Abstract: The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), ...

Objective Patients with atrial fibrillation (AF) frequently have multiple comorbidities that increase the risk of hospitalisation and contribute to higher mortality. However, studies examining the ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

The biopharmaceutical industry must navigate a complex ecosystem in which therapy innovation is linked intrinsically to stringent quality standards and regulatory mandates. Raman spectroscopy has ...

The blend of butadiene and acrylonitrile copolymer (NBR) with natural poly-cis-isoprene (NR) shows increased resistance to swelling in solvents in comparison to the individual components. In aerospace ...

Introduction: Increasing evidence suggests that individuals with obesity are at a higher risk of developing depression, and conversely, depression can contribute to the onset of obesity, creating a ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation ...

(A) Spatial relationships between gene expression and sex-specific functional connectivity abnormalities in MDD. (B) Association between MDD-related functional gradient alterations and gene expression ...