Results 1 to 10 of about 6,450 (280)

LASSO type penalized spline regression for binary data [PDF]

BMC Medical Research Methodology, 2021
Background Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects.
Muhammad Abu Shadeque Mullah, James A. Hanley, Andrea Benedetti   +2 more
doaj   +5 more sources

SEMIPARAMETRIC PENALIZED SPLINE REGRESSION [PDF]

Bulletin of informatics and cybernetics, 2012
In this paper, we propose a new semiparametric regression estimator by using a hybrid technique of a parametric approach and a nonparametric penalized spline method. The overall shape of the true regression function is captured by the parametric part, while its residual is consistently estimated by the nonparametric part.
Yoshida, Takuma, Naito, Kanta
openaire   +3 more sources

Robust Causal Estimation from Observational Studies Using Penalized Spline of Propensity Score for Treatment Comparison

Stats, 2021
Without randomization of treatments, valid inference of treatment effects from observational studies requires controlling for all confounders because the treated subjects generally differ systematically from the control subjects.
Tingting Zhou, Michael R Elliott, Roderick J Little   +2 more
exaly   +3 more sources

Handling Overlapping Asymmetric Data Sets—A Twice Penalized P-Spline Approach

Mathematics
Aims: Overlapping asymmetric data sets are where a large cohort of observations have a small amount of information recorded, and within this group there exists a smaller cohort which have extensive further information available.
Matthew Mcteer, Robin Henderson, Quentin M Anstee   +2 more
exaly   +3 more sources

Extensions of the Penalized Spline of Propensity Prediction Method of Imputation [PDF]

Biometrics, 2009
Summary Little and An (2004, Statistica Sinica 14, 949–968) proposed a penalized spline of propensity prediction (PSPP) method of imputation of missing values that yields robust model‐based inference under the missing at random assumption. The propensity score for a missing variable is estimated and a regression model is fitted that includes the ...
Roderick J Little
exaly   +5 more sources

Robust Permutation Tests for Penalized Splines

Stats, 2022
Penalized splines are frequently used in applied research for understanding functional relationships between variables. In most applications, statistical inference for penalized splines is conducted using the random effects or Bayesian interpretation of ...
Nathaniel E. Helwig
doaj   +2 more sources

Penalized hyperbolic-polynomial splines [PDF]

Applied Mathematics Letters, 2021
Splines and spline approximations using penality functions are especially useful tools in univariate approximation theory when univariate data are to be approximated, and when no interpolation property is needed. The methods using piecewise polynomial splines and penalty methods can be formulated via square (or otherwise, other \(L^p\)-norms are ...
Rosanna Campagna, Costanza Conti
openaire   +3 more sources

D-splines: Estimating rate schedules using high-dimensional splines with empirical demographic penalties

Demographic Research, 2021
Background: High-dimensional parametric models with penalized likelihood functions strike a good balance between bias and variance for estimating continuous age schedules from large samples. The penalized spline (P-spline) approach is particularly useful
Carl Schmertmann
doaj   +1 more source

PENALIZED SPLINE: A GENERAL ROBUST TRAJECTORY MODEL FOR ZIYUAN-3 SATELLITE [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Owing to the dynamic imaging system, the trajectory model plays a very important role in the geometric processing of high resolution satellite imagery. However, establishing a trajectory model is difficult when only discrete and noisy data are available.
H. Pan, Z. Zou
doaj   +1 more source

Dynamic Penalized Splines for Streaming Data

Statistica Sinica, 2022
Summary: We propose a dynamic version of the penalized spline regression designed for streaming data that allows for the insertion of new knots dynamically based on sequential updates of the summary statistics. A new theory using direct functional methods rather than the traditional matrix analysis is developed to attain the optimal convergence rate in
Xue, Dingchuan, Yao, Fang
openaire   +1 more source