Results 71 to 80 of about 7,637,186 (260)
Analysis of the time to sustained progression in Multiple Sclerosis using generalised linear and additive models [PDF]
, 2003 The course of multiple sclerosis (MS) is generally difficult to predict. This is due to the great inter-individual variability with respect to symptoms and disability status.
Hellriegel, B. +5 more
core +1 more source
Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
wiley +1 more source
BayesX: Analyzing Bayesian Structural Additive Regression Models [PDF]
There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC)
Andreas Brezger +2 more
core
Molecular Oncology, EarlyView.Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
wiley +1 more source
Oracally Efficient Two-Step Estimation of Generalized Additive Model [PDF]
Generalized additive models (GAM) are multivariate nonparametric regressions for non-Gaussian responses including binary and count data. We propose a spline-backfitted kernel (SBK) estimator for the component functions.
Wolfgang Karl Härdle +2 more
core
Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications [PDF]
An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) – one of the
Klein, Nadja +4 more
core +1 more source
Molecular Oncology, EarlyView.Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
Boosting Correlation Based Penalization in Generalized Linear Models [PDF]
, 2007 In high dimensional regression problems penalization techniques are a useful tool for estimation and variable selection. We propose a novel penalization technique that aims at the grouping effect which encourages strongly correlated predictors to be in ...
Tutz, Gerhard, Ulbricht, Jan
core +1 more source
Using generalized estimating equations with regression splines to improve analysis of butterfly transect data [PDF]
, 2008 Surveying animal populations is an important aspect of wildlife management. Distinguishing trend from random fluctuations and quantifying trend are key goals in any analysis.
Brewer, Ciara
core +2 more sources
Statistical Qualification for Approval of Commercial Credits through Generalized Additive Models
Latin-American Journal of Computing, 2020 This article presents the application of a methodological procedure for the construction of a statistical qualification model for the approval of commercial credits in a public financial institution.
Verónica Garrido +2 more
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