Abstract

The expected cumulative number of localizations observed by frame f is given by7 ⟨n cumulative ⟩(f ) ≈ N emitters (1 − p miss )τ 1 − exp[−λ 1 (f − 1)] λ 1 − 1 − exp[−λ 2 (f − 1)] λ 2 (2)The authors apologize for this error and state that this does not change the scientific conclusions of the 8 article in any way. The original article has been updated. The local pre-cluster density corresponding to each pre-cluster is estimated by finding the k (chosen to be 2 in this study) nearest pre-clusters and then computing ρ c = (k + 1)/πr 2 k where r k is the distance to the k-th nearest pre-cluster. The underlying local emitter density present at the beginning of the experiment is then estimated for each pre-cluster aŝρ 0,local = ρ c 1 k offτ 1 1 −p miss 1 − exp[−λ 1 (f end − 1)] λ 1 − 1 − exp[−λ 2 (f end − 1)] λ 2 −1 1Sample et al.where f end is the last frame containing localizations in the experiment.The authors apologize for this error and state that this does not change the scientific conclusions of the 16 article in any way. The original article has been updated.17 This is a provisional file, not the final typeset article 2

Highlights

  • A Corrigendum on Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem by Schodt D

  • A correction has been made to MATERIALS AND METHODS, Estimating Local Emitter Densities and Kinetic Rates, Paragraph Number 2: The expected cumulative number of localizations observed by frame f is given by

  • A correction has been made to MATERIALS AND METHODS, Estimating Local Emitter Densities and Kinetic Rates, Paragraph Number 4: The local pre-cluster density corresponding to each pre-cluster is estimated by finding the k nearest pre-clusters and computing ρc (k + 1)/πr2k where rk is the distance to the kth nearest pre-cluster

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Summary

Introduction

A Corrigendum on Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem by Schodt D. Corrigendum: Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem Edited and reviewed by: Thomas Pengo, University of Minnesota Twin Cities, United States

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