Journal Series C: current and forthcoming papers

RSS Series C journalVolume 67 (2018), part 3

Current and scheduled papers are available to subscribers from the Wiley Online Library.

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Bayesian non-parametric conditional copula estimation of twin data
L Dalla Valle, F Leisen and L Rossini

Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach
G M Gallo and E Otranto

Segmentation of sea current fields by cylindrical hidden Markov models: a composite likelihood approach
M Ranalli, F Lagona, M Picone and E Zambianchi

Stochastic differential equation based on a multimodal potential to model movement data in ecology
P Gloaguen, M-P Etienne and S Le Corff

Boosting factor-specific functional historical models for the detection of synchronization in bioelectrical signals
D Rügamer, S Brockhaus, K Gentsch, K Scherer and S Greven

Standardized drought indices: a novel univariate and multivariate approach
T M Erhardt and C Czado

Signal regression models for location, scale and shape with an application to stock returns
S Brockhaus, A Fuest, A Mayr and S Greven

Modelling time varying heterogeneity in recurrent infection processes: an application to serological data
S Abrams, A Wienke and N Hens

A spatiotemporal multispecies model of a semicontinuous response
C M Jones-Todd, B Swallow, J B Illian and M Toms

BLAST: Bayesian latent subgroup design for basket trials accounting for patient heterogeneity
Y Chu and Y Yuan

Forthcoming papers

On the ranking of test match batsmen
R J Boys and P M Philipson

Distributed lag interaction models with two pollutants
Y-H Chen, B Mukherjee and V J Berrocal

Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies
P Samartsidis, C R Eickhoff, S B Eickhoff, T D Wager, L F Barrett, S Atzil, T D Johnson and T E Nichols

Two-stage design for phase I–II cancer clinical trials using continuous dose combinations of cytotoxic agents
M Tighiouart

Multivariate posterior inference for spatial models with the integrated nested Laplace approximation
V Gómez-Rubio and F Palmí-Perales

An information theoretic phase I–II design for molecularly targeted agents that does not require an assumption of monotonicity
P Mozgunov and T Jaki

AAA: triple adaptive Bayesian designs for the identification of optimal dose combinations in dual-agent dose finding trials
J Lyu, Y Ji, N Zhao and D V T Catenacci

Temporal trends of biomarkers and between-biomarker associations
Z Hu

A dose finding design for seizure reduction in neonates
M Ursino, Y Yuan, C Alberti, E Comets, G Favrais, T Friede, F Lentz, N Stallard and S Zohar

Detecting epistatic selection with partially observed genotype data by using copula graphical models
P Behrouzi and E C Wit

A utility-based Bayesian phase I–II design for immunotherapy trial with progression-free survival end point
B Guo, Y Park and S Liu

Stratified space–time infectious disease modelling, with an application to hand, foot and mouth disease in China
C Bauer and J Wakefield

Methods for preferential sampling in geostatistics
D Dinsdale and M Salibian-Barrera

Multivariate latent variable transition models of longitudinal mixed data: an analysis on alcohol use disorder
S Cagnone and C Viroli

A non-linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies
H Zhang and L Wu

Peptide refinement by using a stochastic search
N H Lewis, D B Hitchcock, I L Dryden and J R Rose

Testing for pathway (in)activation by using Gaussian graphical models
W N van Wieringen, C F W Peeters, R X de Menezes and M A van de Wiel

Constructing treatment decision rules based on scalar and functional predictors when moderators of treatment effect are unknown
A Ciarleglio, E Petkova, T Ogden and T Tarpey

Unravelling the predictive power of telematics data in car insurance pricing
R Verbelen, K Antonio and G Claeskens

Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection
T Rajala, D J Murrell and S C Olhede

Marginal logistic regression for spatially clustered binary data
M Cattelan and C Varin

Optimizing natural killer cell doses for heterogeneous cancer patients on the basis of multiple event times
J Lee, P F Thall and K Rezvani

Radiologic image-based statistical shape analysis of brain tumours
K Bharath, S Kurtek, A Rao and V Baladandayuthapani

Simultaneous equation penalized likelihood estimation of vehicle accident injury severity
F Donat and G Marra

Modelling correlated binary variables: an application to lower urinary tract symptoms
W Barcella, M De Iorio and J Malone-Lee

Spatially varying auto-regressive models for prediction of new human immunodeficiency virus diagnoses
L Shand, B Li, T Park and D Albarracín

Using artificial censoring to improve extreme tail quantile estimates
Y Liu, M Salibián-Barrera, R H Zamar and J V Zidek

gBOIN: a unified model-assisted phase I trial design accounting for toxicity grades, and binary or continuous end points
R Mu, Y Yuan, J Xu, S J Mandreker and J Yin

Functional principal components analysis on moving time windows of longitudinal data: dynamic prediction of times to event
F Yan, X Lin, R Li and X Huang

Improving heritability estimation by a variable selection approach in sparse high dimensional linear mixed models
A Bonnet, C Lévy-Leduc, E Gassiat, R Toro and T Bourgeron

The functional latent block model for the co-clustering of electricity consumption curves
C Bouveyron, L Bozzi, J Jacques and F-X Jollois

Bayesian models for weighted data with missing values: a bootstrap approach
H Goldstein, J Carpenter and M G Kenward