Results 21 to 30 of about 343,435 (310)

Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery

open access: yesSensors, 2006
The performance of weak gaseous plume-detection methods in hyperspectral long-wave infrared imagery depends on scene-specific conditions such at the ability to properly estimate atmospheric transmission, the accuracy of estimated chemical signatures, and
Nicolas Hengartner, Tom Burr
doaj   +1 more source

Model‐Averaged Confidence Intervals [PDF]

open access: yesScandinavian Journal of Statistics, 2015
AbstractWe develop an approach to evaluating frequentist model averaging procedures by considering them in a simple situation in which there are two‐nested linear regression models over which we average. We introduce a general class of model averaged confidence intervals, obtain exact expressions for the coverage and the scaled expected length of the ...
Kabaila, Paul   +2 more
openaire   +3 more sources

Model averaging for generalized linear models in fragmentary data prediction

open access: yesStatistical Theory and Related Fields, 2022
Fragmentary data is becoming more and more popular in many areas which brings big challenges to researchers and data analysts. Most existing methods dealing with fragmentary data consider a continuous response while in many applications the response ...
Chaoxia Yuan, Yang Wu, Fang Fang
doaj   +1 more source

A New Model Averaging Approach in Predicting Credit Risk Default

open access: yesRisks, 2021
The paper introduces a novel approach to ensemble modeling as a weighted model average technique. The proposed idea is prudent, simple to understand, and easy to implement compared to the Bayesian and frequentist approach.
Paritosh Navinchandra Jha   +1 more
doaj   +1 more source

RETRACTED: Deep Fractional Max Pooling Neural Network for COVID-19 Recognition

open access: yesFrontiers in Public Health, 2021
Aim: Coronavirus disease 2019 (COVID-19) is a form of disease triggered by a new strain of coronavirus. This paper proposes a novel model termed “deep fractional max pooling neural network (DFMPNN)” to diagnose COVID-19 more efficiently.Methods: This 12 ...
Shui-Hua Wang   +4 more
doaj   +1 more source

Capture‐recapture using multiple data sources: estimating the prevalence of diabetes

open access: yesAustralian and New Zealand Journal of Public Health, 2012
Objective: To examine the potential for using multiple list sources and capture‐recapture methods for estimating the prevalence of diagnosed diabetes. Method: A model‐averaging procedure using an adjusted Akaike's Information Criterion (QAICc) was used ...
Claire M. Cameron   +3 more
doaj   +1 more source

Determinants of Shoot Biomass Production in Mulberry: Combined Selection with Leaf Morphological and Physiological Traits

open access: yesPlants, 2019
Physiological and morphological traits have a considerable impact on the biomass production of fast-growing trees. To compare cultivar difference in shoot biomass and investigate its relationships with leaf functional traits in mulberry, agronomic traits
Xu Cao   +5 more
doaj   +1 more source

Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities [PDF]

open access: yes, 2008
We deal with the arbitrariness in the choice of the prior over the models in Bayesian model averaging(BMA), by modelling prior knowledge by a set of priors (i.e., a prior credal set). We consider Dash and Cooper's BMA applied to naive Bayesian networks, replacing the single prior over the naive models by a credal set; this models a condition close to ...
Giorgio Corani, Marco Zaffalon
openaire   +1 more source

Digital Mapping of Soil Classes Using Ensemble of Models in Isfahan Region, Iran

open access: yesSoil Systems, 2019
Digital soil maps can be used to depict the ability of soil to fulfill certain functions. Digital maps offer reliable information that can be used in spatial planning programs.
Ruhollah Taghizadeh-Mehrjardi   +5 more
doaj   +1 more source

Recovering Crossed Random Effects in Mixed-Effects Models Using Model Averaging

open access: yesMethodology, 2022
Random effects contain crucial information to understand the variability of the processes under study in mixed-effects models with crossed random effects (MEMs-CR).
José Ángel Martínez-Huertas   +1 more
doaj   +1 more source

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