Thomas Staudt

collaborators

3 papers

stat.AP2019

Statistical Molecule Counting in Super-Resolution Fluorescence Microscopy: Towards Quantitative Nanoscopy

Thomas Staudt, Timo Aspelmeier, Oskar Laitenberger +3

Super-resolution microscopy is rapidly gaining importance as an analytical tool in the life sciences. A compelling feature is the ability to label biological units of interest with…

math.ST2018

Posterior Consistency in the Binomial $(n, p)$ Model with Unknown $n$ and $p$ : A Numerical Study

Laura Fee Schneider, Thomas Staudt, Axel Munk

Estimating the parameters from $k$ independent Bin $(n, p)$ random variables, when both parameters $n$ and $p$ are unknown, is relevant to a variety of applications. It is particular…

math.ST2018

Posterior analysis of $n$ in the binomial $(n, p)$ problem with both parameters unknown -- with applications to quantitative nanoscopy

Johannes Schmidt-Hieber, Laura Fee Schneider, Thomas Staudt +3

Estimation of the population size $n$ from $k$ i.i.d.\ binomial observations with unknown success probability $p$ is relevant to a multitude of applications and has a long history.…

Statistical Molecule Counting in Super-Resolution Fluorescence Microscopy: Towards Quantitative Nanoscopy

Posterior Consistency in the Binomial (n,p) Model with Unknown n and p: A Numerical Study

Posterior analysis of n in the binomial (n,p) problem with both parameters unknown -- with applications to quantitative nanoscopy

Posterior Consistency in the Binomial $(n, p)$ Model with Unknown $n$ and $p$ : A Numerical Study

Posterior analysis of $n$ in the binomial $(n, p)$ problem with both parameters unknown -- with applications to quantitative nanoscopy