Journal Series C: current and forthcoming papers

RSS Series C journalVolume 68 (2019), part 1

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

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Dirichlet process mixtures of order statistics with applications to retail analytics
J Pitkin, G Ross and I Manolopoulou

Projecting UK mortality by using Bayesian generalized additive models
J Hilton, E Dodd, J J Forster, P W F Smith

Computer model calibration with large non-stationary spatial outputs: application to the calibration of a climate model
K-L Chang and S Guillas

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

Spatial cluster detection in mobility networks: a copula approach
H Kim, R Duan, S Kim, J Lee and G-Q Ma

Informing a risk prediction model for binary outcomes with external coefficient information
W Cheng, J M G Taylor, T Gu, S A Tomlins and B Mukherjee

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

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

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

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

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

Temporal trends of biomarkers and between-biomarker associations
Z Hu

Forthcoming papers

Ranking the importance of genetic factors by variable-selection confidence sets
C Zheng, D Ferrari, M Zhang and P Baird

Improving the identification of antigenic sites in the H1N1 influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model
V Davies, W T Harvey, R Reeve and D Husmeier

Testing critical points of non-parametric regression curves: application to the management of stalked barnacles
M Sestelo and J Roca-Pardińas

Landmark linear transformation model for dynamic prediction with application to a longitudinal cohort study of chronic disease
Y Zhu, L Li and X Huang

Additive quantile regression for clustered data with an application to children’s physical activity
M Geraci

PairClone: a Bayesian subclone caller based on mutation pairs
T Zhou, P Müller, S Sengupta and Y Ji

Bayesian non-parametric survival regression for optimizing precision dosing of intravenous busulfan in allogeneic stem cell transplantation
Y Xu, P F Thall, W Hua and Borje S Andersson

Dose individualization and variable selection by using the Bayesian lasso in early phase dose finding trials
Y Kakurai, S Kaneko, C Hamada and A Hirakawa

Detecting weak dependence in computer network traffic patterns by using higher criticism
M Price-Williams, N Heard and P Rubin-Delanchy

Bayesian analysis of functional magnetic resonance imaging data with spatially varying auto-regressive orders
M Teng, F S Nathoo and T D Johnson

Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
S H Sørbye, J B Illian, D P Simpson, D Burslem and H Rue

Exploring patterns of demand in bike sharing systems via replication point process models
D Gervini and M Khanal

Rectangular latent Markov models for time-specific clustering, with an analysis of the wellbeing of nations
G Anderson, A Farcomeni, M G Pittau and R Zelli

Phase I–II trial design for biologic agents using conditional auto-regressive models for toxicity and efficacy
D G Muenz, J M G Taylor and T M Braun

Discrete Weibull generalized additive model: an application to count fertility data
A Peluso, V Vinciotti and K Yu

Optimal design of experiments for non-linear response surface models
Y Huang, S G Gilmour, K Mylona and P Goos

Functional clustering of accelerometer data via transformed input variables
Y Lim, H-S Oh and Y K Cheung

Semi parametric dose finding methods: special cases
M Clertant and J O’Quigley

Joint modelling of a binary and a continuous outcome measured at two cycles to determine the optimal dose
M Ezzalfani, T Burzykowski and X Paoletti

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

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

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

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

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