Results 51 to 60 of about 204,377 (277)
Smoothing Parameter Selection in two Frameworks for Penalized Splines [PDF]
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
openaire +4 more sources
Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini +2 more
wiley +1 more source
The selection of data smoothing methods is one of the key steps in extracting land surface phenology parameters from time-series remote sensing data. However, existing studies often use default parameters for denoising the time-series data, neglecting ...
Mengna Liu, Baocheng Wei, Xu Jia
doaj +1 more source
Estimating the changes of epidemiological parameters, such as instantaneous reproduction number, Rt, is important for understanding the transmission dynamics of infectious diseases.
Xian Yang +6 more
doaj +1 more source
Semiparametric and Additive Model Selection Using an Improved Akaike Information Criterion [PDF]
An improved AIC-based criterion is derived for model selection in general smoothing-based modeling, including semiparametric models and additive models. Examples are provided of applications to goodness-of-fit, smoothing parameter and variable selection ...
Simonoff, Jeffrey S., Tsai, Chih-Ling
core
A fast method for implementing Generalized Cross-Validation in multi-dimensional nonparametric regression [PDF]
This article presents a modified Newton method for minimizing the Generalized Cross-Validation criterion, a commonly used smoothing parameter selection method in nonparametric regression.
Kauermann, Göran, Opsomer, J. D.
core +1 more source
Induction of diabetes in three different mouse strains uniformly resulted in an increase in TNAP activity and a reduction in pyrophosphate (PPi) in the circulation. Inhibition of TNAP restored plasma PPi. Diabetes‐induced calcification in the media layer of the aorta was detected only in the Abcc6−/− strain, which is predisposed to ectopic ...
Krisztina Fülöp +13 more
wiley +1 more source
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 more
wiley +1 more source
Semiparametric Stepwise Regression to Estimate Sales Promotion Effects [PDF]
Kalyanam and Shively (1998) and van Heerde et al. (2001) have proposed semiparametric models to estimate the influence of price promotions on brand sales, and both obtained superior performance for their models compared to strictly parametric modeling ...
Belitz, Christiane +2 more
core +2 more sources
Smoothing Parameter Selection and Alpha-Stable P-Adic Time Signals
The estimation of the spectral density of stable p-adic signals is already done. Such estimation is based on smoothing the periodogram by using a spectral window. The convergence rate of this estimator depends on bandwidth of spectral window (called the smoothing parameter).
Sabre, Rachid, Horrigue, Walid
openaire +2 more sources

