Results 261 to 270 of about 1,351,383 (295)

Capturing infant and child growth dynamics with P-splines mixed effects models

Hernandez MA, Li Z, Cole TJ, Ong YY, Tilling K, Elhakeem A.   +5 more
europepmc   +1 more source

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Real-time smoothing of G01 commands for five-axis machining by constructing an entire spline with the bounded smoothing error

Mechanism and Machine Theory, 2021
G01 commands generated by computer-aided manufacturing (CAM) software need to be smoothed to eliminate the tangential discontinuities at corners. Although the smoothing methods for five-axis tool paths have been widely studied, it is still challenging to
Qun-Bao Xiao, Min Wan, Xue-Bin Qin
exaly   +2 more sources

Bayesian “Confidence Intervals” for the Cross-Validated Smoothing Spline

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1983
Grace Wahba
exaly   +2 more sources

Asymmetrical pythagorean-hodograph (PH) spline-based C3 continuous corner smoothing algorithm for five-axis tool paths with short segments

, 2021
Local corner smoothing is widely used for the G01 motion commands to achieve the motion continuity of transition corners. Most splines constructed by the existing local corner smoothing methods oriented for five-axis machining mainly must be connected by
M. Wan, Xue-Bin Qin, Qun-Bao Xiao, Yang Liu, Weihong Zhang   +4 more
semanticscholar   +1 more source

The regression curve estimation by using mixed smoothing spline and kernel (MsS-K) model

, 2020
In this article, we propose a new method in estimating non parametric regression curve. This method combines the smoothing Spline and Kernel functions. Estimation of the estimator is completed by minimizing penalized least square.
R. Hidayat, I. Budiantara, B. Otok, V. Ratnasari   +3 more
semanticscholar   +1 more source

Divide and Recombine Approaches for Fitting Smoothing Spline Models with Large Datasets

Journal of Computational And Graphical Statistics, 2018
Spline smoothing is a widely used nonparametric method that allows data to speak for themselves. Due to its complexity and flexibility, fitting smoothing spline models is usually computationally intensive which may become prohibitive with large datasets.
Danqing Xu, Yuedong Wang
semanticscholar   +1 more source

Smoothing noisy data with spline functions

, 1978
Peter Craven, G. Wahba
semanticscholar   +1 more source

An ultrasound study of Canadian French rhotic vowels with polar smoothing spline comparisons.

Journal of the Acoustical Society of America, 2015
Jeff Mielke
semanticscholar   +1 more source

Smoothing Spline Anova Models

, 2002
Chong Gu
semanticscholar   +1 more source

Smoothing Spline Models with Correlated Random Errors

Journal of the American Statistical Association, 1998
Yuedong Wang
exaly   +2 more sources