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Using sequential statistical tests for efficient hyperparameter tuning AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2024-03-14 Philip Buczak, Andreas Groll, Markus Pauly, Jakob Rehof, Daniel Horn
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Weighted likelihood methods for robust fitting of wrapped models for p-torus data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2024-03-11 Claudio Agostinelli, Luca Greco, Giovanni Saraceno
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Robust Bayesian small area estimation using the sub-Gaussian $$\alpha$$ -stable distribution for measurement error in covariates AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2024-03-06
Abstract In small area estimation, the sample size is so small that direct estimators have seldom enough adequate precision. Therefore, it is common to use auxiliary data via covariates and produce estimators that combine them with direct data. Nevertheless, it is not uncommon for covariates to be measured with error, leading to inconsistent estimators. Area-level models accounting for measurement
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Post-processing for Bayesian analysis of reduced rank regression models with orthonormality restrictions AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-12-20 Christian Aßmann, Jens Boysen-Hogrefe, Markus Pape
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Bayesian generalized additive model selection including a fast variational option AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-12-15 Virginia X. He, Matt P. Wand
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A note on sufficient dimension reduction with post dimension reduction statistical inference AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-12-13 Kyongwon Kim
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Zero-modified count time series modeling with an application to influenza cases AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-11-27 Marinho G. Andrade, Katiane S. Conceição, Nalini Ravishanker
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Mixtures of generalized normal distributions and EGARCH models to analyse returns and volatility of ESG and traditional investments AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-11-18 Pierdomenico Duttilo, Stefano Antonio Gattone, Barbara Iannone
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Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-11-15 David Rügamer, Florian Pfisterer, Bernd Bischl, Bettina Grün
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GPS data on tourists: a spatial analysis on road networks AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-11-03 Nicoletta D’Angelo, Antonino Abbruzzo, Mauro Ferrante, Giada Adelfio, Marcello Chiodi
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A Bayesian approach to modeling topic-metadata relationships AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-11-03 Patrick Schulze, Simon Wiegrebe, Paul W. Thurner, Christian Heumann, Matthias Aßenmacher
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Conditional sum of squares estimation of k-factor GARMA models AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-10-31 Paul M. Beaumont, Aaron D. Smallwood
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Measures of interrater agreement for quantitative data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-10-10 Daniela Marella, Giuseppe Bove
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Calibrated imputation for multivariate categorical data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-10-05 Ton de Waal, Jacco Daalmans
Non-response is a major problem for anyone collecting and processing data. A commonly used technique to deal with missing data is imputation, where missing values are estimated and filled in into the dataset. Imputation can become challenging if the variable to be imputed has to comply with a known total. Even more challenging is the case where several variables in the same dataset need to be imputed
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Editorial AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-09-15 Harry Haupt, Thomas Kneib, Yarema Okhrin
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Debiasing SHAP scores in random forests AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-08-22 Markus Loecher
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A family of consistent normally distributed tests for Poissonity AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-06-15 Antonio Di Noia, Marzia Marcheselli, Caterina Pisani, Luca Pratelli
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Correlation-type goodness-of-fit tests based on independence characterizations AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-05-04 Katarina Halaj, Bojana Milošević, Marko Obradović, M. Dolores Jiménez-Gamero
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Conditional feature importance for mixed data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-04-29 Kristin Blesch, David S. Watson, Marvin N. Wright
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Clustering of extreme values: estimation and application AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-03-31 Marta Ferreira
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Robust estimation of fixed effect parameters and variances of linear mixed models: the minimum density power divergence approach AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-03-29 Giovanni Saraceno, Abhik Ghosh, Ayanendranath Basu, Claudio Agostinelli
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A spatial semiparametric M-quantile regression for hedonic price modelling AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-03-30 Francesco Schirripa Spagnolo, Riccardo Borgoni, Antonella Carcagnì, Alessandra Michelangeli, Nicola Salvati
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Lasso-based variable selection methods in text regression: the case of short texts AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-03-20 Marzia Freo, Alessandra Luati
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A dynamic causal modeling of the second outbreak of COVID-19 in Italy AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-02-07 Massimo Bilancia, Domenico Vitale, Fabio Manca, Paola Perchinunno, Luigi Santacroce
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Left-truncated health insurance claims data: theoretical review and empirical application AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-02-02 Rafael Weißbach, Achim Dörre, Dominik Wied, Gabriele Doblhammer, Anne Fink
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Statistical guarantees for sparse deep learning AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-01-24 Johannes Lederer
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Addressing non-normality in multivariate analysis using the t-distribution AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2023-01-21 Felipe Osorio, Manuel Galea, Claudio Henríquez, Reinaldo Arellano-Valle
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Bayesian ridge regression for survival data based on a vine copula-based prior AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-12-30 Hirofumi Michimae, Takeshi Emura
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Hedonic pricing modelling with unstructured predictors: an application to Italian Fashion Industry AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-12-13 Federico Crescenzi
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Estimating the Impact of Medical Care Usage on Work Absenteeism by a Trivariate Probit Model with Two Binary Endogenous Explanatory Variables AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-10-18 Panagiota Filippou, Giampiero Marra, Rosalba Radice, David Zimmer
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Control charts for measurement error models AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-10-05 Vasyl Golosnoy, Benno Hildebrandt, Steffen Köhler, Wolfgang Schmid, Miriam Isabel Seifert
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Sieve bootstrapping the memory parameter in long-range dependent stationary functional time series AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-10-01 Han Lin Shang
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Hierarchical disjoint principal component analysis AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-08-24 Carlo Cavicchia, Maurizio Vichi, Giorgia Zaccaria
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Distributional properties of continuous time processes: from CIR to bates AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-08-25 Ostap Okhrin, Michael Rockinger, Manuel Schmid
In this paper, we compute closed-form expressions of moments and comoments for the CIR process which allows us to provide a new construction of the transition probability density based on a moment argument that differs from the historic approach. For Bates’ model with stochastic volatility and jumps, we show that finite difference approximations of higher moments such as the skewness and the kurtosis
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Multiple imputation of ordinal missing not at random data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-08-22 Angelina Hammon
We introduce a selection model-based imputation approach to be used within the Fully Conditional Specification (FCS) framework for the Multiple Imputation (MI) of incomplete ordinal variables that are supposed to be Missing Not at Random (MNAR). Thereby, we generalise previous work on this topic which involved binary single-level and multilevel data to ordinal variables. We apply an ordered probit
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Testing for the presence of treatment effect under selection on observables AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-08-09 Pier Luigi Conti, Livia De Giovanni
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Authors' response: on the role of data, statistics and decisions in a pandemic. AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-07-30 Beate Jahn,Sarah Friedrich,Joachim Behnke,Joachim Engel,Ursula Garczarek,Ralf Münnich,Markus Pauly,Adalbert Wilhelm,Olaf Wolkenhauer,Markus Zwick,Uwe Siebert,Tim Friede
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A new price index for multi-period and multilateral comparisons AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-07-12 Mario Faliva, Consuelo Rubina Nava, Maria Grazia Zoia
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Editorial special issue: Statistics in sports AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-07-11 Andreas Groll, Dominik Liebl
Triggered by advances in data gathering technologies, the use of statistical analyzes, predictions and modeling techniques in sports has gained a rapidly growing interest over the last decades. Today, professional sports teams have access to precise player positioning data and sports scientists design experiments involving non-standard data structures like movement-trajectories. This special issue
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Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-07-04 Manlio Migliorati, Marica Manisera, Paola Zuccolotto
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Correction to: Local spatial log-Gaussian Cox processes for seismic data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-30 Nicoletta D’Angelo, Marianna Siino, Antonino D’Alessandro, Giada Adelfio
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Comment “On the role of data, statistics and decisions in a pandemic” by Jahn et al. AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-18 Michael Höhle
We comment the paper by Jahn et al. (On the role of data, statistics and decisions in a pandemic, 2022).
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Having a ball: evaluating scoring streaks and game excitement using in-match trend estimation AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-17 Claus Thorn Ekstrøm, Andreas Kryger Jensen
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Discussion on On the role of data, statistics and decisions in a pandemic AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-10 Ursula Berger, Göran Kauermann, Helmut Küchenhoff
The authors make an important contribution presenting a comprehensive and thoughtful overview about the many different aspects of data, statistics and data analyses in times of the recent COVID-19 pandemic discussing all relevant topics. The paper certainly provides a very valuable reflection of what has been done, what could have been done and what needs to be done. We contribute here with a few comments
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Describing a landscape we are yet discovering. AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-09 Sebastian Contreras,Jonas Dehning,Viola Priesemann
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Hierarchical clustering and matrix completion for the reconstruction of world input–output tables AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-06-02 Rodolfo Metulini, Giorgio Gnecco, Francesco Biancalani, Massimo Riccaboni
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Comment on: On the role of data, statistics and decisions in a pandemic statistics for climate protection and health—dare (more) progress! AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-05-21 Walter J. Radermacher
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Tests of stochastic dominance with repeated measurements data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-05-11 Angel G. Angelov, Magnus Ekström
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On dealing with the unknown population minimum in parametric inference AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-05-05 Matheus Henrique Junqueira Saldanha, Adriano Kamimura Suzuki
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Local spatial log-Gaussian Cox processes for seismic data AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-25 Nicoletta D’Angelo, Marianna Siino, Antonino D’Alessandro, Giada Adelfio
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Some measures of kurtosis and their inference on large datasets AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-14 Claudio Giovanni Borroni, Lucio De Capitani
This paper deals with the estimation of kurtosis on large datasets. It aims at overcoming two frequent limitations in applications: first, Pearson's standardized fourth moment is computed as a unique measure of kurtosis; second, the fact that data might be just samples is neglected, so that the opportunity of using suitable inferential tools, like standard errors and confidence intervals, is discarded
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A quantile regression perspective on external preference mapping AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-12 Cristina Davino, Tormod Næs, Rosaria Romano, Domenico Vistocco
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Group sparse recovery via group square-root elastic net and the iterative multivariate thresholding-based algorithm AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-08 Wanling Xie, Hu Yang
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On the role of data, statistics and decisions in a pandemic AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-07 Beate Jahn, Sarah Friedrich, Joachim Behnke, Joachim Engel, Ursula Garczarek, Ralf Münnich, Markus Pauly, Adalbert Wilhelm, Olaf Wolkenhauer, Markus Zwick, Uwe Siebert, Tim Friede
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Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-04-06 Xiaoshuang Zhou, Peixin Zhao, Yujie Gai
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Correction to: Assessment of agricultural sustainability in European Union countries: a group-based multivariate trajectory approach AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-03-17 Alessandro Magrini
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On the Gaussian representation of the Riesz probability distribution on symmetric matrices AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-03-06 Abdelhamid Hassairi, Fatma Ktari, Raoudha Zine
The Riesz probability distribution on symmetric matrices represents an important extension of the Wishart distribution. It is defined by its Laplace transform involving the notion of generalized power. Based on the fact that some Wishart distributions are presented by the mean of the multivariate Gaussian distribution, it is shown that some Riesz probability distributions which are not necessarily
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Assessment of agricultural sustainability in European Union countries: a group-based multivariate trajectory approach AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-03-05 Alessandro Magrini
Sustainability of agriculture is difficult to measure and assess because it is a multidimensional concept that involves economic, social and environmental aspects and is subjected to temporal evolution and geographical differences. Existing studies assessing agricultural sustainability in the European Union (EU) are affected by several shortcomings that limit their relevance for policy makers. Specifically
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Action rate models for predicting actions in soccer AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-03-02 Uwe Dick, Ulf Brefeld
We present a data-driven approach to predict the next action in soccer. We focus on passing actions of the ball possessing player and aim to forecast the pass itself and when, in time, the pass will be played. At the same time, our model estimates the probability that the player loses possession of the ball before she can perform the action. Our approach consists of parameterized exponential rate models
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Scoring predictions at extreme quantiles AStA. Adv. Stat. Anal. (IF 1.4) Pub Date : 2022-02-14 Axel Gandy, Kaushik Jana, Almut E. D. Veraart
Prediction of quantiles at extreme tails is of interest in numerous applications. Extreme value modelling provides various competing predictors for this point prediction problem. A common method of assessment of a set of competing predictors is to evaluate their predictive performance in a given situation. However, due to the extreme nature of this inference problem, it can be possible that the predicted