Prof. Dr. Enno Mammen

Professor - aktiv

Position / Amtsbezeichnung
Universität Mannheim
Fakultät für Rechtswissenschaft und Volkswirtschaftslehre
Abteilung Volkswirtschaftslehre
Ort / PLZ
68131 Mannheim


Publications and Preprints


[1] Approximation von Binomialexperimenten durch Gaußexperimente.Diplomarbeit, University of Heidelberg.


[2] The increase of information due to additional observations in thecase of asymptotically Gaussian experiments. Preprint Nr. 148, SFB 123,University of Heidelberg.


[3] Die statistische Information zusätzlicher Beobachtungen.Dissertation, University of Heidelberg.

[4] Asymptotic power comparison of one-sided tests. Preprint Nr. 298,SFB 123, University of Heidelberg, ( with W.Ehm, D.W.Müller and W.Sauermann).


[5] The statistical information contained in additional observations.Ann. Statist. 14 , 665 - 678.


[6] Optimal local Gaussian approximation of an exponential family.Probab. Th. Rel. Fields 76, 103 - 119.


[7] Asymptotics with increasing dimension for robust regression withapplications to the bootstrap. Ann. Statist. 17, 382 - 400.

[8] A nonparametric regression estimator based on simple assumptionson the shape of the regression function. In: Proceedings of theInternational Workshop on Theory and Practice in Data Analysis,Akademie der Wissenschaften der DDR, Berlin, p. 35 - 41.


[9] On the relation between asymptotic normality and consistency ofbootstrap. Preprint SFB 123, University of Heidelberg.

[10] A short note on optimal bandwidth selection for kernelestimators. Statist. Probab. Lett. 9, 23 - 25.


[11] Estimating a smooth monotone regression function. Ann. Statist.19 724 - 740.

[12] Nonparametric regression under qualitative smoothnessassumptions. Ann. Statist. 19 741 - 759.

[13] Bootstrap methods in nonparametric regression. In: Proceedingsof the NATO Advaced Study Institute on Nonparametric functionalestimation and related topics, Spetses, Greece ( ed. by G. Roussas), p.111 - 124 (with W. Härdle).

[14] Nonparametric curve estimation and simple curve characteristics.In: Proceedings of the NATO Advaced Study Institute on Nonparametricfunctional estimation and related topics, Spetses, Greece ( ed. by G.Roussas), p. 133 - 140.


[15] When does bootstrap work: asymptotic results and simulations.Lecture Notes in Statistics 77, Springer Verlag, New York,Heidelberg.

[16] Higher - order accuracy of bootstrap for smooth functionals.Scand. J. Statist. 19 255 - 270.

[17] Some asymptotics for multimodality tests based on kernel densityestimates. Probab. Th. Rel. Fields 91 115 - 132 (with J. S. Marron andN. I. Fisher).

[18] Bootstrap, wild bootstrap, and asymptotic normality. Probab. Th.Rel. Fields 93 439 - 455.


[19] Comparing non parametric versus parametric regression fits .Ann. Statist. 21 1926 - 1947, (with W. Härdle).

[20] Bootstrap and wild bootstrap for high - dimensional linearmodels. Ann. Statist. 21 255 - 285.

[21] Bootstrap, wild bootstrap and generalized bootstrap. Preprint,Institut für Mathematik, Humboldt - Universität.


[22] Testing for multimodality. Computational Statistics & DataAnalysis 18 499 - 512 (with N. I. Fisher and J. S. Marron).

[23] On general resampling algorithms and their performance indistribution estimation. Ann. Statist. 22 2011 - 2031 (with P.Hall).


[24] On qualitative smoothness of kernel density estimates.Statistics 26 253 - 267.

[25] Power robustification of approximately linear tests. JournalAmerican Statist. Assoc. 90 1025 - 1033 (with W. Ehm and D. W.Müller)

[26] Asymptotical minimax recovery of sets with smooth boundaries.Ann. Statist. 23 502 -524 (with A. B. Tsybakov).


[27] Behaviour of kernel density estimates and bandwidth selectorsfor contaminated data sets. Statistics 28 89 - 104. (with B. U.Park).

[28] Empirical processes of residuals for high - dimensional linearmodels. Ann. Statist. 24 307 -335

[29] Estimation of functions with spatially inhomogeneous smoothness:an approach based on total variation penalties. ZAMM - Zeitschrift fürAngewandte Mathematik und Mechanik 76 Suppl. 3 139 - 142, (with S. vande Geer)


[30] Local adaptive regression splines. Ann. Statist. 25 387 - 413(with S. van de Geer).

[31] Optimal spatial adaptation to inhomogeneous smoothness: anapproach based on kernel estimates with variable bandwidth selectors.Ann. Statist. 25 929 - 947 (with O. V. Lepskii and V. G. Spokoiny)

[32] Penalized quasi-likelihood estimation in partial linear models.Ann. Statist. 25 1014 - 1035 (with S. van de Geer)

[33] Mass recentered kernel smoothers. Biometrika 84 765 - 778 (withJ. S. Marron)

[34] Optimal smoothing in adaptive location estimation. J. Stat.Plann. Inference 58 333 - 348, Add. 67 165 (with B. U. Park)

[35] The shape of kernel density estimates in higher dimensions.Mathematical Methods of Statisitcs 6 440 - 464 (with V. Konakov)

[36] Introduction to "P. Hall (1988). Theoretical comparison ofbootstrap confidence intervals. Ann. Statist. 16, 927-985" . In:Breakthroughs in Statistics Vol. III, edit. by S. Kotz and N. L.Johnson, Springer, New York, Berlin, Heidelberg 483 - 488.


[37] On local adaptivity of kernel estimates with plug - in localbandwidth selectors. Scand. J. Statist. 25 503-520 (with I. Gijbels)

[38] Direct estimation of low dimensional components in additivemodels. Ann. Statist. 26 943 - 971 (with J. Fan and W. Härdle)

[39] Testing parametric versus semiparametric modelling ingeneralized linear models. J. Amer. Statist. Assoc. 93 1461 - 1474(with W. Härdle and M. Müller)


[40] Smoothing splines and shape restrictions. Scand. J. Statist. 26239 - 252 (with C. Thomas-Agnan)

[41] On Estimation of Monotone and Concave Frontier Functions. J.Amer. Statist. Assoc., 94 220 - 228 (with I. Gijbels, B.U. Park and L.Simar)

[42] Smooth discrimination analysis. Ann. Statist. 27, 1808 - 1829(with A. B. Tsybakov)

[43] The existence and asymptotic properties of a backfittingprojection algorithm under weak conditions. Ann. Statist. 27, 1443 -1490 (with O. Linton and J. Nielsen)


[44] Local limit theorems for transition densities of Markov chainsconverging to diffusions. Probability Theory and rel. Fields117, 551-587 (with V. Konakov)

[45] Resampling methods for curve estimation. In Smoothing andRegression. Approaches, Computation and Application (M. G. Schimek,edit.) Wiley, New York.

[46] Evaluating the C-CAPM and the equity premium puzzle at short andlong horizons. Preprint. (with T. Engsted and C. Tanggaard)

[47] Semiparametric additive indices for binary response andgeneralized additive models. Preprint (with W. Härdle, S. Huet and S.Sperlich)


[48] A general framework for constrained smoothing. StatisticalScience 16, 232-248 (with J. S. Marron, B. A. Turlach and M. P.Wand)

[49] Local approximations of Markov random walks by diffusions.Stochastic Processes and their Applications 96, 73-98 (with V.Konakov)

[50] Estimating yield curves by kernel smoothing methods. Journalof Econometrics 105/1, 185-223 (with O. Linton, J. Nielsenand C. Tanggaard)

[51] A bootstrap test for single index models. Statistics 35,427-452 (with W. Härdle and I. Proença)

[52] Generalised structured models. Biometrika 90551-566 (with J. P. Nielsen)


[53] Edgeworth type expansions for Euler schemes for stochasticdifferential equations.Monte Carlo Methods and Applications 8,271-286. (with V. Konakov)

[54] Bootstrap of kernel smoothing in nonlinear time series.Bernoulli 8, 1-39. ( with J. Franke and J. -P. Kreiss)

[55] Estimation in an additive model when the parameters are linkedparametrically.Econometric Theory 18, 886-912 (with R. J.Carroll and W. Härdle)

[56] Properties of the nonparametric autoregressive bootstrap. J.Time Series Analysis 23, 555-586 (with J. Franke, J.-P. Kreiss andM. H. Neumann)


[57] More efficient kernel estimation in nonparametric regressionwith autocorrelated errors. Journal of the American StatisticalAsscoiation, 98, 980-992 (with R. J. Carroll, O. Linton, and Z.Xiao)

[58] Accounting for correlation in marginal longitudinalnonparametric regression. Second Seattle Symposium on Biostatistics, editors D. Lin and P.J. Heagerty, Lecture Notes inStatistics 179, springer, New York. (with Linton, O. B., Lin, X. andCarroll, R. J.)

[59] Nonparametric smoothing methods for a class of non-standardcurve estimation problems. In: Recent advances and trends innonparametric statistics (M.G. Akritas and D. N. Politis, eds.,Elsevier, Amsterdam (with Linton, O. B.)


[60] Bootstrap inference in semiparametric generalized additivemodels. Econometric Theory 20 265-300 (with W. Härdle, S.Huet and S. Sperlich)

[61] Change of the nature of a test when surrogate data are applied.Physical Review E 70 016121 (11 pages)(with S. Nandi)

[62] Nonparametric estimation of an additive model with a linkfunction. Ann. Statist.,32, 2412-2443. (with J.Horowitz)

[63] Bootstrap and resampling. In Handbook of ComputationalStatistics. Editors: J. E. Gentle, W. Härdle, Y. Mori, Springer Berlin,p. 467-496 (with S. Nandi)


[64] Edgeworth type expansions for transition densities of Markov chains converging to diffusions. Bernoulli 11 591–641 (with V. Konakov)

[65] Estimating semiparametric ARCH(¥)models by kernel smoothing methods. Econometrica 73771-836 (with Linton, O. B.)

[66] Bandwidth selection for smooth backfitting in additive models.Ann. Statist. 33 1260- 1294. (with B. U. Park)


[67] Optimal estimation in additive regression models. Bernoulli, 12, 271-298. (with J. Horowitz and J. Klemelä)

[68] Some Theoretical Properties of Phase Randomized Multivariate Surrogates preprint (with S. Nandi)

[69] A simple smooth backfitting method for additive models. Ann. Statist., 34, 2252-2271 (with B. U. Park)


[70] A semiparametric factor model for implied volatility surface dynamics J. Financial Econometrics, 5, 189-218 (with Fengler, M., W. Härdle)

[71] Rate-optimal estimation for a general class of nonparametric regression models. Ann. Statist., to appear (with J. Horowitz )

[72] Smooth backfitting in generalized additive models. Ann. Statist., to appear (with K. Yu and B. U.Park)

[73] A general approach to the predictability issue in survival analysis with applications. Biometrika , to appear (with J. P. Nielsen)

[74] Additive Isotone Regression. IMS Lecture Notes, to appear (with K. Yu)

[75] Identification of Marginal Effects in Nonseparable Models without Monotonicity. Econometrica, to appear (with S. Hoderlein)

[76] Nonparametric Transformation to White Noise. J. of Econometrics, to appear (with O. Linton)

[77] Partial identification and nonparametric estimation of nonseparable, nonmonotonic functions. preprint (with S. Hoderlein)

[78] Nonparametric additive models for panels of time series. preprint (with B. Støve and D. Tjøstheim)

[79] Small time Edgeworth-type expansions for weakly convergent nonhomogenous Markov chains. preprint (with V. Konakov)

[80] Fully Automatic Bandwidth Selection for Kernel Regression With Correlated Errors. preprint (with Y. K. Lee and B. Park)

[81] Oracle-efficient estimation of an additive model with an unknown link function. preprint (with J. Horowitz)

[82] Time Series Modelling with Semiparametric Factor Dynamics. preprint (with S. Borak, W. Härdle and B. Park)

[83] Additivity Tests Based on Smooth Backfitting. preprint (with S. Sperlich)

[84] Nonparametric Additive Regression for Repeatedly Measured Data. preprint (with K. Yu, R. Carroll and A. Maity)

[85] Reconsidering the Random Coefficient Model. preprint (with S. Hoderlein and J. Klemelä)

Teile diesen Professor

Nutzungshinweise: Jede natürliche Person darf sich nur mit einer E-Mail Adresse bei WiWi-Online registrieren lassen. Die Nutzung der Daten die WiWi-Online bereitstellt ist nur für den privaten Gebrauch bestimmt - eine gewerbliche Nutzung ist verboten. Eine automatisierte Nutzung von WiWi-Online und dessen Inhalte, z.B. durch Offline-Browser, Download-Manager oder Webseiten etc. ist ausdrücklich strengstens untersagt. Zuwiderhandlungen werden straf- und zivilrechtlich verfolgt.