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Multiscale scanning in inverse problems
Supplement to “Multiscale scanning in inverse problems”. This supplementary material
contains an explanation of the full width at half maximum (FWHM), a detailed mathematical …
contains an explanation of the full width at half maximum (FWHM), a detailed mathematical …
Multiscale methods for shape constraints in deconvolution: confidence statements for qualitative features
Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative
features Page 1 The Annals of Statistics 2013, Vol. 41, No. 3, 1299–1328 DOI …
features Page 1 The Annals of Statistics 2013, Vol. 41, No. 3, 1299–1328 DOI …
Non asymptotic minimax rates of testing in signal detection with heterogeneous variances
The aim of this paper is to establish non-asymptotic minimax rates for goodness-of-fit
hypotheses testing in an heteroscedastic setting. More precisely, we deal with sequences (Y …
hypotheses testing in an heteroscedastic setting. More precisely, we deal with sequences (Y …
Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression
L Comminges, AS Dalalyan - 2013 - projecteuclid.org
We consider the problem of testing a particular type of composite null hypothesis under a
nonparametric multivariate regression model. For a given quadratic functional Q, the null …
nonparametric multivariate regression model. For a given quadratic functional Q, the null …
Optimal regularized hypothesis testing in statistical inverse problems
Testing of hypotheses is a well studied topic in mathematical statistics. Recently, this issue
has also been addressed in the context of inverse problems, where the quantity of interest is …
has also been addressed in the context of inverse problems, where the quantity of interest is …
Goodness-of-fit test for noisy directional data
C Lacour, TM Pham Ngoc - 2014 - projecteuclid.org
We consider spherical data X_i noised by a random rotation i∈SO(3) so that only the
sample Z_i=iX_i, i=1,\dots,N is observed. We define a nonparametric test procedure to …
sample Z_i=iX_i, i=1,\dots,N is observed. We define a nonparametric test procedure to …
Model selection and estimationof a component in additive regression
X Gendre - ESAIM: Probability and Statistics, 2014 - cambridge.org
Let Y∈ ℝn be a random vector with mean s and covariance matrix σ2PntPn where Pn is
some known n× n-matrix. We construct a statistical procedure to estimate s as well as under …
some known n× n-matrix. We construct a statistical procedure to estimate s as well as under …
General regularization schemes for signal detection in inverse problems
C Marteau, P Mathé - Mathematical methods of statistics, 2014 - Springer
The authors discuss how general regularization schemes, in particular, linear regularization
schemes and projection schemes, can be used to design tests for signal detection in …
schemes and projection schemes, can be used to design tests for signal detection in …
Adaptive minimax testing for circular convolution
S Schluttenhofer, J Johannes - Mathematical Methods of Statistics, 2020 - Springer
Given observations from a circular random variable contaminated by an additive
measurement error, we consider the problem of minimax optimal goodness-of-fit testing in a …
measurement error, we consider the problem of minimax optimal goodness-of-fit testing in a …
Minimax fast rates for discriminant analysis with errors in variables
S Loustau, C Marteau - 2015 - projecteuclid.org
The effect of measurement errors in discriminant analysis is investigated. Given
observations Z=X+ε, where ε denotes a random noise, the goal is to predict the density of X …
observations Z=X+ε, where ε denotes a random noise, the goal is to predict the density of X …