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Humboldt-Universität zu Berlin - Statistics

Publications

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2019+

Assessing the relationship between markers of glycemic control through flexible copula regression models
Espasandin Dominguez, E, Cadarso-Suárez, C, Kneib, T, Marra, G, Klein, N, Radice, R, Lado-Baleato, O, and Gude, F
Accepted for publication in Statistics in Medicine.
Directional Bivariate Quantiles – A Robust Approach based on the Cumulative Distribution Function
Klein, N and Kneib, T
Accepted for publication in AStA Advances in Statistical Analysis.
Modelling Regional Patterns of Inefficiency: A Bayesian Approach to Geoadditive Panel Stochastic Frontier Analysis with an Application to Cereal Production in England and Wales
Klein, N, Herwartz, H, and Kneib, T
Accepted for publication in Journal of Econometrics.

2019

Bayesian Inference for Regression Copulas
Smith, MS and Klein, N
arXiv:1907.04529.
Bayesian Variable Selection for Non-Gaussian Responses: A Marginally Calibrated Copula Approach
Klein, N and Smith, MS
arXiv:1907.04530.
Implicit Copulas from Bayesian Regularized Regression Smoothers
Klein, N and Smith, M
Bayesian Analysis.
Inference for L2-Boosting
Rügamer, D and Greven, S
Statistics and Computing.
Mixed binary-continuous copula regression models with application to adverse birth outcomes
Klein, N, Kneib, T, Marra, G, Radice, R, Rokicki, S, and McGovern, M
Statistics in Medicine, 38(3):413–436.
Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T, Klein, N, Lang, S, and Umlauf, N
Test, 28(1).
Multivariate Conditional Transformation Models
Klein, N, Hothorn, T, and Kneib, T
arXiv:1906.03151.
Multivariate effect priors in bivariate semiparametric recursive Gaussian models
Thaden, H, Klein, N, and Kneib, T
Computational Statistics and Data Analysis, 137:51–66.
Rejoinder on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T, Klein, N, Lang, S, and Umlauf, N
Test, 28(1):55–59.
Response to the letter of “Under-reported data analysis with INAR-hidden Markov chains”
Fernández-Fontelo, A, Cabaña, A, Puig, P, and Moriña, D
Statistics in Medicine, 38(5):899-900.
Temporal dynamics of Middle East respiratory syndrome coronavirus in the Arabian Peninsula, 2012-2017
Alkhamis, M, Fernández-Fontelo, A, Vanderwaal, K, Abuhadida, S, Puig, P, and Alba-Casals, A
Epidemiology and Infection, 147.

2018

An exact goodness-of-fit test based on the occupancy problems to study zero-inflation and zero-deflation in biological dosimetry data
Fernández-Fontelo, A, Puig, P, Ainsbury, E, and Higueras, M
Radiation Protection Dosimetry, 179(4):317-326.
BAMLSS: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Umlauf, N, Klein, N, and Zeileis, A
Journal of Computational and Graphical Statistics, 27(3):612–627.
Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects
Michaelis, P, Klein, N, and Kneib, T
Journal of Computational and Graphical Statistics, 27(3):602–611.
Boosting factor-specific functional historical models for the detection of synchronization in bioelectrical signals
Rügamer, D, Brockhaus, S, Gentsch, K, Scherer, K, and Greven, S
Journal of the Royal Statistical Society. Series C: Applied Statistics, 67(3):621-642.
Die Implementation und Evaluation eines Flipped Classrooms in einer Großveranstaltung der Statistik
Förster, M, Heiß, F, Klinke, S, Maur, A, Schank, T, and Weise, C
Beiträge zur Hochschulforschung(4):50.67.
Fast symmetric additive covariance smoothing
Cederbaum, J, Scheipl, F, and Greven, S
Computational Statistics and Data Analysis, 120:25-41.
More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach
Helbich, M, Klein, N, Roberts, H, Hagedoorn, P, and Groenewegen, P
Environmental Research, 166:290–297.
Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
Happ, C and Greven, S
Journal of the American Statistical Association, 113(522):649-659.
Nonlinear association structures in flexible Bayesian additive joint models
Köhler, M, Umlauf, N, and Greven, S
Statistics in Medicine, 37(30):4771-4788.
Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany
Pross, C, Strumann, C, Geissler, A, Herwartz, H, and Klein, N
PLoS ONE, 13(9).
R-Package ‘sdPrior’: Scale-Dependent Hyperpriors in Structured Additive Distributional Regression
Klein, N
Miscellaneous publication, https://cran.r-project.org/web/packages/sdPrior/index.html.
Selective inference after likelihood- or test-based model selection in linear models
Rügamer, D and Greven, S
Statistics and Probability Letters, 140:7-12.
Serotonin selective reuptake inhibitor treatment improves cognition and grey matter atrophy but not amyloid burden during two-year follow-up in mild cognitive impairment and Alzheimer's disease patients with depressive symptoms
Brendel, M, Sauerbeck, J, Greven, S, Kotz, S, Scheiwein, F, Blautzik, J, Delker, A, Pogarell, O, Ishii, K, Bartenstein, P, Rominger, A, and Initiative, ftADN
Journal of Alzheimer's Disease, 65(3):793-806.
Signal regression models for location, scale and shape with an application to stock returns
Brockhaus, S, Fuest, A, Mayr, A, and Greven, S
Journal of the Royal Statistical Society. Series C: Applied Statistics, 67(3):665-686.
Single-Index-Based CoVaR With Very High-Dimensional Covariates
Fan, Y, Härdle, W, Wang, W, and Zhu, L
Journal of Business and Economic Statistics, 36(2):212-226.
Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression
Ríos-Pena, L, Kneib, T, Cadarso-Suárez, C, Klein, N, and Marey-Pérez, M
Environmental Modelling and Software:107–118.
The impact of model assumptions in scalar-on-image regression
Happ, C, Greven, S, and Schmid, V
Statistics in Medicine, 37(28):4298-4317.

2017

A general framework for functional regression modelling
Greven, S and Scheipl, F
Statistical Modelling, 17(1-2):1-35.
Applying INAR-hidden Markov chains in the analysis of under-reported data
Fernández-Fontelo, A, Cabaña, A, Puig, P, and Moriña, D
Trends in Mathematics, 7:29-34.
Boosting flexible functional regression models with a high number of functional historical effects
Brockhaus, S, Melcher, M, Leisch, F, and Greven, S
Statistics and Computing, 27(4):913-926.
Boosting joint models for longitudinal and time-to-event data
Waldmann, E, Taylor-Robinson, D, Klein, N, Kneib, T, Pressler, T, Schmid, M, and Mayr, A
Biometrical Journal, 59(6):1104–1121.
Editorial “Joint modeling of longitudinal and time-to-event data and beyond”
Cadarso Suárez, C, Klein, N, Kneib, T, Molenberghs, G, and Rizopoulos, D
Biometrical Journal, 59(6):1101–1103.
Flexible Bayesian additive joint models with an application to type 1 diabetes research
Köhler, M, Umlauf, N, Beyerlein, A, Winkler, C, Ziegler, A, and Greven, S
Biometrical Journal, 59(6):1144-1165.
Integer-valued AR processes with Hermite innovations and time-varying parameters: An application to bovine fallen stock surveillance at a local scale
Fernández-Fontelo, A, Fontdecaba, S, Alba, A, and Puig, P
Statistical Modelling, 17(3):172-195.
Integrating multivariate conditionally autoregressive spatial priors into recursive bivariate models for analyzing environmental sensitivity of mussels
Thaden, H, Pata, M, Klein, N, Cadarso-Suárez, C, and Kneib, T
Spatial Statistics, 22:419–433.
Joint modeling of longitudinal autoantibody patterns and progression to type 1 diabetes: results from the TEDDY study
Köhler, M, Beyerlein, A, Vehik, K, Greven, S, Umlauf, N, Lernmark, �, Hagopian, W, Rewers, M, She, J, Toppari, J, Akolkar, B, Krischer, J, Bonifacio, E, Ziegler, A, Bautista, K, Baxter, J, Bedoy, R, Felipe-Morales, D, Driscoll, K, Frohnert, B, Gesualdo, P, Hoffman, M, Karban, R, Liu, E, Norris, J, Samper-Imaz, A, Steck, A, Waugh, K, Wright, H, Simell, O, Adamsson, A, Ahonen, S, Hyöty, H, Ilonen, J, Jokipuu, S, Kallio, T, Karlsson, L, Kähönen, M, Knip, M, Kovanen, L, Koreasalo, M, Kurppa, K, Latva-aho, T, Lönnrot, M, Mäntymäki, E, Multasuo, K, Mykkänen, J, Niininen, T, Niinistö, S, Nyblom, M, Rajala, P, Rautanen, J, Riikonen, A, Riikonen, M, Rouhiainen, J, Romo, M, Simell, T, Simell, V, Sjöberg, M, Stenius, A, Leppänen, M, Vainionpää, S, Varjonen, E, Veijola, R, Virtanen, S, Vähä-Mäkilä, M, Åkerlund, M, Lindfors, K, Schatz, D, Hopkins, D, Steed, L, Thomas, J, Adams, J, Silvis, K, Haller, M, Gardiner, M, McIndoe, R, Sharma, A, Williams, J, Young, G, Anderson, S, Jacobsen, L, Ziegler, A, Hummel, M, Hummel, S, Foterek, K, Janz, N, Kersting, M, Knopff, A, Koletzko, S, Peplow, C, Roth, R, Scholz, M, Stock, J, Warncke, K, Wendel, L, Winkler, C, Agardh, D, Aronsson, C, Ask, M, Bremer, J, Carlsson, U, Cilio, C, Ericson-Hallström, E, Fransson, L, Gard, T, Gerardsson, J, Bennet, R, Hansen, M, Hansson, G, Hyberg, S, Johansen, F, Jonsdottir, B, Larsson, H, Lindström, M, Lundgren, M, Månsson-Martinez, M, Markan, M, Melin, J, Mestan, Z, Ottosson, K, Rahmati, K, Ramelius, A, Salami, F, Sibthorpe, S, Sjöberg, B, Swartling, U, Amboh, E, Törn, C, Wallin, A, Wimar, �, Åberg, S, Killian, M, Crouch, C, Skidmore, J, Carson, J, Dalzell, M, Dunson, K, Hervey, R, Johnson, C, Lyons, R, Meyer, A, Mulenga, D, Tarr, A, Uland, M, Willis, J, Becker, D, Franciscus, M, Smith, M, Daftary, A, Klein, M, Yates, C, Abbondondolo, M, Austin-Gonzalez, S, Avendano, M, Baethke, S, Brown, R, Burkhardt, B, Butterworth, M, Clasen, J, Cuthbertson, D, Eberhard, C, Fiske, S, Garcia, D, Garmeson, J, Gowda, V, Heyman, K, PerezLaras, F, Lee, H, Liu, S, Liu, X, Lynch, K, Malloy, J, McCarthy, C, Meulemans, S, Parikh, H, Shaffer, C, Smith, L, Smith, S, Sulman, N, Tamura, R, Uusitalo, U, Vijayakandipan, P, Wood, K, Yang, J, Ballard, L, Hadley, D, McLeod, W, Yu, L, Miao, D, Bingley, P, Williams, A, Chandler, K, Rokni, S, Williams, C, Wyatt, R, George, G, Grace, S, Erlich, H, Mack, S, Ke, S, Mulholland, N, Bourcier, K, Briese, T, Johnson, S, and Triplett, E
Acta Diabetologica, 54(11):1009-1017.
Mixed modeling for irregularly sampled and correlated functional data: Speech science applications
Pouplier, M, Cederbaum, J, Hoole, P, Marin, S, and Greven, S
Journal of the Acoustical Society of America, 142(2):935-946.
Modelling a response as a function of high-frequency count data: The association between physical activity and fat mass
Augustin, N, Mattocks, C, Faraway, J, Greven, S, and Ness, A
Statistical Methods in Medical Research, 26(5):2210-2226.
Rejoinder
Greven, S and Scheipl, F
Statistical Modelling, 17(1-2):100-115.
Structured additive distributional regression for analysing landings per unit effort in fisheries research
Mamouridis, V, Klein, N, Kneib, T, Cadarso Suarez, C, and Maynou, F
Mathematical Biosciences, 283:145–154.
Studying the relationship between a woman's reproductive lifespan and age at menarche using a Bayesian multivariate structured additive distributional regression model
Duarte, E, de Sousa, B, Cadarso-Suárez, C, Klein, N, Kneib, T, and Rodrigues, V
Biometrical Journal, 59(6):1232–1246.

2016

A consistent two-factor model for pricing temperature derivatives
Groll, A, López-Cabrera, B, and Meyer-Brandis, T
Energy Economics, 55:112-126.
Analysing farmland rental rates using Bayesian geoadditive quantile regression
März, A, Klein, N, Kneib, T, and Musshoff, O
European Review of Agricultural Economics, 43(4):663–698.
Comment
Greven, S and Scheipl, F
Journal of the American Statistical Association, 111(516):1568-1573.
Corridors restore animal-mediated pollination in fragmented tropical forest landscapes
Kormann, U, Scherber, C, Tscharntke, T, Klein, N, Larbig, M, Valente, J, Hadley, A, and Betts, M
Proceedings of the Royal Society B: Biological Sciences, 283(1823).
Functional linear mixed models for irregularly or sparsely sampled data
Cederbaum, J, Pouplier, M, Hoole, P, and Greven, S
Statistical Modelling, 16(1):67-88.
Generalized functional additive mixed models
Scheipl, F, Gertheiss, J, and Greven, S
Electronic Journal of Statistics, 10(1):1455-1492.
Identifiability in penalized function-on-function regression models
Scheipl, F and Greven, S
Electronic Journal of Statistics, 10(1):495-526.
Localizing Temperature Risk
Härdle, W, López Cabrera, B, Okhrin, O, and Wang, W
Journal of the American Statistical Association, 111(516):1491-1508.
Mixed modeling for functional data for research in the speech sciences
Pouplier, M, Cederbaum, J, Hoole, P, and Greven, S
.
Scale-dependent priors for variance parameters in structured additive distributional regression
Klein, N and Kneib, T
Bayesian Analysis, 11(4):1071–1106.
Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach
Klein, N and Kneib, T
Statistics and Computing, 26(4):841–860.
Smoothing parameter uncertainty in general smooth models
Greven, S and Scheipl, F
Invited comment on Wood et al (2016). To appear in the Journal of the American Statistical Association.
TENET: Tail-Event driven NETwork risk
Härdle, W, Wang, W, and Yu, L
Journal of Econometrics, 192(2):499-513.
Under-reported data analysis with INAR-hidden Markov chains
Fernández-Fontelo, A, Cabaña, A, Puig, P, and Moriña, D
Statistics in Medicine, 35(26):4875-4890.
Volatility linkages between energy and agricultural commodity prices
López Cabrera, B and Schulz, F
Energy Economics, 54:190-203.

2015

A General Framework for Functional Regression
Greven, S
In: Proceedings of the 30th International Workshop on Statistical Modelling, ed. by Friedl Herwig and Wagner Helga, pp. 39–54.
A Semiparametric Analysis of Conditional Income Distributions
Sohn, A, Klein, N, and Kneib, T
Schmollers Jahrbuch, 135:13–22.
BayesX - Software for Bayesian inference in structured additive regression models
Belitz, C, Brezger, A, Klein, N, Kneib, T, Lang, S, and Umlauf, N
Miscellaneous publication, http://www.bayesx.org.
Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data
Klein, N, Kneib, T, and Lang, S
Journal of the American Statistical Association, 110(509):405–419.
Bayesian Structured Additive Distributional Regression for Multivariate Responses
Klein, N, Kneib, T, Klasen, S, and Lang, S
Journal of the Royal Statistical Society. Series C: Applied Statistics, 64(4):569–591.
Bayesian structured additive distributional regression with an application to regional income inequality in Germany
Klein, N, Kneib, T, Lang, S, and Sohn, A
Annals of Applied Statistics, 9(2):1024–1052.
Designing an index for assessing wind energy potential
Ritter, M, Shen, Z, López Cabrera, B, Odening, M, and Deckert, L
Renewable Energy, 83:416-424.
Development of new strategies to model bovine fallen stock data from large and small subpopulations for syndromic surveillance use
Alba-Casals, A, Fernández-Fontelo, A, Revie, C, Dórea, F, Sánchez, J, Romero, L, Cáceres, G, Pérez, A, and Puig, P
Epidemiologie et Sante Animale, 67:67-76.
Functional Additive Mixed Models
Scheipl, F, Staicu, A, and Greven, S
Journal of Computational and Graphical Statistics, 24(2):477-501.
Functional regression models for location, scale and shape applied to stock returns
Brockhaus, S, Fuest, A, Mayr, A, and Greven, S
In: Proceedings of the 30th International Workshop on Statistical Modelling, ed. by Friedl Herwig and Wagner Helga, pp. 117–122.
Hedonic house price modeling based on multilevel structured additive regression
Razen, A, Brunauer, W, Klein, N, Lang, S, and Umlauf, N
Springer International Publishing. (ISBN: 9783319114699; 9783319114682).
Hidden markov structures for dynamic copulae
Härdle, W, Okhrin, O, and Wang, W
Econometric Theory, 31(5):981-1015.
Introduction to Statistics: Using Interactive MM*Stat Elements
Härdle, WK, Klinke, S, and Rönz, B
Springer. (ISBN: 978-3-319-17703-8).
Modelling Hospital Admission and Length of Stay by Means of Generalised Count Data Models
Herwartz, H, Klein, N, and Strumann, C
Journal of Applied Econometrics, 31(6):1159–1182.
Penalized function-on-function regression
Ivanescu, A, Staicu, A, Scheipl, F, and Greven, S
Computational Statistics, 30(2):539-568.
Penalized scalar-on-functions regression with interaction term
Fuchs, K, Scheipl, F, and Greven, S
Computational Statistics and Data Analysis, 81:38-51.
Quantile regression in risk calibration
Chao, S, Härdle, W, and Wang, W
Springer New York. (ISBN: 9781461477501; 9781461477495).
State price densities implied from weather derivatives
Karl Härdle, W, López-Cabrera, B, and Teng, H
Insurance: Mathematics and Economics, 64:106-125.
Structured functional principal component analysis
Shou, H, Zipunnikov, V, Crainiceanu, C, and Greven, S
Biometrics, 71(1):247-257.
The functional linear array model
Brockhaus, S, Scheipl, F, Hothorn, T, and Greven, S
Statistical Modelling, 15(3):279-300.
Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models
Härdle, W, Ritov, Y, and Wang, W
Journal of Multivariate Analysis, 134:129-145.
Uniform confidence bands for pricing kernels
Härdle, W, Okhrin, Y, and Wang, W
Journal of Financial Econometrics, 13(2):376-413.

2014

A unifying approach to the estimation of the conditional Akaike information in generalized linear mixed models
Saefken, B, Kneib, T, van Waveren, C, and Greven, S
Electronic Journal of Statistics, 8(1):201-225.
Bivariate Gaussian Distributional Regression: An Application on Diabetes
Klein, N, Gude, F, Cadarso-Suárez, C, and Kneib, T
Proceedings of the 29th International Workshop on Statistical Modelling, 1:167–172.
Comment
Härdle, W and Wang, W
Journal of Business and Economic Statistics, 32(2):173-174.
Functional linear mixed model for irregularly spaced phonetics data
Cederbaum, J, Greven, S, Pouplier, M, and Hoole, P
In: Proceedings of the 29th International Workshop on Statistical Modelling, ed. by Kneib, Thomas and Sobotka, Fabian and Fahrenholz, Jan and Irmer, Henriette.
Longitudinal high-dimensional principal components analysis with application to diffusion tensor imaging of multiple sclerosis
Zipunnikov, V, Greven, S, Shou, H, Caffo, B, Reich, D, and Crainiceanu, C
Annals of Applied Statistics, 8(4):2175-2202.
Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape
Klein, N, Denuit, M, Lang, S, and Kneib, T
Insurance: Mathematics and Economics, 55(1):225–249.
Nonparametric estimates for conditional quantiles of time series
Franke, J, Mwita, P, and Wang, W
AStA Advances in Statistical Analysis, 99(1):107-130.
Perceptual and articulatory factors in German fricative assimilation
Pouplier, M, Hoole, P, Cederbaum, J, Greven, S, and Pastätter, M
In: Proceedings of the 10th International Seminar on Speech Production (ISSP), ed. by Fuchs, Susanne and Grice, Martine and Hermes, Anne and Lancia, Leonardo and Mücke, Doris, pp. 332–335.
Quantifying alternative splicing from paired-end RNA-sequencing data
Rossell, D, Attolini, C, Kroiss, M, and Stöcker, A
Annals of Applied Statistics, 8(1):309-330.
R-Package ‘BayesX’, R Utilities Accompanying the Software Package BayesX
Kneib, T, Heinzl, F, Brezger, A, Sabanes Bove, D, and Klein, N
Miscellaneous publication, http://cran.r-project.org/web/packages/BayesX.
The Functional Linear Array Model and an Application to Viscosity Curves
Brockhaus, S, Scheipl, F, Hothorn, T, and Greven, S
In: Proceedings of the 29th International Workshop on Statistical Modelling, ed. by Kneib, Thomas and Sobotka, Fabian and Fahrenholz, Jan and Irmer, Henriette, pp. 63–68.

2013

Bayesian Functional Generalized Additive Models with Sparsely Observed Covariates
McLean, MW, Scheipl, F, Hooker, G, Greven, S, and Ruppert, D
.
Bayesian Generalized Additive Models for Location, Scale and Shape for Insurance Data
Klein, N, Kneib, T, and Lang, S
Proceedings of the 28th International Workshop on Statistical Modelling, 2:645–650.
Corrected Confidence Bands for Functional Data Using Principal Components
Goldsmith, J, Greven, S, and Crainiceanu, C
Biometrics, 69(1):41-51.
HMM and HAC
Wang, W, Okhrin, O, and Härdle, W
Advances in Intelligent Systems and Computing, 190 AISC:341-348.
Local quantile regression
Spokoiny, V, Wang, W, and Karl Härdle, W
Journal of Statistical Planning and Inference, 143(7):1109-1129.
Longitudinal scalar-on-functions regression with application to tractography data
Gertheiss, J, Goldsmith, J, Crainiceanu, C, and Greven, S
Biostatistics, 14(3):447-461.
On likelihood ratio testing for penalized splines
Greven, S and Crainiceanu, C
AStA Advances in Statistical Analysis, 97(4):387-402.
Pricing rainfall futures at the CME
López Cabrera, B, Odening, M, and Ritter, M
Journal of Banking and Finance, 37(11):4286-4298.
Prüfung auf nicht-lineare Zusammenhänge und deren Modellierung in der Kompetenzforschung - Ein Beispiel aus dem Projekt ILLEV
Förster, M and Klinke, S
In: Kompetenzmodellierung und Kompetenzmessung bei Studierenden der Wirtschaftswissenschaften und Ingenieurswissenschaften, ed. by Olga Zlatkin-Troitschanskaia and Reinhold Nickolaus and Klaus Beck. Verlag Empirische Pädagogik, chap. Prüfung auf nicht-lineare Zusammenhänge und deren Modellierung in der Kompetenzforschung - Ein Beispiel aus dem Projekt ILLEV, pp. 49-68. (ISBN: 978-3944996004).
Rejoinder: Local quantile regression
Spokoiny, V, Wang, W, and Karl Härdle, W
Journal of Statistical Planning and Inference, 143(7):1145-1149.
Testing for increasing weather risk
Wang, W, Bobojonov, I, Härdle, W, and Odening, M
Stochastic Environmental Research and Risk Assessment, 27(7):1565-1574.
Using wiki to build an e-learning system in statistics in the Arabic language
Ahmad, T, Härdle, W, Klinke, S, and Alawadhi, S
Computational Statistics, 28(2):481–491.

2012

Statistical user interfaces
Klinke, S
Springer Berlin Heidelberg. (ISBN: 9783642215513; 9783642215506).
Variability of fibrinogen measurements in post-myocardial infarction patients: Results from the AIRGENE study center Augsburg
Baumert, J, Karakas, M, Greven, S, Rückerl, R, Peters, A, and Koenig, W
Thrombosis and Haemostasis, 107(5):895-902.

2011

Ambient air pollution and lipoprotein-associated phospholipase A2 in survivors of myocardial infarction
Brüske, I, Hampel, R, Baumgärtner, Z, Rückerl, R, Greven, S, Koenig, W, Peters, A, and Schneider, A
Environmental Health Perspectives, 119(7):921-926.
An approach to the estimation of chronic air pollution effects using spatio-temporal information
Greven, S, Dominici, F, and Zeger, S
Journal of the American Statistical Association, 106(494):396-406.
Mortality due to myocardial infarction in the Bavarian population during World Cup Soccer 2006
Wilbert-Lampen, U, Nickel, T, Scheipl, F, Greven, S, Küchenhoff, H, Kääb, S, and Steinbeck, G
Clinical Research in Cardiology, 100(9):731-736.
Restricted likelihood ratio testing in linear mixed models with general error covariance structure
Wiencierz, A, Greven, S, and Küchenhoff, H
Electronic Journal of Statistics, 5:1718-1734.

2010

Longitudinal functional principal component analysis
Greven, S, Crainiceanu, C, Caffo, B, and Reich, D
Electronic Journal of Statistics, 4:1022-1054.
On the behaviour of marginal and conditional AIC in linear mixed models
Greven, S and Kneib, T
Biometrika, 97(4):773-789.
Reproducibility in serial C-reactive protein and interleukin-6 measurements in post-myocardial infarction patients: Results from the AIRGENE study
Karakas, M, Baumert, J, Greven, S, Rückerl, R, Peters, A, and Koenig, W
Clinical Chemistry, 56(5):861-864.
Schüler/-innen evaluieren Unterricht. Ergebnisse aus dem "Netzwerk Schülerbefragung".
Wagner, C, Grützmann, J, Neumann, U, and Klinke, S
Wirtschaft & Erziehung(7/8):228-233.

2009

Fibrinogen genes modify the fibrinogen response to ambient particulate matter
Peters, A, Greven, S, Heid, I, Baldari, F, Breitner, S, Bellander, T, Chrysohoou, C, Illig, T, Jacquemin, B, Koenig, W, Lanki, T, Nyberg, F, Pekkanen, J, Pistelli, R, Rückerl, R, Stefanadis, C, Schneider, A, Sunyer, J, and Wichmann, H
American Journal of Respiratory and Critical Care Medicine, 179(6):484-491.
Mediterranean diet and inflammatory response in myocardial infarction survivors
Panagiotakos, D, Dimakopoulou, K, Katsouyanni, K, Bellander, T, Grau, M, Koenig, W, Lanki, T, Pistelli, R, Schneider, A, Peters, A, Brueske-Hohfeld, I, Chavez, H, Cyrys, J, Geruschkat, U, Grallert, H, Greven, S, Ibald-Mulli, A, Illig, T, Kirchmair, H, von Klot, S, Kolz, M, Marowsky-Koeppl, M, Mueller, M, Rueckerl, R, Schaffrath Rosario, A, Schneider, A, Wichmann, H, Holle, R, Nagl, H, Fabricius, I, Greschik, C, Güther, F, Haensel, M, Hah, U, Kuch, U, Meisinger, C, Pietsch, M, Rempfer, E, Schaich, G, Schwarzwãlder, I, Zeitler, B, Loewel, H, Koenig, W, Khuseyinova, N, Trischler, G, Forastiere, F, Compagnucci, P, Di Carlo, F, Ferri, M, Montanari, A, Perucci, C, Picciotto, S, Romeo, E, Stafoggia, M, Pistelli, R, Altamura, L, Andreani, M, Baldari, F, Infusino, F, Santarelli, P, Jesi, A, Cattani, G, Marconi, A, Pekkaen, J, Alanne, M, Alastalo, H, Eerola, T, Eriksson, J, Kauppila, T, Lanki, T, Nyholm, P, Perola, M, Salomaa, V, Tiittanen, P, Luotola, K, Bellader, T, Berglind, N, Bohm, K, Härden, R, Lampa, E, Ljungman, P, Nyberg, F, Ohlander, B, Pershagen, G, Rosenqvist, M, Larsdotter Svensson, T, Thunberg, E, Wedeen, G, Sunyer, J, Covas, M, Fitó, M, Grau, M, Jacquemin, B, Marrugat, J, Muñz, L, Perelló, M, Plana, E, Rebato, C, Schroeder, H, Soler, C, Katsouyanni, K, Chalamandaris, A, Dimakopoulou, K, Panaggiotakos, D, Stefanadis, C, Pitasavos, C, Antoiades, C, Chrysohoou, C, Mitropoulos, J, Kulmala, M, Aalto, P, and Paatero, P
International Journal of Epidemiology, 38(3):856-866.
Restricted likelihood ratio testing for zero variance components in linear mixed models
Greven, S, Crainiceanu, C, Küchenhoff, H, and Peters, A
Journal of Computational and Graphical Statistics, 17(4):870-891.

2008

Cardiovascular events during World Cup Soccer
Wilbert-Lampen, U, Leistner, D, Greven, S, Pohl, T, Sper, S, Völker, C, Güthlin, D, Plasse, A, Knez, A, Küchenhoff, H, and Steinbeck, G
New England Journal of Medicine, 358(5):475-483.
Common Genetic Polymorphisms and Haplotypes of Fibrinogen Alpha, Beta, and Gamma Chains Affect Fibrinogen Levels and the Response to Proinflammatory Stimulation in Myocardial Infarction Survivors. The AIRGENE Study
Jacquemin, B, Antoniades, C, Nyberg, F, Plana, E, Müller, M, Greven, S, Salomaa, V, Sunyer, J, Bellander, T, Chalamandaris, A, Pistelli, R, Koenig, W, and Peters, A
Journal of the American College of Cardiology, 52(11):941-952.
DNA variants, plasma levels and variability of C-reactive protein in myocardial infarction survivors: Results from the AIRGENE study
Kolz, M, Koenig, W, Müller, M, Andreani, M, Greven, S, Illig, T, Khuseyinova, N, Panagiotakos, D, Pershagen, G, Salomaa, V, Sunyer, J, and Peters, A
European Heart Journal, 29(10):1250-1258.
Schulprogramme und Schulprogrammarbeit an beruflichen Schulen - Konstruktionsleistungen und Implementationserwartungen.
Buer, Jv, Köller, M, and Klinke, S
Zeitschrift für Berufs- und Wirtschaftspädagogik, 104(3):358-384.
Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models
Scheipl, F, Greven, S, and Küchenhoff, H
Computational Statistics and Data Analysis, 52(7):3283-3299.
Variability of serial lipoprotein-associated phospholipase A2 measurements in post-myocardial infarction patients: Results from the AIRGENE Study Center Augsburg
Khuseyinova, N, Greven, S, Rückerl, R, Trischler, G, Loewel, H, Peters, A, and Koenig, W
Clinical Chemistry, 54(1):124-130.

2007

Air pollution and inflammation (Interleukin-6, C-reactive protein, fibrinogen) in myocardial infarction survivors
Rückerl, R, Greven, S, Ljungman, P, Aalto, P, Antoniades, C, Bellander, T, Berglind, N, Chrysohoou, C, Forastiere, F, Jacquemin, B, von Klot, S, Koenig, W, Küchenhoff, H, Lanki, T, Pekkanen, J, Perucci, C, Schneider, A, Sunyer, J, and Peters, A
Environmental Health Perspectives, 115(7):1072-1080.
Air pollution and inflammatory response in myocardial infarction survivors: Gene-environment interactions in a high-risk group
Peters, A, Schneider, A, Greven, S, Bellander, T, Forastiere, F, Ibald-Mulli, A, Illig, T, Jacquemin, B, Katsouyanni, K, Koenig, W, Lanki, T, Pekkanen, J, Pershagen, G, Picciotto, S, Rückerl, R, Rosario, A, Stefanadis, C, and Sunyer, J
Inhalation Toxicology, 19(SUPPL. 1):161-175.
On the utility of E-learning in statistics
Härdle, W, Klinke, S, and Ziegenhagen, U
International Statistical Review, 75(3):355-364.
Special issue: Workshop data and information visualisation 2006
Klinke, S
Computational Statistics, 22(4):497.

2005

Projection Pursuit for Exploratory Supervised Classification
Lee, E, Cook, D, Klinke, S, and Lumley, T
Journal of Computational and Graphical Statistics, 14(4):831-846.

2004

A parametric model for studying organism fitness using step-stress experiments
Greven, S, Bailer, A, Kupper, L, Muller, K, and Craft, J
Biometrics, 60(3):793-799.

2002

4. Workshop Wirtschaftsstatistik: Inflationsmessung in Deutschland und Europa, Daten - Methoden - Entwicklungen
Schmerbach, S and Klinke, S
Miscellaneous publication, CD.
Proceedings of the Conference CompStat 2002 - Short Communications and Posters
Klinke, S, Ahrend, P, and Richter, L
Miscellaneous publication, CD.

2001

Data Structures for Computational Statistics (Contributions to Statistics)
Klinke, S
Physica. (ISBN: 978-3-7908-0982-4).

2000

XploRe Learning Guide
Härdle, W, Klinke, S, and Müller, M
Springer. (ISBN: 978-3-540-66207-5).
XploRe® - Application Guide
Härdle, W, Hlavka, Z, and Klinke, S
Springer. (ISBN: 978-3-642-57292-0).

1999

Introduction to the special issue on interactive graphical data analysis: What is interaction?
Swayne, DF and Klinke, S
Computational Statistics, 14(1):1-6.

1997

Binning of Kernel-based projection pursuit indices in XGobi
Klinke, S and Cook, D
Computational Statistics and Data Analysis, 25(3):363-369.
Teaching Wavelets in XploRe
Klinke, S, Golubev, Y, Härdle, WK, and Neumann, MH
Computational Statistics, 13(2):141-151.

1995

XploRe: An Interactive Statistical Computing Environment (Statistics and Computing)
Härdle, W, Klinke, S, and Turlach, BA
Springer. (ISBN: 978-0-387-94429-6).

No names specified
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