Results 111 to 120 of about 70,549 (302)
An Algorithm for Clustered Data Generalized Additive Modelling with S-PLUS [PDF]
We present a set of functions in S-PLUS to implement the clustered data generalized additive marginal modelling (CDGAM) strategy proposed by Berhane and Tibshirani (1998).
Vincent Carey, Lin Yee Hin
core +1 more source
Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment
ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute large‐vessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang +22 more
wiley +1 more source
Introducing COZIGAM: An R Package for Unconstrained and Constrained Zero-Inflated Generalized Additive Model Analysis [PDF]
Zero-inflation problem is very common in ecological studies as well as other areas. Nonparametric regression with zero-inflated data may be studied via the zero-inflated generalized additive model (ZIGAM), which assumes that the zero-inflated responses ...
Kung-Sik Chan, Hai Liu
core +1 more source
Generalized additive models: background, definitions, extensions [PDF]
This thesis gives an extensive overview of generalized additive models withan outlook on their robustication. Chapter 1 shortly introduces the mainproblems with the linear model - with Gaussian errors.
Rieser, Christopher; orcid:
core +1 more source
Five‐Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease
ABSTRACT Objective To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework.
Paulina Gonzalez‐Latapi +19 more
wiley +1 more source
As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because ...
Christophe Coupé
doaj +1 more source
Generalized additive models are generalized linear models in which the linear predictor includes a sum of smooth functions of covariates, where the shape of the functions is to be estimated. They have also been generalized beyond the original generalized linear model setting to distributions outside the exponential family and to situations in which ...
openaire +1 more source
Additive models for quantile regression: model selection and confidence bandaids [PDF]
Additive models for conditional quantile functions provide an attractive framework for nonparametric regression applications focused on features of the response beyond its central tendency.
Roger Koenker
core
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
Bayesian Regularisation in Structured Additive Regression Models for Survival Data [PDF]
During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models.
Konrath, Susanne +2 more
core +1 more source

