This paper applies univariate nonlinear time series analysis to the daily (TZS/USD) exchange rate data spanning from January 4, 2009 to July 27, 2015 to examine the behavior of exchange rate in ...

After EHAP, the incidence of HepA showed a faster downward trend than before in the central and western regions, while a slower downward trend than before in the eastern region. The results of ITS ...

View inline View popup Table 5 Univariate and multivariate regression analyses for factors associated with the development of neuropathic corneal pain after laser-assisted in-situ keratomileuses ...

Therefore, a black-box graph injection attack, Bayesian Ridge Regression Injection Attack (BRRIA), is proposed to study the impact of the internal relations on a system and to investigate the ...

Sparse matrix regression (SMR) is a two-dimensional supervised feature selection method that can directly select the features on matrix data. It uses several couples of left and right regression ...

Modeling of human exposure to aqueous algal odorants geosmin (earthy), 2-methylisoborneol (musty), and (trans,cis)-2,6-nonadienal (cucumber, fishy), and the solvent trichloroethylene (sweet chemical), ...

Official Code for "Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction (CVPR 2024)" and "Social Reasoning-Aware Trajectory Prediction via Multimodal Language Model ...

Classical univariate regression is the most used regression method in Analytical Chemistry. It is generally implemented by ordinary least squares (OLS) fitting using n points (xi, yi) to a response ...

Notably, Sweden’s nuclear energy share was forecasted using linear regression due to the instability of GM results, while France’s natural gas data required the removal of outliers and subsequent ...

Socioeconomic disparities were examined using the Sociodemographic Index (SDI) and Gini coefficient, while time-series analysis, regression models, and Joinpoint regression identified trends. Machine ...

The analysis produced graphs with the model and parameters of the logistic regression, the graph of the monthly contributions, a list of NRMSE values, the quotient between the number of features in ...