Results 51 to 60 of about 6,487,763 (293)
A Novel Correction for the Adjusted Box-Pierce Test
Frontiers in Applied Mathematics and Statistics, 2022 The classical Box-Pierce and Ljung-Box tests for auto-correlation of residuals possess severe deviations from nominal type I error rates. Previous studies have attempted to address this issue by either revising existing tests or designing new techniques.
Sidy Danioko +4 more
doaj +1 more source
Entropic criterion for model selection
, 2006 Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback-Leibler distance or relative entropy as a selection criterion.
Barker +20 more
core +2 more sources
Model selection for amplitude analysis [PDF]
, 2015 Model complexity in amplitude analyses is often a priori under-constrained since the underlying theory permits a large number of possible amplitudes to contribute to most physical processes.
Guegan, Baptiste +3 more
core +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objective To evaluate selumetinib exposure using therapeutic drug monitoring (TDM) in pediatric patients with neurofibromatosis type 1 (NF1) and plexiform neurofibromas (PN), assess interpatient pharmacokinetic variability, and explore the relationship between drug exposure, clinical response, and adverse effects.
Janka Kovács +8 more
wiley +1 more source
Handwritten Digit Recognition: Hyperparameters-Based Analysis
Applied Sciences, 2020 Neural networks have several useful applications in machine learning. However, benefiting from the neural-network architecture can be tricky in some instances due to the large number of parameters that can influence performance.
Saleh Albahli +3 more
doaj +1 more source
Knowledge-Guided Symbolic Regression for Interpretable Camera Calibration
Journal of ImagingCalibrating cameras accurately requires the identification of projection and distortion models that effectively account for lens-specific deviations. Conventional formulations, like the pinhole model or radial–tangential corrections, often struggle to ...
Rui Pimentel de Figueiredo
doaj +1 more source
Animal, 2018 Recent reports on livestock environmental impact based on life cycle assessment (LCA) did not fully consider the case of the dairy goat. Assignment of an environmental impact (e.g.
P.P. Danieli, B. Ronchi
doaj +1 more source
Predictive Bayesian selection of multistep Markov chains, applied to the detection of the hot hand and other statistical dependencies in free throws [PDF]
Royal Society Open Science, 2019 Consider the problem of modelling memory effects in discrete-state random walks using higher-order Markov chains. This paper explores cross-validation and information criteria as proxies for a model’s predictive accuracy. Our objective is to select, from
Joshua C. Chang
doaj +1 more source
Entropic Priors and Bayesian Model Selection
, 2009 We demonstrate that the principle of maximum relative entropy (ME), used judiciously, can ease the specification of priors in model selection problems. The resulting effect is that models that make sharp predictions are disfavoured, weakening the usual ...
Brendon J. Brewer +3 more
core +1 more source
Finite mixture regression: A sparse variable selection by model selection for clustering [PDF]
, 2014 We consider a finite mixture of Gaussian regression model for high- dimensional data, where the number of covariates may be much larger than the sample size. We propose to estimate the unknown conditional mixture density by a maximum likelihood estimator,
Devijver, Emilie
core +4 more sources