Results 31 to 40 of about 34,984 (259)
Proceedings, 2018 Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
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Smoothing Parameter Selection for a Class of Semiparametric Linear Models
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2009 SummarySpline-based approaches to non-parametric and semiparametric regression, as well as to regression of scalar outcomes on functional predictors, entail choosing a parameter controlling the extent to which roughness of the fitted function is penalized.
Reiss, Philip T., Ogden, R. Todd
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Targeted smoothing parameter selection for estimating average causal effects [PDF]
Computational Statistics, 2014 The non-parametric estimation of average causal effects in observational studies often relies on controlling for confounding covariates through smoothing regression methods such as kernel, splines or local polynomial regression. Such regression methods are tuned via smoothing parameters which regulates the amount of degrees of freedom used in the fit ...
Jenny Häggström, Xavier de Luna
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Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
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HISAPS: High-order smoothing spline with automatic parameter selection and shape constraints
SoftwareXObtaining a good functional fit with noisy data is difficult. This is especially true when the derivative of the fitted function is needed, which is often the case in engineering applications. One solution is to use smoothing splines.
Peter H. Broberg +8 more
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Smoothing Parameter Selection in two Frameworks for Penalized Splines [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2013 SummaryThere are two popular smoothing parameter selection methods for spline smoothing. First, smoothing parameters can be estimated by minimizing criteria that approximate the average mean-squared error of the regression function estimator. Second, the maximum likelihood paradigm can be employed, under the assumption that the regression function is a
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Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
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Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data [PDF]
Revista Română de Statistică, 2017 In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya-Watson (Nadarya, 1964; Watson, 1964) type kernel estimator. In this estimation procedure, the censored observations are replaced by synthetic data points
Dursun AYDIN, Ersin YILMAZ
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Molecular Oncology, EarlyView.Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
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Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies. [PDF]
PLoS ONE, 2014 PURPOSE: Compressed sensing (CS) has been widely applied to prospective cardiac cine MRI. The aim of this work is to study the benefits obtained by including motion estimation in the CS framework for small-animal retrospective cardiac cine.
Juan F P J Abascal +4 more
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