Results 111 to 120 of about 312,189 (299)
ON MODELING SYSTEMS OF CROP ACREAGE DEMANDS [PDF]
This article presents an alternative approach to the specification of systems of crop acreage responses. Derived demands for acreages of individual crops are specified as conditional on total crop acreage, and related separability and dynamic ...
Coyle, Barry T.
core +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Esimasi Parameter Regresi Ridge Menggunakan Iterasi Hoerl, Kennard, Dan Baldwin (Hkb) Untuk Penanganan Multikolinieritas [PDF]
, 2015 Regression analysis is statistical method used to analyze the dependence of respond variables to predictor variable. In multiple linear regression analysis, there are assumptions that must be met, they are normality, homoscedasticity, absence of ...
Ispriyansti, D. (Dwi) +2 more
core
Advanced Intelligent Discovery, EarlyView.scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source
Kuwait Journal of ScienceThe performance of ordinary least squares (OLS) and ridge regression (RR) are influenced when outliers are present in y-direction with multicollinearity among independent variables. The robust RR with ridge parameters provides a biased estimator that has
doaj +1 more source
Do instructional attributes pose multicollinearity problems? An empirical exploration [PDF]
It is commonly perceived that variables ‘measuring’ different dimensions of teaching (construed as instructional attributes) used in student evaluation of teaching (SET) questionnaires are so highly correlated that they pose a serious multicollinearity ...
Hong Son Nghiem, Mohammad Alauddin
core
Advanced Intelligent Discovery, EarlyView.A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
AxiomsPredictive regression models often face a common challenge known as multicollinearity. This phenomenon can distort the results, causing models to overfit and produce unreliable coefficient estimates.
Muteb Faraj Alharthi, Nadeem Akhtar
doaj +1 more source
On the Identification of Time Varying Structures [PDF]
The identifiability of reduced form econometric models with variable coefficients is investigated using the control theoretic concepts of uniform complete observability and uniform complete controllability.
Kent D. Wall, Thomas F. Cooley
core
American Journal of Agricultural Economics, EarlyView.Abstract Discrete choice experiments are increasingly being used to estimate land managers' willingness to accept participation in incentive‐based environmental programs. This is a specific application of discrete choice experiments: the estimation of willingness to accept for a private good (program participation) where respondents have to make trade ...
Anastasio J. Villanueva +2 more
wiley +1 more source