pvclass: An R Package for p Values for Classification

Autor: Niki Zumbrunnen, Lutz Dümbgen

Publikováno v: Journal of Statistical Software, Vol 78, Iss 1, Pp 1-19 (2017)

Let (X, Y) be a random variable consisting of an observed feature vector X and an unobserved class label Y ∈ {1, 2, . . . , L} with unknown joint distribution. In addition, let D be a training data set consisting of n completely observed independen

Externí odkaz: https://doaj.org/article/590d2bb070eb4ed19a2f9fca3ae871b5

logcondens: Computations Related to Univariate Log-Concave Density Estimation

Autor: Lutz Dümbgen, Kaspar Rufibach

Publikováno v: Journal of Statistical Software, Vol 39, Iss 06 (2011)

Maximum likelihood estimation of a log-concave density has attracted considerable attention over the last few years. Several algorithms have been proposed to estimate such a density. Two of those algorithms, an iterative convex minorant and an active

Externí odkaz: https://doaj.org/article/4108383dbe2b4f11afb45487fc398e22

Active set algorithms for estimating shape-constrained density ratios

Autor: Christof Strähl, Lutz Dümbgen, Alexandre Mösching

Publikováno v: Dümbgen, Lutz; Mösching, Alexandre; Strähl, Christof (2021). Active set algorithms for estimating shape-constrained density ratios. Computational statistics & data analysis, 163, p. 107300. Elsevier 10.1016/j.csda.2021.107300

In many instances, imposing a constraint on the shape of a density is a reasonable and flexible assumption. It offers an alternative to parametric models, which can be too rigid, and to other nonparametric methods, which require the choice of tuning

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::208a887eb2864a18bd222329a3403dca
https://boris.unibe.ch/156874/1/cas-active-set.pdf

Monotone least squares and isotonic quantiles

Autor: Alexandre Mösching, Lutz Dümbgen

Publikováno v: Electron. J. Statist. 14, no. 1 (2020), 24-49
Mösching, Alexandre; Dümbgen, Lutz (2020). Monotone least squares and isotonic quantiles. Electronic journal of statistics, 14(1), pp. 24-49. Institute of Mathematical Statistics 10.1214/19-EJS1659

We consider bivariate observations $(X_{1},Y_{1}),\ldots,(X_{n},Y_{n})$ such that, conditional on the $X_{i}$, the $Y_{i}$ are independent random variables. Precisely, the conditional distribution function of $Y_{i}$ equals $F_{X_{i}}$, where $(F_{x}

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54bb54b6fff79d2c598200fe765ae141
https://projecteuclid.org/euclid.ejs/1578020615

Bi-log-concave Distribution Functions

Autor: Lutz Dümbgen, Petro Kolesnyk, Ralf A. Wilke

Publikováno v: Dümbgen, Lutz; Kolesnyk, Petro; Wilke, Ralf A. (2017). Bi-log-concave distribution functions. Journal of statistical planning and inference, 184, pp. 1-17. Elsevier 10.1016/j.jspi.2016.10.005
Journal of Statistical Planning and Inference

Nonparametric statistics for distribution functions F or densities f = F ′ under qualitative shape constraints constitutes an interesting alternative to classical parametric or entirely nonparametric approaches. We contribute to this area by consid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65747860b2fde9170553739fc14ae165
https://doi.org/10.1016/j.jspi.2016.10.005