https://www.econstor.eu/handle/10419/77175
EconStor: Finite sample efficiency of OLS in linear regression models with long-memory disturbances
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
linear regression modelslong memoryfinitesampleefficiency
https://research.monash.edu/en/publications/the-consistency-of-mdl-for-linear-regression-models-with-increasi/
The consistency of MDL for linear regression models with increasing signal-to-noise ratio - Monash...
linear regression modelssignal to noiseconsistencymdlincreasing
https://iaras.org/home/caijbb/development-of-an-algorithm-for-the-transition-from-regression-models-to-optimization-models-in-the-differential-diagnosis-of-iron-deficiency-anemia-and-thalassemia-in-children-in-the-republic-of-artsakh
Development of an Algorithm for the Transition From Regression Models to Optimization Models in the...
Development of an Algorithm for the Transition From Regression Models to Optimization Models in the Differential Diagnosis of Iron Deficiency Anemia and...
for theregression modelsdevelopmentalgorithmtransition
https://cran.wustl.edu/web/packages/psfmi/vignettes/psfmi_LogisticModels.html
Pooling and Selection of Logistic Regression Models
logistic regressionpoolingselectionmodels
https://mural.maynoothuniversity.ie/id/eprint/5755/
Living with Collinearity in Local Regression Models - MURAL - Maynooth University Research Archive...
living withregression modelsmaynooth universityresearch archivelocal
https://publires.unicatt.it/en/publications/inference-for-spatial-regression-models-with-functional-response-/
Inference for spatial regression models with functional response using a permutational approach -...
regression modelsinferencespatialfunctionalresponse
https://ideas.repec.org/p/azt/cemmap/08-04.html
Endogeneity in quantile regression models: a control function approach
Downloadable! This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity...
regression modelsendogeneitycontrolfunctionapproach
https://events.ubc.ca/event/introduction-to-machine-learning-regression-models__trashed-3/2024-07-03/
Introduction to Machine Learning: Regression Models - UBCevents
Jul 3, 2024 - This workshop focuses on regression models to provide participants with a foundational understanding of machine learning concepts, techniques, and tools used...
introduction tomachine learningregression models
https://ve.scielo.org/scielo.php?script=sci_arttext&pid=S0254-07702006000200007&lng=pt&nrm=iso&tlng=es
Regression models for the prediction of high impact polystyrene properties using operational...
regression modelsfor thehigh impactpolystyrene propertiesprediction
https://www.econbiz.de/Record/neural-network-test-and-nonparametric-kernel-test-for-neglected-nonlinearity-in-regression-models-lee-tae-hwy/10004966216
Neural Network Test and Nonparametric Kernel Test for Neglected Nonlinearity in Regression Models -...
This article considers two conditional moment tests for neglected nonlinearity in regression models and examines their finite sample performance. The two tests...
neural networkregression modelstestkernelneglected
https://www.epj-conferences.org/articles/epjconf/abs/2021/05/epjconf_chep2021_04031/epjconf_chep2021_04031.html
Development of FPGA-based neural network regression models for the ATLAS Phase-II barrel muon...
EPJ Web of Conferences, open-access proceedings in physics and astronomy
neural networkregression modelsfor thephase iidevelopment
https://www.ornl.gov/publication/machine-learning-based-regression-models-ironmaking-blast-furnace-automation
Machine Learning-Based Regression Models for Ironmaking Blast Furnace Automation | ORNL
Computational fluid dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex...
machine learningregression modelsblast furnacebasedironmaking
https://www.mdpi.com/1424-8220/20/23/6742
Wind Turbine Gearbox Condition Monitoring Based on Class of Support Vector Regression Models and...
The intelligent condition monitoring of wind turbines reduces their downtime and increases reliability. In this manuscript, a feature selection-based...
support vector regressionwind turbinecondition monitoringgearboxbased
https://www.mitacs.ca/our-projects/regression-models-for-credit-card-strategies/
Regression Models for Credit Card Strategies - Mitacs
ATB Financial is a large Alberta based full service financial institution. The Card Services department was formed 5 years ago and is growing rapidly. The Card...
regression modelscredit cardstrategiesmitacs
https://researchportal.hw.ac.uk/en/publications/rank-estimation-in-cointegrated-vector-auto-regression-models-via/
Rank estimation in cointegrated vector auto-regression models via automated Trans-dimensional...
regression modelsrankestimationvectorauto
https://nofima.com/publication/360431/
Regression models with process variables and parallel blocks of raw material measurements - Nofima
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https://pdxscholar.library.pdx.edu/cengin_fac/331/
"Comparisons of Linear Regression Models for Properties of Alkaliactiva" by Arkamitra Kar, Udaya B....
Concrete with alkali-activated binder (AAB) is increasingly considered as a better alternative to conventional portland cement (PC) concrete due to its...
linear regression modelsfor propertiescomparisonskarudaya
https://repository.lsu.edu/plantsoil_pubs/712/
"Wavelet regression models for predicting flood stages in rivers: A cas" by Rajeev Ranjan Sahay and...
Combining discrete wavelet transform (DWT) and autoregression (AR), two types of wavelet regression (WR) models were developed for forecasting 1-day-ahead...
regression modelswaveletfloodstagesrivers
https://ijcttjournal.org/archives/ijctt-v72i6p107
Comparative Analysis of Panel Data Regression Models on Nigeria Money Deposit Bank Dataset
Panel data regression models have gained significant attention in empirical research due to their ability to capture both cross-sectional and time-series...
comparative analysisdata regressionpanelmodelsnigeria
https://www.varsitytutors.com/practice/subjects/ap-statistics/help/linear-regression-models
Linear Regression Models - AP Statistics... | Varsity Tutors
Get help with Linear Regression Models in AP Statistics. Get detailed explanations, step-by-step solutions, and instant feedback to improve your skills.
linear regression modelsap statisticsvarsity tutors
https://avesis.omu.edu.tr/yayin/3f87d8f4-184a-4018-89a7-6b68b52135e6/comparison-of-random-regression-models-with-different-order-legendre-polynomials-for-genetic-parameter-estimation-on-race-completion-speed-of-arabian-horses
Comparison of Random Regression Models with Different Order Legendre Polynomials for Genetic...
regression modelscomparisonrandomdifferentorder
https://cran.dcc.uchile.cl/web/packages/clarify/vignettes/clarify.html
clarify: Simulation-Based Inference for Regression Models
regression modelsclarifysimulationbasedinference
https://hrcak.srce.hr/en/clanak/460268
A comparison of multilevel ordinal regression models in the analysis of police force ratings
In the literature several methods have been developed to model ordinal data while considering their natural ordering. However, this study sought to compare two...
ordinal regressionpolice forcecomparisonmultilevelmodels
https://digitalcommons.usf.edu/jpt/vol16/iss4/6/
"Simulation-Based Regression Models to Estimate Bus Routes and Network " by Yaser E. Hawas
This paper presents an approach to estimate bus route and network travel times using micro-simulation. This can be used in predicting the effectiveness of bus...
regression modelsbus routessimulationbasedestimate
https://community.sisense.com/forum/cdt-44/topic/a-beginners-guide-to-linear-regression-models-in-python-5196/?focus_post=11693
A Beginner's Guide To Linear Regression Models In Python | CDT | Sisense Community
Mar 2, 2023 - Does your team prefer Python over R? Or are you looking to brush up your on your Python skills? We'll walk through a simple example of a linear regression...
linear regression modelsguide tobeginnerpythoncdt
https://fr.mathworks.com/help/econ/create-regression-models-with-arima-errors.html
Create Regression Models with ARIMA Errors - MATLAB & Simulink
Create regression models with autoregressive integrated moving average errors using regARIMA or the Econometric Modeler app.
regression modelscreatearimaerrorsmatlab
https://www.sciensano.be/fr/biblio/relative-response-factors-and-multiple-regression-models-liquid-chromatography-quantify-low-dosed
Relative response factors and multiple regression models in liquid chromatography to quantify...
multiple regressionliquid chromatographyrelativeresponsefactors
https://www.ijariit.com/manuscript/ai-based-cancer-detection-using-frcnn-random-forest-svm-and-regression-models/
Research Paper: AI-Based Cancer Detection using FRCNN, Random Forest, SVM, and Regression Models -...
Dec 23, 2024 - Early detection of cancers, especially in the mouth, throat, and lungs, significantly improves patient survival rates. This paper presents a comprehensive...
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https://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S0375-15892004000300005&lng=es&nrm=iso
Application of random regression models to the genetic evaluation of cow weight in Bonsmara cattle...
regression modelsto thegenetic evaluationapplicationrandom
https://research.rciueducation.org/en/publications/modeling-recidivism-through-bayesian-regression-models-and-deep-n-3/
Modeling recidivism through bayesian regression models and deep neural networks - Regnum Christi...
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https://research.tilburguniversity.edu/en/publications/central-limit-theorems-for-least-squares-estimators-in-linear-reg/
Central limit theorems for least squares estimators in linear regression models including lagged...
central limit theoremslinear regression modelsleastsquaresestimators
https://bugfree.ai/knowledge-hub/evaluating-regression-models-mae-mse-r-squared
Evaluating Regression Models: MAE, MSE, and R-Squared - Machine Learning Interview Guide |...
A comprehensive guide on evaluating regression models using MAE, MSE, and R-Squared metrics, essential for machine learning interviews. Master machine learning...
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https://blog.stata.com/tag/regression-models/
regression models Archives - The Stata Blog
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https://research.ceu.edu/en/publications/using-multiple-linear-regression-models-to-identify-factors-under/
Using multiple linear regression models to identify factors underlying avian species imperilment in...
multiple linear regressionusingmodelsidentifyfactors
https://portal.fis.tum.de/en/publications/bayesian-inference-of-binary-regression-models-with-parametric-li/
Bayesian inference of binary regression models with parametric link - Technical University of Munich
bayesian inferenceregression modelsbinaryparametrictechnical
https://edoc.ku.de/id/eprint/3706/
KU.edoc: Asymptotically optimal tests and optimal designs for testing the mean in regression models...
and designsregression modelskuedocoptimal
https://studylib.net/doc/27843735/michael-h.-kutner--christopher-j-nachtsheim--john-neter--...
Applied Linear Regression Models - 4th Ed | Kutner, Nachtsheim, Neter
Explore applied linear regression models with this comprehensive 4th edition textbook. Covers theory, applications, model building, diagnostics, and...
linear regression modelsappliednachtsheim
https://scholarsarchive.byu.edu/etd/2226/
"Zero-Inflated Censored Regression Models: An Application with Episode " by Jonathan P. Prasad
The objective of this project is to fit a sequence of increasingly complex zero-inflated censored regression models to a known data set. It is quite common to...
regression modelsby jonathanzeroinflatedcensored
https://rdrr.io/cran/glm.predict/
glm.predict: Predicted Values and Discrete Changes for Regression Models version 4.3-0 from CRAN
Functions to calculate predicted values and the difference between the two cases with confidence interval for lm() [linear model], glm() [generalized linear...
regression modelsglmpredictvaluesdiscrete
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217967
Functional form estimation using oblique projection matrices for LS-SVM regression models | PLOS One
Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to...
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https://conservancy.umn.edu/items/a739b293-0491-45bf-a64f-9507e2fbc20f
An Elicitation Method for Multiple Linear Regression Models
multiple linear regressionmethodmodels
https://researchportalplus.anu.edu.au/en/publications/robust-model-selection-in-linear-regression-models/
Robust Model Selection in Linear Regression Models - The Australian National University
linear regression modelsthe australiannational universityrobustselection
https://research.vu.nl/en/publications/misspecification-in-linear-spatial-regression-models-3/
Misspecification in Linear Spatial Regression Models - Vrije Universiteit Amsterdam
vrije universiteit amsterdamregression modelslinearspatial
https://www.educative.io/courses/linear-algebra-for-data-science-using-python/classification-through-regression
Understanding Classification Using Regression Models in Data Science
Learn how classification can be performed through regression models using softmax, one-hot encoding, and categorical cross-entropy loss in Python.
regression modelsin dataunderstandingclassificationusing
https://arxiv.org/abs/1906.10221
[1906.10221] Parametric versus Semi and Nonparametric Regression Models
Abstract page for arXiv paper 1906.10221: Parametric versus Semi and Nonparametric Regression Models
regression modelsparametricversussemi
https://repository.lib.ncsu.edu/items/f210924c-b4c4-4ba7-b060-ebfc3acb271a
Bayesian Inference in High-dimensional Regression Models using Sparse Projection Posterior.
bayesian inferenceregression modelshighdimensionalusing
https://www.sendowl.com/s/android-development/linear-regression-for-android-build-price-prediction-apps-by-udemy/
Buy Train ML Regression Models & Build Predictive Android Apps on Sendowl
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https://pure.psu.edu/en/publications/a-deterministic-annealing-approach-for-parsimonious-design-of-pie/
A Deterministic Annealing Approach for Parsimonious Design of Piecewise Regression Models - Penn...
design ofregression modelsdeterministicannealingapproach
https://birkeland.uib.no/time-scale-dependence-of-solar-wind-based-regression-models-of-ionospheric-electrodynamics/
Time-scale dependence of solar wind-based regression models of ionospheric electrodynamics -...
Oct 2, 2020 - Illustration: NASA One of the important pieces in the puzzle to understand how Earth is coupled to space, is the transfer of energy from the solar wind to the...
time scalesolar windregression modelsdependencebased
https://research.utwente.nl/en/publications/displacement-prediction-of-slow-moving-landslides-using-insar-and/
Displacement prediction of slow-moving landslides using InSAR and ensemble regression models based...
regression modelsdisplacementpredictionslowmoving
https://ricerca.unich.it/handle/11564/102228
Modelling Coupled Environmetal Variables by Dynamic Regression Models
regression modelsmodellingcoupledvariablesdynamic
https://pupuweb.com/da0-001-best-technology-for-creating-multiple-linear-regression-models/
DA0-001: Best Technology for Creating Multiple Linear Regression Models - PUPUWEB
Apr 23, 2024 - Discover why R is the ideal choice for building multiple linear regression models. Learn about R's powerful statistical capabilities and how it simplifies
multiple linear regressionbest technologycreatingmodels
https://research.chalmers.se/publication/505229
Minimization of water pumps' electricity usage: A hybrid approach of regression models with...
Due to pervasive deployment of electricity-propelled water-pumps, water distribution systems (WDSs) are energy-intensive technologies which are largely...
water pumpselectricity usagehybrid approachregression modelsminimization
https://bytez.com/docs/arxiv/1901.07643/paper
Solving All Regression Models For Learning Gaussian Networks Using Givens Rotations | Read Paper on...
Jan 22, 2019 - Score based learning (SBL) is a promising approach for learning Bayesian networks. The initial step in the majority of the SBL algorithms consists of computing...
regression modelsfor learningread papersolvinggaussian
https://blogs.sas.com/content/iml/2021/08/11/sweep-operator-ls-regression.html
More on the SWEEP operator for least-square regression models - The DO Loop
One of the benefits of using the SWEEP operator is that it enables you to "sweep in" columns (add effects to a model) in any order.
more onthe sweepregression modelsoperatorleast
https://www.openread.academy/paper/reading?corpusId=548778855
Navigating Multicollinearity in Linear Regression Models: Implications for Big Data Analysis
linear regression modelsbig datanavigatingmulticollinearityimplications
https://benny.aeaweb.org/articles?id=10.1257/jep.15.4.29
Semiparametric Censored Regression Models - American Economic Association
Semiparametric Censored Regression Models by Kenneth Y. Chay and James L. Powell. Published in volume 15, issue 4, pages 29-42 of Journal of Economic...
american economic associationregression modelscensored
https://publications.hse.ru/articles/65982986
Difference-based semiparametric estimation of partial linear regression models
linear regression modelsdifferencebasedestimationpartial
https://eldorado.tu-dortmund.de/items/156f5061-dece-4ff3-aea8-888139a25260/full
Robust covariance estimation in mixed-effects meta-regression models
In this PhD thesis we consider robust (sandwich) variance-covariance matrix estimators in the context of univariate and multivariate meta-analysis and...
regression modelsrobustcovarianceestimationmixed
https://experts.unthsc.edu/en/publications/sample-size-determination-for-between-group-comparisons-in-mixed--2/
Sample size determination for between group comparisons in mixed-effects logistic regression models...
sample size determinationlogistic regressiongroupcomparisonsmixed
https://idr.nitk.ac.in/items/74d5d096-7b3c-4340-9078-4ccbce48e1b5
Development of machine learning regression models for the prediction of tensile strength of...
Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and fabrication of surface composites....
machine learningregression modelsfor thetensile strengthdevelopment
https://www.gse-journal.org/articles/gse/ref/2004/03/g0352/g0352.html
Computing approximate standard errors for genetic parameters derived from random regression models...
Genetics Selection Evolution, an international research journal in genetics
regression modelscomputingapproximatestandarderrors
https://pubmed.ncbi.nlm.nih.gov/30960318/
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of...
Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for...
regression modelsextendedpumpingcapabilityviscous
https://nij.ojp.gov/library/publications/class-regression-models-pairwise-comparisons-forensic-handwriting-comparison
A Class of Regression Models for Pairwise Comparisons of Forensic Handwriting Comparison Systems |...
a classregression modelspairwisecomparisonsforensic
https://www.math-stockholm.se/en/kalender/luciano-egusquiza-castillo-boosting-regression-models-with-neural-networks-because-we-cann-1.1408429?date=2025-06-09&orgdate=2025-01-16&length=1&orglength=0
Luciano Egusquiza Castillo: Boosting Regression Models with Neural Networks, Because We CANN | SMC
regression modelsneural networkslucianocastilloboosting
https://scholarworks.gnu.ac.kr/item/b1d86e6a-b0a3-4286-89b8-a216cd28c4d7
ScholarWorks :: Study on the applicability of regression models and machine learning models for...
Accurately predicting the strength of concrete is vital for ensuring the safety and durability of structures, thereby contributing to time and cost savings thro
on theregression modelsmachine learningstudyapplicability
https://rpubs.com/dernapo/143577
RPubs - Regression Models - week2
regression models
https://aet.irost.ir/article_1514.html
Evaluation of some regression models in the prediction of dissolved oxygen and water temperature of...
The climate change phenomenon has resulted in increased unpredictability regarding water availability in dry and semi-dry areas. This challenge affects not...
regression modelsthe predictiondissolved oxygenwater temperatureevaluation
https://cran.csiro.au/web/packages/sjPlot/vignettes/plot_interactions.html
Plotting Interaction Effects of Regression Models
regression modelsplottinginteractioneffects
https://repository.helmholtz-hzi.de/handle/10033/621230
Effects of drift and noise on the optimal sliding window size for data stream regression models
on thesliding windowdata streamregression modelseffects
https://www.pluralsight.com/courses/building-regression-models-scikit-learn
Building Regression Models with scikit-learn
regression modelsscikit learnbuilding
https://repository.gatech.edu/entities/publication/8e7d9f0e-62f8-4fc6-81d3-5db6ea8ef207
Regression models to predict levels of AOX generation. Project 3826, report 1 : a progress report...
regression modelspredictlevelsaoxgeneration