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We consider the problem of testing a particular type of composite null hypothesis under a nonparametric multivariate regression model. For a given quadraticfunctional Q, the null hypothesis states tha...
Inter-coder agreement measures, like Cohen’sκ, correct the relative frequency of agreement between coders to account for agreement which simply occurs by chance. However, in some situations these mea...
Following a series of high-pro le drug safety disasters in recent years, many countries are redoubling their e orts to ensure the safety of licensed medical products. Large-scale observa-tional databa...
We analyze general model selection procedures using penalized empirical loss minimization under computational constraints. While classical model selection approaches do not consider computational aspe...
Motivated by genome-wide association studies we consider astan-dard linear model with one additional random effect in situations where many predictors have been collected on the same subjects and each...
In this note, we consider the problem of existence of adaptive confidence bands in the fixed design regression model, adapting ideas in Hoffmann and Nickl [10] to the present case. In the course of th...
To better understand the interplay of censoring and sparsity we develop finite sample properties of nonparametric Cox proportional hazard乫s model. Due to high impact of sequencing data, carrying genet...
Optogenetics is a new tool to stimulate genetically targeted neuronal circuits us-ing light flashes that can be delivered at high frequencies. It has shown promise for studying neural circuits that ar...
We compute the expected value of the Kullback-Leibler divergence to various fundamental statistical models with respect to canonical priors on the probability simplex. This yields information about th...
We compute the expected value of the Kullback-Leibler divergence to various fundamental statistical models with respect to canonical priors on the probability simplex. This yields information about th...
We prove that the three-state toric homogenous Markov chain model has Markov degree two. In algebraic terminology this means, that a certain class of toric ideals are generated by quadratic binomials...
Many statistical data are imprecise due to factors such as mea-surement errors, computation errors, and lack of information. In such cases, data are better represented by intervals rather thanby singl...
Sparse linear (or generalized linear) models combine a standard likelihood func-tion with a sparse prior on the unknown coefficients. These priors can conve- niently be expressed as a maximization ov...
We propose a probabilistic formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for cer-tain functionals of ch...
In this paper, we consider the classic measurement error regression scenario in which our independent,or design, variables are observed with several sources of additive noise. We will show that our mo...

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