Results 31 to 40 of about 71,763 (309)
Stats, 2022 The first hitting time of a boundary or threshold by the sample path of a stochastic process is the central concept of threshold regression models for survival data analysis.
Mei-Ling Ting Lee, George A. Whitmore
doaj +1 more source
A regularized stochastic configuration network based on weighted mean of vectors for regression [PDF]
PeerJ Computer Science, 2023 The stochastic configuration network (SCN) randomly configures the input weights and biases of hidden layers under a set of inequality constraints to guarantee its universal approximation property.
Yang Wang +4 more
doaj +2 more sources
Journal of Probability and Statistics, 2018 The analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multicollinearity exists among the explanatory variables. The Stochastic Restricted Ridge Estimator (SRRE), Stochastic Restricted Almost
Manickavasagar Kayanan +1 more
doaj +1 more source
Modelling daily water temperature from air temperature for the Missouri River [PDF]
PeerJ, 2018 The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature.
Senlin Zhu +2 more
doaj +2 more sources
Stochastic EM for Shuffled Linear Regression
CoRR, 2018 We consider the problem of inference in a linear regression model in which the relative ordering of the input features and output labels is not known. Such datasets naturally arise from experiments in which the samples are shuffled or permuted during the protocol.
Abubakar Abid, James Y. Zou
openaire +2 more sources
Stochastic regression and its application to hedging in finance [PDF]
, 2009 In this paper we investigate how to employ stochastic regression to hedge risks in finance, where the risk of a security is measured by its quadratic variation process.
Liu, Zhi +3 more
core +1 more source
Journal of Big Data, 2023 This paper presents a stochastic imputation approach for large datasets using a correlation selection methodology when preferred commercial packages struggle to iterate due to numerical problems. A variable range-based guard rail modification is proposed
Benjamin D. Leiby, Darryl K. Ahner
doaj +1 more source
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes [PDF]
, 2018 Recent advances in Deep Learning and probabilistic modeling have led to strong improvements in generative models for images. On the one hand, Generative Adversarial Networks (GANs) have contributed a highly effective adversarial learning procedure, but ...
Bernt Schiele (17432442) +2 more
core +3 more sources
ON THE USING OF THE SHANNON INFORMATION QUANTITY IN THE TASKS ASSOCIATED WITH LINEAR REGRESSION
St. Petersburg Polytechnical University Journal: Physics and Mathematics, 2019 The article discusses the use of the Shannon information quantity (SIQ) in the tasks associated with linear regression. It is shown that the SIQ contained in the response components with respect to stochastic parameters is expressed through the Fisher ...
Pichugin Yury
doaj +1 more source
A review on quantile regression for stochastic computer experiments
Reliability Engineering & System Safety, 2020 We report on an empirical study of the main strategies for quantile regression in the context of stochastic computer experiments. To ensure adequate diversity, six metamodels are presented, divided into three categories based on order statistics, functional approaches, and those of Bayesian inspiration.
Torossian, Léonard +3 more
openaire +5 more sources