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Missing data 7 EM algorithm 6 Econometrics 6 Probability Theory and Stochastic Processes 6 Statistical consulting 6 Statistics for Business, Management, Economics, Finance, Insurance 6 Statistics, general 6 Estimation 5 Explainable artificial intelligence 5 Interpretable machine learning 5 Moments 5 Panel data 5 Cointegration 4 Computer experiments 4 Factor analysis 4 Feature importance 4 Measurement error 4 Mixture models 4 Multiple imputation 4 Structural equation modeling 4 Analysis of variance 3 Asymptotic normality 3 Capture–recapture 3 Deep learning 3 Design of experiments 3 Forecasting 3 Functional data 3 Heterogeneity 3 Imputation 3 Monte Carlo simulation 3 Monte Carlo study 3 Regularization 3 Sample selection 3 Statistical process control 3 Stochastic differential equations 3 products of random variables 3 Bayesian analysis 2 Bayesian statistics 2 Beta regression 2 Bradley–Terry model 2
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Undetermined 261 Free 41
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Article 302
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Article 39 Book Review 2
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Undetermined 261 English 41
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Uebe, Götz 11 Nadarajah, Saralees 10 Kauermann, Göran 8 Kneib, Thomas 6 Härdle, Wolfgang 5 Schlittgen, Rainer 5 Schmid, Wolfgang 5 Groll, Andreas 4 Böhning, Dankmar 3 Golosnoy, Vasyl 3 Hassler, Uwe 3 Haupt, Harry 3 Hsiao, Cheng 3 Kotz, Samuel 3 Krumbholz, Wolf 3 Münnich, Ralf 3 Okhrin, Yarema 3 Pauly, Markus 3 Rendtel, Ulrich 3 Schmidt, Klaus 3 Singer, Hermann 3 Webel, Karsten 3 Weiß, Christian 3 Weißbach, Rafael 3 Ötting, Marius 3 Aßenmacher, Matthias 2 Behnke, Joachim 2 Berger, Ursula 2 Bischl, Bernd 2 Blesch, Kristin 2 Brefeld, Ulf 2 Bresson, Georges 2 Böckenhoff, Annette 2 Demetrescu, Matei 2 Doblhammer, Gabriele 2 Dörre, Achim 2 Engel, Joachim 2 Fahrmeir, Ludwig 2 Fickel, Norman 2 Fink, Anne 2
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AStA Advances in Statistical Analysis 302
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RePEc 261 EconStor 41
Showing 31 - 40 of 302
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Describing a landscape we are yet discovering
Contreras, Sebastian; Dehning, Jonas; Priesemann, Viola - In: AStA Advances in Statistical Analysis 106 (2022) 3, pp. 399-402
Persistent link: https://www.econbiz.de/10015181960
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Introducing LASSO-type penalisation to generalised joint regression modelling for count data
van der Wurp, Hendrik; Groll, Andreas - In: AStA Advances in Statistical Analysis 107 (2021) 1-2, pp. 127-151
In this work, we propose an extension of the versatile joint regression framework for bivariate count responses of the R package GJRM by Marra and Radice (R package version 0.2-3, 2020) by incorporating an (adaptive) LASSO-type penalty. The underlying estimation algorithm is based on a quadratic...
Persistent link: https://www.econbiz.de/10014497493
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A smooth dynamic network model for patent collaboration data
Bauer, Verena; Harhoff, Dietmar; Kauermann, Göran - In: AStA Advances in Statistical Analysis 106 (2021) 1, pp. 97-116
The development and application of models, which take the evolution of network dynamics into account, are receiving increasing attention. We contribute to this field and focus on a profile likelihood approach to model time-stamped event data for a large-scale dynamic network. We investigate the...
Persistent link: https://www.econbiz.de/10014497502
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Small area estimation of socioeconomic indicators for sampled and unsampled domains
Burgard, Jan Pablo; Morales, Domingo; Wölwer, Anna-Lena - In: AStA Advances in Statistical Analysis 106 (2021) 2, pp. 287-314
Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based indicators such as the median income of sub-populations can provide information on the impact of measures, e.g., on poverty reduction. Regional information is usually published...
Persistent link: https://www.econbiz.de/10014497551
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A copula-based multivariate hidden Markov model for modelling momentum in football
Ötting, Marius; Langrock, Roland; Maruotti, Antonello - In: AStA Advances in Statistical Analysis 107 (2021) 1-2, pp. 9-27
We investigate the potential occurrence of change points—commonly referred to as “momentum shifts”—in the dynamics of football matches. For that purpose, we model minute-by-minute in-game statistics of Bundesliga matches using hidden Markov models (HMMs). To allow for within-state...
Persistent link: https://www.econbiz.de/10014497575
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Measuring spatial price differentials at the basic heading level: a comparison of stochastic index number methods
Weinand, Sebastian - In: AStA Advances in Statistical Analysis 106 (2021) 1, pp. 117-143
Spatial price comparisons rely to a high degree on the quality of the underlying price data that are collected within or across countries. Below the basic heading level, these price data often exhibit large gaps. Therefore, stochastic index number methods like the Country–Product–Dummy (CPD)...
Persistent link: https://www.econbiz.de/10014497592
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Continuous-time state-space modelling of the hot hand in basketball
Mews, Sina; Ötting, Marius - In: AStA Advances in Statistical Analysis 107 (2021) 1-2, pp. 313-326
We investigate the hot hand phenomenon using data on 110,513 free throws taken in the National Basketball Association. As free throws occur at unevenly spaced time points within a game, we consider a state-space model formulated in continuous time to investigate serial dependence in players’...
Persistent link: https://www.econbiz.de/10014497594
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Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players
Hanck, Christoph; Arnold, Martin C. - In: AStA Advances in Statistical Analysis 107 (2021) 1-2, pp. 177-204
Judging by its significant potential to affect the outcome of a game in one single action, the penalty kick is arguably the most important set piece in football. Scientific studies on how the ability to convert a penalty kick is distributed among professional football players are scarce. In this...
Persistent link: https://www.econbiz.de/10014497598
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Contextual movement models based on normalizing flows
Fadel, Samuel G.; Mair, Sebastian; da Silva Torres, Ricardo - In: AStA Advances in Statistical Analysis 107 (2021) 1-2, pp. 51-72
Movement models predict positions of players (or objects in general) over time and are thus key to analyzing spatiotemporal data as it is often used in sports analytics. Existing movement models are either designed from physical principles or are entirely data-driven. However, the former suffers...
Persistent link: https://www.econbiz.de/10014497613
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On variance estimation under shifts in the mean
Axt, Ieva; Fried, Roland - In: AStA Advances in Statistical Analysis 104 (2020) 3, pp. 417-457
In many situations, it is crucial to estimate the variance properly. Ordinary variance estimators perform poorly in the presence of shifts in the mean. We investigate an approach based on non-overlapping blocks, which yields good results in change-point scenarios. We show the strong consistency...
Persistent link: https://www.econbiz.de/10014503393
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