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September 2022, Volume 31, Issue 3
- 587-615 Evidences from survey data and fiscal data: nonresponse and measurement errors in annual incomes
by Maddalena Cavicchioli & Michele Lalla - 617-635 A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany
by Francesca Di Iorio & Umberto Triacca - 637-659 Alternative sensitivity analyses for regression estimates of treatment effects to unobserved confounding in binary and survival data
by Byeong Yeob Choi & Jason P. Fine & Roman Fernandez & M. Alan Brookhart - 661-678 Queue hurdle Coxian phase-type model for two-stage process of population-based cancer screening
by Hsiao-Hsuan Jen & Chen-Yang Hsu & Amy Ming-Fang Yen & Han-Mo Chiu & Hsiu-Hsi Chen - 679-707 Hessian orderings of multivariate normal variance-mean mixture distributions and their applications in evaluating dependent multivariate risk portfolios
by Mehdi Amiri & Narayanaswamy Balakrishnan & Abbas Eftekharian - 709-727 A pseudo-values regression model for non-fatal event free survival in the presence of semi-competing risks
by Annalisa Orenti & Patrizia Boracchi & Giuseppe Marano & Elia Biganzoli & Federico Ambrogi
June 2022, Volume 31, Issue 2
- 197-225 Bayesian graphical models for modern biological applications
by Yang Ni & Veerabhadran Baladandayuthapani & Marina Vannucci & Francesco C. Stingo - 227-229 Discussion to: Bayesian Graphical Models for Modern Biological Applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Alberto Roverato - 231-233 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by David Marcano & Adrian Dobra - 235-239 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Anindya Bhadra - 241-251 Extending graphical models for applications: on covariates, missingness and normality
by Luigi Augugliaro & Veronica Vinciotti & Ernst C. Wit - 253-260 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Michael Schweinberger - 261-267 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Federico Castelletti & Guido Consonni & Luca Rocca - 269-278 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Maria Prosperina Vitale & Giuseppe Giordano & Giancarlo Ragozini - 279-286 Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo
by Yize Zhao & Zhe Sun & Jian Kang - 287-294 Rejoinder to the discussion of “Bayesian graphical models for modern biological applications”
by Yang Ni & Veerabhadran Baladandayuthapani & Marina Vannucci & Francesco C. Stingo - 295-319 Estimation and decomposition of food price inflation risk
by Kris Boudt & Hong Anh Luu - 321-341 Model detection and variable selection for mode varying coefficient model
by Xuejun Ma & Yue Du & Jingli Wang - 343-364 Predictors of refraction prediction error after cataract surgery: a shared parameter model to account for missing post-operative measurements
by D. Claire Miller & Samantha MaWhinney & Jennifer L. Patnaik & Karen L. Christopher & Anne M. Lynch & Brandie D. Wagner - 365-386 Chunk-wise regularised PCA-based imputation of missing data
by A. Iodice D’Enza & A. Markos & F. Palumbo - 387-424 Goodness-of-fit test for $$\alpha$$ α -stable distribution based on the quantile conditional variance statistics
by Marcin Pitera & Aleksei Chechkin & Agnieszka Wyłomańska - 425-425 Publisher Correction to: Goodness-of-fit test for α-stable distribution based on the quantile conditional variance statistics
by Marcin Pitera & Aleksei Chechkin & Agnieszka Wyłomańska - 427-458 Estimation and computations for Gaussian mixtures with uniform noise under separation constraints
by Pietro Coretto
March 2022, Volume 31, Issue 1
- 1-20 Studying the relationship between anxiety and school achievement: evidence from PISA data
by Antonella D’Agostino & Francesco Schirripa Spagnolo & Nicola Salvati - 21-39 Dependence on a collection of Poisson random variables
by Luis E. Nieto-Barajas - 41-61 A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity
by Rui Martins - 63-85 Modelling interaction patterns in a predator-prey system of two freshwater organisms in discrete time: an identified structural VAR approach
by Helmut Herwartz - 87-108 Exact parametric causal mediation analysis for a binary outcome with a binary mediator
by Marco Doretti & Martina Raggi & Elena Stanghellini - 109-131 A Bayesian bivariate hierarchical model with correlated parameters for the analysis of road crashes in Italian tunnels
by Ciro Caliendo & Maurizio Guida & Fabio Postiglione & Isidoro Russo - 133-158 Support provided by elderly in Italy: a hierarchical analysis of ego networks controlling for alter–overlapping
by Elvira Pelle & Susanna Zaccarin & Emanuela Furfaro & Giulia Rivellini - 159-180 A simple yet efficient method of local false discovery rate estimation designed for genome-wide association data analysis
by Ali Karimnezhad - 181-195 When did coronavirus arrive in Europe?
by Augusto Cerqua & Roberta Di Stefano
December 2021, Volume 30, Issue 5
- 1285-1288 Special issue on statistical analysis of networks
by Michael Schweinberger & Francesco C. Stingo & Maria Prosperina Vitale - 1289-1314 Structural learning and estimation of joint causal effects among network-dependent variables
by Federico Castelletti & Alessandro Mascaro - 1315-1335 The Relative Fit measure for evaluating a blockmodel
by Marjan Cugmas & Aleš Žiberna & Anuška Ferligoj - 1337-1364 Online network monitoring
by Anna Malinovskaya & Philipp Otto - 1365-1398 Weighted stochastic block model
by Tin Lok James Ng & Thomas Brendan Murphy - 1399-1423 Learning social networks from text data using covariate information
by Xiaoyi Yang & Nynke M. D. Niezink & Rebecca Nugent - 1425-1444 Multiplexity analysis of networks using multigraph representations
by Termeh Shafie & David Schoch - 1445-1464 A network analysis of student mobility patterns from high school to master’s
by Vincenzo G. Genova & Michele Tumminello & Fabio Aiello & Massimo Attanasio - 1465-1483 Bayesian dynamic network actor models with application to South Korean COVID-19 patient movement data
by Antonio Mario Arrizza & Alberto Caimo - 1485-1505 On the interpretation of inflated correlation path weights in concentration graphs
by Alberto Roverato - 1507-1533 A clustering procedure for mixed-type data to explore ego network typologies: an application to elderly people living alone in Italy
by Elvira Pelle & Roberta Pappadà
October 2021, Volume 30, Issue 4
- 1109-1133 A multiple inflated negative binomial hurdle regression model: analysis of the Italians’ tourism behaviour during the Great Recession
by Chiara Bocci & Laura Grassini & Emilia Rocco - 1135-1155 The variation of the posterior variance and Bayesian sample size determination
by Jörg Martin & Clemens Elster - 1157-1174 The sufficiency of the evidence, the relevancy of the evidence, and quantifying both with a single number
by David R. Bickel - 1175-1195 Bootstrap confidence intervals for correlation between continuous repeated measures
by Guogen Shan & Hua Zhang & Jim Barbour - 1197-1217 Population size estimation based upon zero-truncated, one-inflated and sparse count data
by Dankmar Böhning & Herwig Friedl - 1219-1236 A split questionnaire survey design in the context of statistical matching
by Mehboob Ali & Göran Kauermann - 1237-1258 Parametric modeling of quantile regression coefficient functions with count data
by Paolo Frumento & Nicola Salvati - 1259-1283 Transition models for count data: a flexible alternative to fixed distribution models
by Moritz Berger & Gerhard Tutz
September 2021, Volume 30, Issue 3
- 767-778 Forum on Benford’s law and statistical methods for the detection of frauds
by Lucio Barabesi & Andrea Cerioli & Domenico Perrotta - 779-795 The mathematics of Benford’s law: a primer
by Arno Berger & Theodore P. Hill - 797-817 Recurrence relations and Benford’s law
by Madeleine Farris & Noah Luntzlara & Steven J. Miller & Lily Shao & Mengxi Wang - 819-840 A multivariate test for detecting fraud based on Benford’s law, with application to music streaming data
by Nermina Mumic & Peter Filzmoser - 841-861 robROSE: A robust approach for dealing with imbalanced data in fraud detection
by Bart Baesens & Sebastiaan Höppner & Irene Ortner & Tim Verdonck - 863-894 Semiautomatic robust regression clustering of international trade data
by Francesca Torti & Marco Riani & Gianluca Morelli - 895-926 Confronting collinearity in environmental regression models: evidence from world data
by Claudia García-García & Catalina B. García-García & Román Salmerón - 927-945 A measure of interrater absolute agreement for ordinal categorical data
by Giuseppe Bove & Pier Luigi Conti & Daniela Marella - 947-971 Including covariates in a space-time point process with application to seismicity
by Giada Adelfio & Marcello Chiodi - 973-1005 Robust Wald-type tests in GLM with random design based on minimum density power divergence estimators
by Ayanendranath Basu & Abhik Ghosh & Abhijit Mandal & Nirian Martin & Leandro Pardo - 1007-1031 An empirical comparison of two approaches for CDPCA in high-dimensional data
by Adelaide Freitas & Eloísa Macedo & Maurizio Vichi - 1033-1052 A unified approach to permutation testing for equivalence
by Rosa Arboretti & Fortunato Pesarin & Luigi Salmaso - 1053-1078 Bayesian inference of multiple structural change models with asymmetric GARCH errors
by Cathy W. S. Chen & Bonny Lee - 1079-1107 Unified Bayesian conditional autoregressive risk measures using the skew exponential power distribution
by Marco Bottone & Lea Petrella & Mauro Bernardi
June 2021, Volume 30, Issue 2
- 375-407 Counterdiagonal/nonpositive tail dependence in Vine copula constructions: application to portfolio management
by Yuri Salazar Flores & Adán Díaz-Hernández - 409-436 Estimating drift parameters in a non-ergodic Gaussian Vasicek-type model
by Khalifa Es-Sebaiy & Mohammed Es.Sebaiy - 437-459 Improved wrong-model inference for generalized linear models for binary responses in the presence of link misspecification
by Xianzheng Huang - 461-475 Semiparametric model for regression analysis with nonmonotone missing data
by Yang Zhao - 477-514 Asymptotic properties of QMLE for seasonal threshold GARCH model with periodic coefficients
by Abdelouahab Bibi - 515-542 On CUSUM test for dynamic panel models
by Minyoung Jo & Sangyeol Lee - 543-571 A spatial mixed-effects regression model for electoral data
by Agnese Maria Di Brisco & Sonia Migliorati - 573-604 Bayesian isotonic logistic regression via constrained splines: an application to estimating the serve advantage in professional tennis
by Silvia Montagna & Vanessa Orani & Raffaele Argiento - 605-635 Yule–Simpson’s paradox: the probabilistic versus the empirical conundrum
by Aris Spanos - 637-663 Efficacy and toxicity monitoring via Bayesian predictive probabilities in phase II clinical trials
by Valeria Sambucini - 665-688 Financial contagion through space-time point processes
by Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici - 689-709 On the predictive performance of a non-optimal action in hypothesis testing
by Fulvio De Santis & Stefania Gubbiotti - 711-746 Weighted likelihood latent class linear regression
by Luca Greco & Antonio Lucadamo & Claudio Agostinelli - 747-765 A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC
by Katiane S. Conceição & Adriano K. Suzuki & Marinho G. Andrade
March 2021, Volume 30, Issue 1
- 1-48 Penalised robust estimators for sparse and high-dimensional linear models
by Umberto Amato & Anestis Antoniadis & Italia De Feis & Irene Gijbels - 49-77 Improving reproducibility probability estimation and preserving RP-testing
by Lucio De Capitani & Daniele De Martini - 79-108 Small area estimation under a measurement error bivariate Fay–Herriot model
by Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez - 109-137 An empirical study on the parsimony and descriptive power of TARMA models
by Greta Goracci - 139-155 A new time-varying model for forecasting long-memory series
by Luisa Bisaglia & Matteo Grigoletto - 157-173 Regression models for exceedance data: a new approach
by Marcelo Bourguignon & Fernando Ferraz Nascimento - 175-194 Bayesian analysis of ranking data with the Extended Plackett–Luce model
by Cristina Mollica & Luca Tardella - 195-222 Small area estimation under a temporal bivariate area-level linear mixed model with independent time effects
by Roberto Benavent & Domingo Morales - 223-233 Bayesian optimal designs for multi-factor nonlinear models
by Lei He - 235-268 Covariance matrix estimation of the maximum likelihood estimator in multivariate clusterwise linear regression
by Giuliano Galimberti & Lorenzo Nuzzi & Gabriele Soffritti - 269-293 Interaction among three substitute products: an extended innovation diffusion model
by Claudia Furlan & Cinzia Mortarino & Mohammad Salim Zahangir - 295-315 Symbolic interval-valued data analysis for time series based on auto-interval-regressive models
by Liang-Ching Lin & Hsiang-Lin Chien & Sangyeol Lee - 317-330 A note on simultaneous calibrated prediction intervals for time series
by Giovanni Fonseca & Federica Giummolè & Paolo Vidoni - 331-357 Outlier robust small domain estimation via bias correction and robust bootstrapping
by G. Bertarelli & R. Chambers & N. Salvati - 359-373 Can Bayesian, confidence distribution and frequentist inference agree?
by Erlis Ruli & Laura Ventura
December 2020, Volume 29, Issue 4
- 669-708 An alternative semiparametric model for spatial panel data
by Román Mínguez & Roberto Basile & María Durbán - 709-725 Nearest neighbors estimation for long memory functional data
by Lihong Wang - 727-744 Statistical and probabilistic analysis of interarrival and waiting times of Internet2 anomalies
by Piotr Kokoszka & Hieu Nguyen & Haonan Wang & Liuqing Yang - 745-765 PC priors for residual correlation parameters in one-factor mixed models
by Massimo Ventrucci & Daniela Cocchi & Gemma Burgazzi & Alex Laini - 767-786 Context-specific independencies in hierarchical multinomial marginal models
by Federica Nicolussi & Manuela Cazzaro - 787-812 Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform
by Anna Calissano & Simone Vantini & Marika Arena - 813-843 A general piecewise multi-state survival model: application to breast cancer
by Juan Eloy Ruiz-Castro & Mariangela Zenga - 845-869 Modified LASSO estimators for time series regression models with dependent disturbances
by Yujie Xue & Masanobu Taniguchi - 871-897 A copula-based method of classifying individuals into binary disease categories using dependent biomarkers
by Shofiqul Islam & Sonia Anand & Jemila Hamid & Lehana Thabane & Joseph Beyene - 899-912 A weighted $$\chi ^2$$ χ 2 test to detect the presence of a major change point in non-stationary Markov chains
by Alessandra Micheletti & Giacomo Aletti & Giulia Ferrandi & Danilo Bertoni & Daniele Cavicchioli & Roberto Pretolani - 913-936 Regression for compositions based on a generalization of the Dirichlet distribution
by Monique Graf - 937-954 Sliced inverse median difference regression
by Stephen Babos & Andreas Artemiou - 955-982 Multivariate power series interpoint distances
by Reza Modarres & Yu Song
September 2020, Volume 29, Issue 3
- 427-446 Influence function-based empirical likelihood and generalized confidence intervals for the Lorenz curve
by Yuyin Shi & Bing Liu & Gengsheng Qin - 447-482 On firm size distribution: statistical models, mechanisms, and empirical evidence
by Anna Maria Fiori - 483-514 A Monte Carlo subsampling method for estimating the distribution of signal-to-noise ratio statistics in nonparametric time series regression models
by Francesco Giordano & Pietro Coretto - 515-525 Exact confidence limits for proportion difference in clinical trials with bilateral outcome
by Guogen Shan - 527-552 A generalized mixture integer-valued GARCH model
by Huiyu Mao & Fukang Zhu & Yan Cui - 553-580 Variable selection techniques after multiple imputation in high-dimensional data
by Faisal Maqbool Zahid & Shahla Faisal & Christian Heumann - 581-596 Combining permutation tests to rank systemically important banks
by Lorenzo Frattarolo & Francesca Parpinel & Claudio Pizzi - 597-617 Beliefs and needs of academic teachers: a latent class analysis
by Silvia Bacci & Bruno Bertaccini & Alessandra Petrucci - 619-649 Identifying atypically expressed chromosome regions using RNA-Seq data
by Vinícius Diniz Mayrink & Flávio B. Gonçalves - 651-668 Distributions of powers of the central beta matrix variates and applications
by Thu Pham-Gia & Duong Thanh Phong & Dinh Ngoc Thanh
June 2020, Volume 29, Issue 2
- 211-236 One or more rates of ageing? The extended gamma-Gompertz model (EGG)
by Giambattista Salinari & Gustavo De Santis - 237-263 What finite-additivity can add to decision theory
by Mark J. Schervish & Teddy Seidenfeld & Rafael B. Stern & Joseph B. Kadane - 265-288 Planning step-stress test plans under Type-I hybrid censoring for the log-location-scale distribution
by Chien-Tai Lin & Cheng-Chieh Chou & N. Balakrishnan - 289-307 Testing the equality of matrix distributions
by Lingzhe Guo & Reza Modarres - 309-333 Loss-based approach to two-piece location-scale distributions with applications to dependent data
by Fabrizio Leisen & Luca Rossini & Cristiano Villa - 335-355 Bayesian propensity score analysis for clustered observational data
by Qi Zhou & Catherine McNeal & Laurel A. Copeland & Justin P. Zachariah & Joon Jin Song - 357-371 Testing for boundary conditions in case of fractionally integrated processes
by Margherita Gerolimetto & Stefano Magrini - 373-395 Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach
by F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti - 397-397 Correction to: Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach
by F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti - 399-425 Analysing the course of public trust via hidden Markov models: a focus on the Polish society
by Fulvia Pennoni & Ewa Genge
March 2020, Volume 29, Issue 1
- 1-24 On the estimation of the Lorenz curve under complex sampling designs
by Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale - 25-48 Nonparametric imputation method for nonresponse in surveys
by Caren Hasler & Radu V. Craiu - 49-78 Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models
by Roberto Mari & Roberto Rocci & Stefano Antonio Gattone - 79-99 Covariance matrix estimation in a seemingly unrelated regression model under Stein’s loss
by Shun Matsuura & Hiroshi Kurata - 101-128 Spatial prediction and spatial dependence monitoring on georeferenced data streams
by Antonio Balzanella & Antonio Irpino - 129-139 A note on the asymptotic and exact Fisher information matrices of a Markov switching VARMA process
by Maddalena Cavicchioli - 141-171 Prediction of risks of sequence of events using multistage proportional hazards model: a marginal-conditional modelling approach
by Rafiqul I. Chowdhury & M. Ataharul Islam - 173-185 Cyber risk measurement with ordinal data
by Silvia Facchinetti & Paolo Giudici & Silvia Angela Osmetti - 187-207 Decomposition by subpopulations of the Zenga-84 inequality curve and the related index $$\zeta $$ζ: an application to 2014 Bank of Italy survey
by Francesco Porro & Michele Zenga
December 2019, Volume 28, Issue 4
- 571-591 Mutual association measures
by Claudio G. Borroni - 593-623 Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions
by Dariush Najarzadeh - 625-653 BINAR(1) negative binomial model for bivariate non-stationary time series with different over-dispersion indices
by Yuvraj Sunecher & Naushad Mamode Khan & Miroslav M. Ristić & Vandna Jowaheer - 655-678 Single index quantile regression for censored data
by Eliana Christou & Michael G. Akritas - 679-693 Dynamic partially functional linear regression model
by Jiang Du & Hui Zhao & Zhongzhan Zhang - 695-722 Estimation of the volume under the ROC surface in presence of nonignorable verification bias
by Khanh To Duc & Monica Chiogna & Gianfranco Adimari - 723-747 Modelling of lung cancer survival data for critical illness insurances
by Joanna Dȩbicka & Beata Zmyślona - 749-767 Zero-one augmented beta and zero-inflated discrete models with heterogeneous dispersion for the analysis of student academic performance
by Hildete P. Pinheiro & Rafael P. Maia & Eufrásio A. Lima Neto & Mariana Rodrigues-Motta
September 2019, Volume 28, Issue 3
- 385-387 Editorial
by Tommaso Proietti - 389-435 The class of cub models: statistical foundations, inferential issues and empirical evidence
by Domenico Piccolo & Rosaria Simone - 437-439 Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence
by Francesco Bartolucci & Fulvia Pennoni - 441-444 Discussion of “The class of CUB models: statistical foundations, inferential issues and empirical evidence”
by Roberto Colombi & Sabrina Giordano & Anna Gottard - 445-449 The class of CUB models: statistical foundations, inferential issues and empirical evidence
by Alan Agresti & Maria Kateri - 451-456 Discussion of The class of CUB models: statistical foundations, inferential issues and empirical evidence
by Tommaso Proietti - 457-458 A review of: The class of CUB models: statistical foundations, inferential issues and empirical evidence by Domenico Piccolo and Rosaria Simone
by Ron Kenett - 459-463 Discussion of ‘The class of CUB models: statistical foundations, inferential issues and empirical evidence’ by Domenico Piccolo and Rosaria Simone
by Leonardo Grilli & Carla Rampichini - 465-470 Discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo and Rosaria Simone
by Marica Manisera & Paola Zuccolotto - 471-475 Comments on The class of cub models: statistical foundations, inferential issues and empirical evidence by D. Piccolo and R. Simone
by Gerhard Tutz - 477-493 Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”
by Domenico Piccolo & Rosaria Simone - 495-506 The multiple Cantelli inequalities
by Haruhiko Ogasawara - 507-539 Multivariate ordinal regression models: an analysis of corporate credit ratings
by Rainer Hirk & Kurt Hornik & Laura Vana - 541-569 Real and financial cycles: estimates using unobserved component models for the Italian economy
by Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini
June 2019, Volume 28, Issue 2
- 187-215 A model-based fuzzy analysis of questionnaires
by E. Nardo & R. Simone - 217-240 Functional data analysis: local linear estimation of the $$L_1$$ L 1 -conditional quantiles
by Fahimah A. Al-Awadhi & Zoulikha Kaid & Ali Laksaci & Idir Ouassou & Mustapha Rachdi - 241-257 The B-exponential divergence and its generalizations with applications to parametric estimation
by Taranga Mukherjee & Abhijit Mandal & Ayanendranath Basu - 259-280 A rate of consistency for nonparametric estimators of the distribution function based on censored dependent data
by Nour El Houda Rouabah & Nahima Nemouchi & Fatiha Messaci - 281-299 Modeling of the ARMA random effects covariance matrix in logistic random effects models
by Keunbaik Lee & Hoimin Jung & Jae Keun Yoo - 301-322 A k-means procedure based on a Mahalanobis type distance for clustering multivariate functional data
by Andrea Martino & Andrea Ghiglietti & Francesca Ieva & Anna Maria Paganoni - 323-358 Bayesian variable selection in linear regression models with non-normal errors
by Saverio Ranciati & Giuliano Galimberti & Gabriele Soffritti - 359-383 Reconstructing missing data sequences in multivariate time series: an application to environmental data
by Maria Lucia Parrella & Giuseppina Albano & Michele La Rocca & Cira Perna
March 2019, Volume 28, Issue 1
- 1-25 Sample selection when a multivariate set of size measures is available
by R. Benedetti & M. S. Andreano & F. Piersimoni - 27-56 Sample selection models for discrete and other non-Gaussian response variables
by Adelchi Azzalini & Hyoung-Moon Kim & Hea-Jung Kim - 57-76 Mantel–Haenszel estimators of a common odds ratio for multiple response data
by Thomas Suesse & Ivy Liu - 77-99 Nonparametric series density estimation and testing
by Patrick Marsh - 101-101 Correction to: Nonparametric series density estimation and testing
by Patrick Marsh - 103-118 On Wald tests for differential item functioning detection
by Michela Battauz - 119-142 Backtesting VaR and expectiles with realized scores
by Fabio Bellini & Ilia Negri & Mariya Pyatkova - 143-155 Modeling right-censored medical cost data in regression and the effects of covariates
by Lu Deng & Wendy Lou & Nicholas Mitsakakis - 157-185 Random forest-based approach for physiological functional variable selection for driver’s stress level classification
by Neska Haouij & Jean-Michel Poggi & Raja Ghozi & Sylvie Sevestre-Ghalila & Mériem Jaïdane
December 2018, Volume 27, Issue 4
- 559-587 The power of monitoring: how to make the most of a contaminated multivariate sample
by Andrea Cerioli & Marco Riani & Anthony C. Atkinson & Aldo Corbellini - 589-594 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
by Jakob Raymaekers & Peter J. Rousseeuw & Iwein Vranckx - 595-602 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini
by Stephane Heritier & Maria-Pia Victoria-Feser - 603-604 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini
by Ricardo A. Maronna & Víctor J. Yohai - 605-608 Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”
by L. A. García-Escudero & A. Gordaliza & C. Matrán & A. Mayo-Iscar - 609-619 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini
by Claudio Agostinelli & Luca Greco - 621-623 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini
by Christophe Croux - 625-629 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
by Simon J. Sheather & Joseph W. McKean - 631-639 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini
by Valentin Todorov - 641-649 Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
by Domenico Perrotta & Francesca Torti - 651-660 The power of (extended) monitoring in robust clustering
by Alessio Farcomeni & Francesco Dotto - 661-666 Rejoinder to the discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
by Andrea Cerioli & Marco Riani & Anthony C. Atkinson & Aldo Corbellini - 667-688 Wavelet regression estimations with strong mixing data
by Junke Kou & Youming Liu - 689-714 Testing for an excessive number of zeros in time series of bounded counts
by Hee-Young Kim & Christian H. Weiß & Tobias A. Möller - 715-734 Box–Cox t random intercept model for estimating usual nutrient intake distributions
by Giovana Fumes-Ghantous & Silvia L. P. Ferrari & José Eduardo Corrente
August 2018, Volume 27, Issue 3
- 365-384 On multivariate quantile regression analysis
by Jean-Paul Chavas - 385-406 On score vector- and residual-based CUSUM tests in ARMA–GARCH models
by Haejune Oh & Sangyeol Lee - 407-435 Modelling of low count heavy tailed time series data consisting large number of zeros and ones
by Raju Maiti & Atanu Biswas & Bibhas Chakraborty - 437-454 Most stable sample size determination in clinical trials
by Ali Karimnezhad & Ahmad Parsian - 455-477 A note on variable selection in functional regression via random subspace method
by Łukasz Smaga & Hidetoshi Matsui - 479-490 Asymptotics of the weighted least squares estimation for AR(1) processes with applications to confidence intervals
by Ruidong Han & Xinghui Wang & Shuhe Hu - 491-513 Clustering of financial instruments using jump tail dependence coefficient
by Chen Yang & Wenjun Jiang & Jiang Wu & Xin Liu & Zhichuan Li - 515-543 Quis custiodet ipsos custodes? How to detect and correct teacher cheating in Italian student data
by Sergio Longobardi & Patrizia Falzetti & Margherita Maria Pagliuca