the Istanbul Convention. Strasbourg: Council of Europe.

Walsh, H., McNeill, A., Purssell, E. ORCID: 0000-0003-3748-0864 & Duaso, M. (2020). A systematic review and Bayesian meta‐analysis of interventions which target or assess co‐use of tobacco and cannabis in single or multi‐substance interventions. Addiction, 115(10), pp. 1800-1814. doi: 10.1111/add.14993

Wang, Z., Zhu, R. ORCID: 0000-0002-9944-0369, Fukui, K. & Xue, J-H. (2018). Cone-based joint sparse modelling for hyperspectral image classification. Signal Processing, 144, pp. 417-429. doi: 10.1016/j.sigpro.2017.11.001

Wang, Z., Zhu, R. ORCID: 0000-0002-9944-0369, Fukui, K. & Xue, J-H. (2017). Matched Shrunken Cone Detector (MSCD): Bayesian Derivations and Case Studies for Hyperspectral Target Detection. IEEE Transactions on Image Processing, 26(11), pp. 5447-5461. doi: 10.1109/TIP.2017.2740621

Wojtys, M., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2016). Copula Regression Spline Sample Selection Models: The R Package SemiParSampleSel. Journal of Statistical Software, 71(6), doi: 10.18637/jss.v071.i06

Wojtys, M., Marra, G. & Radice, R. ORCID: 0000-0002-6316-3961 (2018). Copula based generalized additive models for location, scale and shape with non-random sample selection. Computational Statistics and Data Analysis, 127, pp. 1-14. doi: 10.1016/j.csda.2018.05.001

X

Xiao, L. Y. (2021). Regulating loot boxes as gambling? Towards a combined legal and self-regulatory consumer protection approach. Interactive Entertainment Law Review, 4(1), pp. 27-47. doi: 10.4337/ielr.2021.01.02

Y

Yates, G. E. & Broom, M. (2007). Stochastic models of kleptoparasitism. Journal of Theoretical Biology, 248(3), pp. 480-489. doi: 10.1016/j.jtbi.2007.05.007

Z

Zanin, L., Radice, R. ORCID: 0000-0002-6316-3961 & Marra, G. (2015). Modelling the impact of women's education on fertility in Malawi. Journal of Population Economics, 28(1), pp. 89-111. doi: 10.1007/s00148-013-0502-8

Zhu, R. ORCID: 0000-0002-9944-0369, Dong, M. & Xue, J-H. (2018). Learning distance to subspace for the nearest subspace methods in high-dimensional data classification. Information Sciences, 481, pp. 69-80. doi: 10.1016/j.ins.2018.12.061

Zhu, R. ORCID: 0000-0002-9944-0369, Dong, M. & Xue, J-H. (2014). Spectral non-local restoration of hyperspectral images with low-rank property. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(6), pp. 3062-3067. doi: 10.1109/JSTARS.2014.2370062

Zhu, R. ORCID: 0000-0002-9944-0369, Fukui, K. & Xue, J-H. (2017). Building a discriminatively ordered subspace on the generating matrix to classify high-dimensional spectral data. Information Sciences, 382, pp. 1-14. doi: 10.1016/j.ins.2016.12.001

Zhu, R. ORCID: 0000-0002-9944-0369, Wang, Z., Ma, Z. , Wang, G. & Xue, J-H. (2018). LRID: A new metric of multi-class imbalance degree based on likelihood-ratio test. Pattern Recognition Letters, 116, pp. 36-42. doi: 10.1016/j.patrec.2018.09.012

Zhu, R. ORCID: 0000-0002-9944-0369 & Xue, J-H. (2017). On the orthogonal distance to class subspaces for high-dimensional data classification. Information Sciences, 417, pp. 262-273. doi: 10.1016/j.ins.2017.07.019

Zhu, R. ORCID: 0000-0002-9944-0369, Zhou, F. & Xue, J-H. (2018). MvSSIM: A quality assessment index for hyperspectral images. Neurocomputing, 272, pp. 250-257. doi: 10.1016/j.neucom.2017.06.073

Zhu, R. ORCID: 0000-0002-9944-0369, Zhou, F., Yang, W. & Xue, J-H. (2018). On Hypothesis Testing for Comparing Image Quality Assessment Metrics [Tips & Tricks]. IEEE Signal Processing Magazine, 35(4), pp. 133-136. doi: 10.1109/MSP.2018.2829209

Č

Černý, A. & Ruf, J. Finance Without Brownian Motions: An Introduction To Simplified Stochastic Calculus. .

This list was generated on Tue May 24 04:26:50 2022 UTC.