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Journal of Applied Statistics|June 16, 2022
Asymmetric autoregressive models: statistical aspects and a financial application under COVID-19 pandemicYonghui Liu, Chaoxuan Mao, Víctor Leiva, et al.
Journal of Applied Statistics|June 16, 2022
Quantification of model risk that is caused by model misspecificationM B Seitshiro, H P Mashele
Journal of Applied Statistics|June 16, 2022
A Bayesian approach on the two-piece scale mixtures of normal homoscedastic nonlinear regression modelsZahra Barkhordar, Mohsen Maleki, Zahra Khodadadi, et al.
Journal of Applied Statistics|June 16, 2022
MAP segmentation in Bayesian hidden Markov models: a case studyAlexey Koloydenko, Kristi Kuljus, Jüri Lember
Journal of Applied Statistics|June 16, 2022
Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series modelsUfuk Beyaztas, Han Lin Shang
Journal of Applied Statistics|June 16, 2022
Shape-constrained Gaussian process regression for surface reconstruction and multimodal, non-rigid image registrationThomas Deregnaucourt, Chafik Samir, Sebastian Kurtek, et al.
Journal of Applied Statistics|June 16, 2022
Cause-specific hazard regression estimation for modified Weibull distribution under a class of non-informative priorsH Rehman, N Chandra, Fatemeh Sadat Hosseini-Baharanchi, et al.
Journal of Applied Statistics|June 16, 2022
Analysis of mixed correlated overdispersed binomial and ordinal longitudinal responses: LogLindley-Binomial and ordinal random effects modelSeyede Sedighe Azimi, Ehsan Bahrami Samani, Mojtaba Ganjali
Journal of Applied Statistics|June 16, 2022
Dynamic principal component analysis with missing valuesJunhyeon Kwon, Hee-Seok Oh, Yaeji Lim
Journal of Applied Statistics|June 16, 2022
Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring triosNadja Klein, Andrew Entwistle, Albert Rosenberger, et al.
Pageof 119