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Showing 1 to 6 of 6 for “"P-splines"”.
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Flexible Modellierung kategorialer Responsevariablen
… As a result of theoretical considerations, P-Splines seem to be the ideal alternative for applying penalized basis function approaches. Based on this result, nonparametric extensions of the multinomial logit model for nominal and the cumulative logit model for ordinal responses are derived. An …
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Gradient-Based Surface Reconstruction and the Application to Wind Waves
… For the spline based methods, either common P-splines or P1-splines can be used. Extensive reconstruction error analysis shows that the new P1-spline based method is superior to conventional methods in the case of gradient fields corrupted with outliers. In the analysis, both spline based …
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Gradient-Based Surface Reconstruction and the Application to Wind Waves
… For the spline based methods, either common P-splines or P1-splines can be used. Extensive reconstruction error analysis shows that the new P1-spline based method is superior to conventional methods in the case of gradient fields corrupted with outliers. In the analysis, both spline based …
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Analysis Using Smoothing Via Penalized Splines as Implemented in LME() in R
… models. Following a review of literature on splines and mixed models, details for implementing mixed model splines are presented. The examples use an experiment in the health sciences to demonstrate how to use mixed models to generate the smoothers. The first example takes a simple one-group …
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Profile Monitoring with Fixed and Random Effects using Nonparametric and Semiparametric Methods
Profile monitoring is a relatively new approach in quality control best used where the process data follow a profile (or curve) at each time period. The essential idea for profile monitoring is to model the profile via some parametric, nonparametric, and semiparametric methods and then monitor the …
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Flexible models and methods for longitudinal and multilevel functional data
… a residual measurement error process. Using P-splines, we propose nonparametric estimation of the population mean function, the varying coefficient, the random subject-specific curves, the associated covariance function that represents between-subject variation, and the variance function of the …