Results 11 to 20 of about 52,118 (271)
Accurate Estimates Without Calibration? [PDF]
, 2008 Most process models calibrate their internal settings using local data. Collecting this data is expensive, tedious, and often an incomplete process. Is it possible to make accurate process decisions without historical data? Variability in model output arises from (a) uncertainty in model inputs and (b) uncertainty in the internal parameters that ...
Menzies, Tim +7 more
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Classification of Event-Related Potentials with Regularized Spatiotemporal LCMV Beamforming
Applied Sciences, 2022 The usability of EEG-based visual brain–computer interfaces (BCIs) based on event-related potentials (ERPs) benefits from reducing the calibration time before BCI operation. Linear decoding models, such as the spatiotemporal beamformer model, yield state-
Arne Van Den Kerchove +3 more
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Synthesizing the classical and inverse methods in linear calibration [PDF]
, 2001 This paper considers the problem of linear calibration and presents two estimators arising from a synthesis of classical and inverse calibration approaches. Their performance properties are analyzed employing the small error asymptotic theory.
Shalabh, Toutenburg, Helge
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Discrete Dynamics in Nature and Society, 2021 In this paper, we focus on heteroscedastic partially linear varying-coefficient errors-in-variables models under right-censored data with censoring indicators missing at random.
Yuye Zou, Chengxin Wu
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Nonparametric Calibration for Age Estimation
Journal of the Royal Statistical Society Series C: Applied Statistics, 2002 SUMMARY A method is proposed for the calibration of a continuous random variable when the dependent variables are a combination of continuous and categorical, and the model between the controlling variables and calibrated variable is empirically derived.
Lucy, David, Ackroyd, R. G., Pollard, M.
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Calibrating parametric subject-specific risk estimation [PDF]
Biometrika, 2010 For modern evidence-based medicine, decisions on disease prevention or management strategies are often guided by a risk index system. For each individual, the system uses his/her baseline information to estimate the risk of experiencing a future disease-related clinical event.
T. Cai +4 more
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Calibration Estimation in Survey Sampling
International Statistical Review, 2010 Summary Calibration estimation, where the sampling weights are adjusted to make certain estimators match known population totals, is commonly used in survey sampling. The generalized regression estimator is an example of a calibration estimator. Given the functional form of the calibration adjustment term, we establish the asymptotic equivalence ...
Kim, Jae Kwang, Park, Mingue
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Calibrating random forests for probability estimation [PDF]
Statistics in Medicine, 2016 Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating random forests for probability estimation.
Theresa Dankowski, Andreas Ziegler
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Calibrated Measures for Breast Density Estimation [PDF]
Academic Radiology, 2011 Breast density is a significant breast cancer risk factor measured from mammograms. Evidence suggests that the spatial variation in mammograms may also be associated with risk. We investigated the variation in calibrated mammograms as a breast cancer risk factor and explored its relationship with other measures of breast density using full field ...
John J, Heine, Ke, Cao, Dana E, Rollison
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A Comparison of Model-Assisted Estimators to Infer Land Cover/Use Class Area Using Satellite Imagery
Remote Sensing, 2014 Remote sensing provides timely, economic, and objective data over a large area and has become the main data source for land cover/use area estimation. However, the classification results cannot be directly used to calculate the area of a given land cover/
Yizhan Li +5 more
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