Results 61 to 70 of about 1,128,323 (301)
In this study, multi linear regression ( MLR), artificial neural network (ANN) and adaptive neuro fuzzy inference system(ANFIS) techniques were developed to predict the Dissolve oxygen concentration at down stream of Agra city, using monthly input data ...
S Abba, Sinan Jasim Hadi, J. Abdullahi
semanticscholar +1 more source
Cluster-Robust Variance Estimation for Dyadic Data [PDF]
Dyadic data are common in the social sciences, although inference for such settings involves accounting for a complex clustering structure. Many analyses in the social sciences fail to account for the fact that multiple dyads share a member, and that ...
Aronow, Peter M. +2 more
core +3 more sources
Log-Regularly Varying Scale Mixture of Normals for Robust Regression
Linear regression with the classical normality assumption for the error distribution may lead to an undesirable posterior inference of regression coefficients due to the potential outliers.
Hamura, Yasuyuki +2 more
core +1 more source
Causal Dantzig: Fast inference in linear structural equation models with hidden variables under additive interventions [PDF]
Causal inference is known to be very challenging when only observational data are available. Randomized experiments are often costly and impractical and in instrumental variable regression the number of instruments has to exceed the number of causal ...
Dominik Rothenhausler +2 more
semanticscholar +1 more source
Bayesian Inference in Numerical Cognition: A Tutorial Using JASP
Researchers in numerical cognition rely on hypothesis testing and parameter estimation to evaluate the evidential value of data. Though there has been increased interest in Bayesian statistics as an alternative to the classical, frequentist approach to ...
Thomas J. Faulkenberry +2 more
doaj +1 more source
In practical applications of regression models, we may meet with the situation where a true model is misspecified in some other forms due to certain unforeseeable reasons, so that estimation and statistical inference results obtained under the true and ...
Ruixia Yuan, Bo Jiang, Yongge Tian
doaj +1 more source
Restricted Inference in Circular-Linear and Linear-Circular Regression
In this paper, we investigate restricted inference on two types of circular regression, called circular-linear and linear-circular. Our aim in this paper is to propose an alternative method which is necessary to apply where one observes a weak association between circular dependent and linear predictor variables, or between linear dependent and ...
Thelge Buddika Peiris, Sungsu Kim
openaire +2 more sources
Linear regression with many controls of limited explanatory power
We consider inference about a scalar coefficient in a linear regression model. One previously considered approach to dealing with many controls imposes sparsity, that is, it is assumed known that nearly all control coefficients are (very nearly) zero. We
Chenchuan Li, Ulrich K. Müller
semanticscholar +1 more source
Parent‐to‐Child Information Disclosure in Pediatric Oncology
ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor +12 more
wiley +1 more source
ABSTRACT Introduction Cognitive impairment and exercise intolerance are common in dialysis patients. Cerebral perfusion and oxygenation play a major role in both cognitive function and exercise execution; HD session per se aggravates cerebral ischemia in this population. This study aimed to compare cerebral oxygenation and perfusion at rest and in mild
Marieta P. Theodorakopoulou +10 more
wiley +1 more source

