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# Statistical Modeling - Science topic

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Publications related to Statistical Modeling (10,000)
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In recent years, the contamination of the earth's materials with radioactive elements as naturally occurring radioactive material has been a source of concern. This study is aimed at the environmental radioactivity of beach sediments and the gamma dose levels along the south-eastern coastal region of the Indian subcontinent, from the Palar River mo...
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We introduce a novel methodology for robust Bayesian estimation with robust divergence (e.g., density power divergence or γ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document...
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Quantifying invasive species abundance informs management and control strategies. However, estimating abundance can be challenging, particularly when dealing with rare species early in the invasion process. Data generated from control strategies, such as removing invasive species, are usually not suited to conventional statistical modelling a...
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Traditionally most cross-selling models in retail banking use demographics information and interactions with marketing as input to statistical models or machine learning algorithms to predict whether a customer is willing to purchase a given financial product or not. We overcome with such limitation by building several models that also use several...
Article
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One of the main indicators for detecting changes in climate and marine ecosystems around the world is the sea surface temperature (SST). Even with several models presented in the literature, it is still a challenging task when only a single model is considered for SST forecasting. In this context, hybrid approaches that combine statistical models (...
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In quasi-induced exposure (QIE) theory, the presence of hazardous driving action is the typical determinant of the driver's responsibility for a crash. However, there is a lack of effort available to analyze the impacts of hazardous actions on the QIE estimate, which may result in estimation bias. Thus, the study aims to explore the difference in Q...
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We present a model to estimate the technical requirements, including the photovoltaic area and battery capacity, along with the costs, for a four-person household to be 100% electrically self-sufficient in Germany. We model the hourly electricity consumption of private households with quasi-Fourier series and an autoregressive statistical model bas...
Preprint
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Compound flooding is a type of flood events caused by multiple flood drivers. The associated risk has usually been assessed using data-based statistical analyses or physics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework...
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Background: Using XGBoost (XGB), this study demonstrates how flexible machine learning modelling can complement traditional statistical modelling (multinomial logistic regression) as a sensitivity analysis and predictive modelling tool in occupational health research. Design: The study predicts welfare dependency for a cohort at 1, 3, and 5 year...
Article
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Meteorological extremes on the seasonal time scale have received increased attention due to their relevance for society and economy. A recently developed approach to identify seasonal extremes is applied here to ERA5 reanalyses from 1950-2020 to identify hot and cold, wet and dry, and stormy and calm extreme seasons globally. The approach consists...
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The relevance of the study lies in the fact that with the depletion of conventional oil and gas reserves and an increase in the global demand for hydrocarbons, the focus of the industrial sector is gradually shifting towards the resources of the Arctic, which have tremendous potential for development. However, the current industrial policy has to t...
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Introduction Due to its increasing prevalence, dementia is currently one of the most extensively studied health issues. Although it represents a comparatively less-addressed issue, the caregiving burden for dementia patients is likewise receiving attention. Methods To identify determinants of depression in dementia caregivers, using Community Heal...
Conference Paper
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In this study, we propose a generating of an odd distribution which is generated by combining the extreme value distribution to Lomax distribution. The obtained distribution is denoted by the ODEL-distribution. An extension over the location parameter λ of the ODEL-distribution is proposed (denoted by EODEL-distribution) via a linear combination of...
Preprint
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The rapid ascent in carbon dioxide emissions is a major cause of global warming and climate change, which pose a huge threat to human survival and impose far-reaching influence on the global ecosystem. Therefore, it is very necessary to effectively control carbon dioxide emissions by accurately predicting and analyzing the change trend timely, so a...
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The increase in the number of infections and the worrisome state of mortality linked to the COVID-19 pandemic demand an optimal statistical model and efficient monitoring scheme to analyze the deaths. This paper aims to model the COVID-19 mortality in Nigeria using four non-normal distributions grouped under the generalized gamma distribution, by s...
Preprint
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Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry-picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of the...
Article
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Reservoir regulation affects various streamflow characteristics, from low to high flows, with important implications for downstream water users. However, information on past reservoir operations is rarely publicly available, and it is hardly known how reservoir operation signals, i.e. information on when water is stored in and released from reservo...
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A GIS-based study has been carried out to map areas landslide susceptibility using both frequency ratio (FR) and Shannon entropy (SE) bivariate statistical models. A total of 270 landslides were identified and classified randomly into training landslides datasets (70%) and the remaining (30%) of landslides datasets were used for validation purpose....
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Purpose: To correlate microvascular changes and assess the relationship between microvascular changes and cardiovascular disease (CVD) risk in patients with retinal vein occlusion (RVO). Methods: Patients over 40 years of age with unilateral RVO were included in this prospective study. Those known to have cardiovascular disease were excluded. A...
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Image segmentation is an important task in image processing and analysis but due to the same ground object having different spectra and different ground objects having similar spectra, segmentation, particularly on high-resolution remote sensing images, can be significantly challenging. Since the spectral distribution of high-resolution remote sens...
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Psoriatic arthritis (PsA) is a common comorbidity of psoriasis, featured by its irreversible joint symptoms. Despite the significant impact on the healthcare system, it is still challenging to leverage machine learning or statistical models to predict PsA and its progression, or analyze drug efficacy. With 3961 patients’ clinical records, we develo...
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We examined whether and how L1-L2 crosslinguistic formal lexical similarity influences L2 word choice. Our sample included two learner subcorpora, containing 8,500 and 6,390 English texts, written in an educational setting, by speakers of diverse L1s in the A1-B2 CEFR range of L2 proficiency. We quantified similarity based on phonological overlap b...
Preprint
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In humans, the nocturnal secretion of melatonin by the pineal gland is suppressed by ocular exposure to light. In the laboratory, melatonin suppression is a convenient biomarker for this neural pathway. Recent work has found that individuals differ substantially in their melatonin-suppressive response to light, with the most sensitive individuals b...
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Urban air pollution is a global concern impairing citizens' health, thus monitoring is a pressing need for city managers. City-wide networks for air pollution monitoring based on low-cost sensors are promising to provide real-time data with detail and scale never before possible. However, they still present limitations preventing their ubiquitous u...
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The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentr...
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This paper investigates the presence of long memory both in mean and volatility of Naira per Dollar exchange rate series, using models of autoregressive fractionally integrated moving average (ARFIMA), generalized autoregressive conditional heteroscedastic (GARCH) and fractionally integrated generalized autoregressive conditional heteroscedastic (F...
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The choice between Basiliximab (BSX) or Anti-Thymocyte Globulin (ATG) as induction therapy in non-immunized kidney transplant recipients remains uncertain. Whilst ATG may allow steroid withdrawal and a decrease in tacrolimus, it also increases infectious complications. We investigated outcomes in non-immunized patients receiving a very low dosage o...
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Land surface albedo (LSA) is an essential component of the surface radiation budget, and has been retrieved extensively as a basic remote sensing product; however, daily LSA products suffer from extensive data gaps primarily caused by cloud cover. Accordingly, several gap-filling methods were developed (e.g., spatiotemporal interpolation and data f...
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We present a new approach to modeling the future development of extreme temperatures globally and on the time-scale of several centuries by using non-stationary generalized extreme value distributions in combination with logistic functions. The statistical models we propose are applied to annual maxima of daily temperature data from fully coupled c...
Article
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July is the rainy peak month of central China, with a large interannual variation of local precipitation often causing serious droughts and floods. The seasonal prediction of the central China July precipitation (CCJP) is an important but still challenging task. Here, we suggest several robust seasonal predictors for the CCJP, including the precedi...
Preprint
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We propose a novel Bayesian inference framework for distributed differentially private linear regression. We consider a distributed setting where multiple parties hold parts of the data and share certain summary statistics of their portions in privacy-preserving noise. We develop a novel generative statistical model for privately shared statistics,...
Preprint
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We study the bi-dimensional $q$-Potts model with long-range bond correlated disorder. Similarly to [C. Chatelain, Phys. Rev. E 89, 032105], we implement a disorder bimodal distribution by coupling the Potts model to auxiliary spin-variables, which are correlated with a power-law decaying function. The universal behaviour of different observables, e...
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Spectral correlations between metabolites in 31P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between 31P-containing metabolites arising from spectral ove...
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Many studies on the relationship between alcohol and health outcome focus primarily on average consumption over time and do not consider how heavy per-occasion drinking may influence apparent relationships. Improved methods concerning the most recent drinking occasion are essential to inform the extent of alcohol-related health problems. We aimed t...
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We develop and apply new statistical models for linked survey and administrative data on employment earnings, incorporating 4 types of measurement error. In addition, we allow error distributions to differ with individual characteristics, which improves model fit and allows us to investigate substantive hypotheses about factors associated with erro...
Article
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Though the picture remains incoherent to draw a concrete conclusion, especially with weakly bound particles, prolific efforts have been devoted to unfolding the reaction mechanisms at energies below 10 MeV/u. The dearth of extensive data and ambiguous findings in the light to medium mass region galvanizes the exploration of the entire mass domain....
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Air temperature records are acquired by networks of weather stations which may be several kilometres apart. In complex topographies the representativeness of a meteorological station may be diminished in relation to a flatter valley, and the nearest station may have no relation to a place located near it. The present study shows a simple method to...
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Mathematical modelling of heating and current drive as well as yields and distributions of fusion products in a magnetically confined plasma subject to neutral beam injection requires, in turn, modelling of distributions of fast ions, which is a complex task including calculations of the source of suprathermal particles, i.e., the number of fast io...
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In terms of the aim of the paper, that consisted of the investigation the impact of information technology as a factor of globalization on the amount of revenue from the services’ sales for enterprises in the field of management consulting on the example of their potential participation in tender procedures (open tenders) for the purchase of servic...
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The groundwater contained in aquifers is among the most important water supply resources, especially in semi-arid and arid regions worldwide. This study aims to evaluate and compare the prediction capability of two well–known models, support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS), combined with a genetic algorithm (G...
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The statistical combination of disjoint signal regions in reinterpretation studies uses more of the data of an analysis and gives more robust results than the single signal region approach. We present the implementation and usage of signal region combination in MadAnalysis 5 through two methods: an interface to the Pyhf package making use of statis...
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We study the forecast of the electrical energy demand of the N'Djamena city, Chad, by 2032 using the statistical model based on the linear regression technic. A series of data of the maximum power demand (PMA) for the past years from 2005 to 2017 are obtained from the dispatching center of the company national electricity board of N'Djamena, which...
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Measurements of the dynamical correlations between neutral and charged kaons in central Pb-Pb collisions at sNN=2.76 TeV by the ALICE Collaboration display anomalous behavior relative to conventional heavy-ion collision simulators such as AMPT, EPOS, and HIJING. We consider other conventional statistical models, none of which can reproduce the magn...
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This paper aims to propose a statistical model to assess pubertal growth spurt using the ratio of the anterior height projection to the posterior (Vba) of the fourth cervical vertebra body (C4) on cephalograms and to calculate the residual proportion of skeletal maturation and the time for the pubertal growth spurt to end for a given Vba. A sample...
Article
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Current oxygen saturation targets in delivery room given by Neonatal Resuscitation Program (NRP) are essentially derived from term neonates. This prospective observational study was conducted in a level-III neonatal unit in preterm neonates (< 37 weeks) who did not receive resuscitation or supplemental oxygen to create centile charts for pre-ductal...
Article
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The Revised Paranormal Belief Scale (RPBS) is the prevailing measure of supernatural credence. However, there exists only limited evidence to support the temporal stability and predictive validity of the instrument over time. Acknowledging this, the present study assessed the test–retest reliability of the RPBS using a large, heterogeneous sample a...
Preprint
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The energy transition is expected to significantly increase the share of renewable energy sources whose production is intermittent in the electricity mix. Apart from key benefits, this development has the major drawback of generating a mismatch between power supply and demand. The innovative dynamic pricing approach may significantly contribute to...
Conference Paper
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A necessidade de realizar exames em imagens térmicas vem se popularizando, assim como o uso de técnicas e ferramentas matemáticas e estatísticas, que em conjunto, possibilitam o auxílio do diagnóstico de tumores malignos na região da tireoide. No entanto, algumas ferramentas estatísticas e matemáticas vem sendo utilizadas de forma indiscriminada, p...
Article
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Retrieving weather extremes from observations is critical for weather forecasting and climate impact studies. Statistical and machine learning methods are increasingly popular in the remote sensing community in particular due to recent advances in artificial intelligence methods. However, these models are regression tools and as such, they are not...
Preprint
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The ability to understand and predict coarse sediment transport in torrent catchments is a key element for the protection and prevention against the associated hazards. In this study, we collected data describing sediment supply at 99 torrential catchments in the Northern French Alps. The sample covers a wide range of geomorphic activity: from torr...
Preprint
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For the last two decades, experimental information on nuclear level densities for about 60 different nuclei has been obtained on the basis of the Oslo method. While each of these measurements has been typically compared to one or a few level density models, a global study including all the measurements has been missing. The present study provides a...
Article
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Epidemics and pandemics require an early estimate of the cumulative infection prevalence, sometimes referred to as the infection "Iceberg," whose tip are the known cases. Accurate early estimates support better disease monitoring, more accurate estimation of infection fatality rate, and an assessment of the risks from asymptomatic individuals. We f...
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Human activity recognition (HAR) has become an interesting topic in healthcare. This application is important in various domains, such as health monitoring, supporting elders, and disease diagnosis. Considering the increasing improvements in smart devices, large amounts of data are generated in our daily lives. In this work, we propose unsupervised...
Preprint
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We generalize quasi-arithmetic means beyond scalars by considering the gradient map of a Legendre type real-valued function. The gradient map of a Legendre type function is proven strictly comonotone with a global inverse. It thus yields a generalization of strictly mononotone and differentiable functions generating scalar quasi-arithmetic means. F...
Preprint
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As coral reefs endure increasing levels of disturbance, understanding patterns of recovery following disturbance(s) is paramount to assessing the sustainability of these ecosystems. Given the slow dynamics of coral reefs and the increasing frequency of environmental pressures, management strategies focus on understanding recovery patterns to drive...
Article
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Abstract The aim of this work is to explain the final negotiated prices for some of the most famous transfers of football players over the last twelve years (2007-2018). The article analyses different values for forwards taken from the sports website Transfermarkt, developing a statistical model based on personal, performance, risk, environmental a...
Preprint
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Partial differential equations (PDEs) have become an essential tool for modeling complex physical systems. Such equations are typically solved numerically via mesh-based methods, such as the finite element method, the outputs of which consist of the solutions on a set of mesh nodes over the spatial domain. However, these simulations are often prohi...
Preprint
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Same Bamboos species have mechanical properties compatible with construction material. Despite this, their low shear strength, the presence of nodes in their culms and their circular geometry inhibit the expansion of the use of this material as construction material. One technique that can solve this problem is Glued Laminated Bamboo (GLB). Based o...
Article
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Data based studies have always provided useful insights of the research problem , provided that correct statistical modeling and inference strategies are adopted. For bi-directional studies or longitudinal datasets, it is always difficult to analyze the dependence of variables and their impact on the key features. With the advancement in the fields...
Article
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In clinical trials, identification of prognostic and predictive biomarkers has became essential to precision medicine. Prognostic biomarkers can be useful for the prevention of the occurrence of the disease, and predictive biomarkers can be used to identify patients with potential benefit from the treatment. Previous researches were mainly focused...
Preprint
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Federated learning is a distributed and privacy-preserving approach to train a statistical model collaboratively from decentralized data of different parties. However, when datasets of participants are not independent and identically distributed (non-IID), models trained by naive federated algorithms may be biased towards certain participants, and...
Article
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In this article, we have proposed a generalized estimator for mean estimation by combining the ratio and regression methods of estimation in the presence of auxiliary information using systematic sampling. We incorporated some robust parameters of the auxiliary variable to obtain precise estimates of the proposed estimator. The mathematical express...
Preprint
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Rankings and ratings are commonly used to express preferences but provide distinct and complementary information. Rankings give ordinal and scale-free comparisons but lack granularity; ratings provide cardinal and granular assessments but may be highly subjective or inconsistent. Collecting and analyzing rankings and ratings jointly has not been pe...
Article
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The ‘multistate lifetable’ is a widely used model for the long-term health impacts of public health interventions. It requires estimates of the incidence, case fatality, and sometimes also remission rates, for multiple diseases by age and gender. The case fatality is the rate of death from a disease for people with a disease, and is commonly not ob...
Article
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Background: The complexity of the upper gastrointestinal (UGI) multidisciplinary team (MDT) is continually growing, leading to rising clinician workload, time pressures, and demands. This increases heterogeneity or 'noise' within decision-making for patients with oesophageal cancer (OC) and may lead to inconsistent treatment decisions. In recent d...
Article
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The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal meteorological conditions, diverse viral variants, and locally implemented non-pharmaceutical interv...
Preprint
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Linear dynamical systems are the foundational statistical model upon which control theory is built. Both the celebrated Kalman filter and the linear quadratic regulator require knowledge of the system dynamics to provide analytic guarantees. Naturally, learning the dynamics of a linear dynamical system from linear measurements has been intensively...
Article
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With the advent of fluorescence superresolution microscopy, nano-sized structures can be imaged with a previously unprecedented accuracy. Therefore, it is rapidly gaining importance as an analytical tool in the life sciences and beyond. However, the images obtained so far lack an absolute scale in terms of fluorophore numbers. Here, we use, for the...