Results 21 to 30 of about 595,073 (274)
Modeling of Cellular Networks Using Stationary and Nonstationary Point Processes
IEEE Access, 2018 The spatial topology of the base stations in wireless networks has a profound impact on their performance evaluation and analysis. It is important to identify a proper and accurate point process model before applying any theoretical stochastic geometry ...
Chunlin Chen +3 more
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Analysing mark-recapture-recovery data in the presence of missing covariate data via multiple imputation [PDF]
, 2014 We consider mark–recapture–recovery data with additional individual time-varying continuous covariate data. For such data it is common to specify the model parameters, and in particular the survival probabilities, as a function of these covariates to ...
Buckland, Stephen Terrence +2 more
core +2 more sources
Determination of environmental factors affecting the distribution of plant species in northern Zagros forests (Case study: Armardeh Forest, Baneh) [PDF]
مجله جنگل ایران, 2015 Northern Zagros forests are one of the most important ecosystems in Iran from ecological and socio-economic points of view. This study was done to determine the most important gradients affecting on plant species distribution by using ordination methods.
Somayeh Gaderzadeh +3 more
doaj
A Review on ROC Curves in the Presence of Covariates
Revstat Statistical Journal, 2014 In this paper we review the literature on ROC curves in the presence of covariates. We discuss the different approaches that have been proposed in the literature to define, model, estimate and do asymptotics for ROC curves that incorporate covariates ...
Juan Carlos Pardo-Fernández +2 more
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An introduction to the full random effects model
CPT: Pharmacometrics & Systems Pharmacology, 2022 The full random‐effects model (FREM) is a method for determining covariate effects in mixed‐effects models. Covariates are modeled as random variables, described by mean and variance.
Gunnar Yngman +4 more
doaj +1 more source
Sichuan jingshen weisheng, 2021 The purpose of the paper was to introduce the three special tests of the survival data and the SAS implementation. Specifically， it was the multiple comparisons， the trend test and the covariate test of the survival data.
Hu Chunyan, Hu Liangping
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Functional PCA With Covariate-Dependent Mean and Covariance Structure
Technometrics, 2022 28 pages, 3 ...
Fei Ding +3 more
openaire +2 more sources
To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias
Journal of Causal Inference, 2015 “M-Bias,” as it is called in the epidemiologic literature, is the bias introduced by conditioning on a pretreatment covariate due to a particular “M-Structure” between two latent factors, an observed treatment, an outcome, and a “collider.” This ...
Ding Peng, Miratrix Luke W.
doaj +1 more source
From patterned response dependency to structured covariate dependency: categorical-pattern-matching [PDF]
, 2017 Data generated from a system of interest typically consists of measurements from an ensemble of subjects across multiple response and covariate features, and is naturally represented by one response-matrix against one covariate-matrix.
Fushing, Hsieh +3 more
core +4 more sources
Covariance-on-covariance regression
BiometricsABSTRACT A covariance-on-covariance regression model is introduced in this manuscript. It is assumed that there exists (at least) a pair of linear projections on outcome covariance matrices and predictor covariance matrices such that a log-linear model links the variances in the projection spaces, as well as additional covariates of ...
Yi Zhao, Yize Zhao
openaire +3 more sources