By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...

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), ...

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

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. Article Views ...

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 ...

Multivariate Analysis of an Indian bank's dataset about loan paybacks in R. Team project from UPC's Master's Degree in Data Science ...

Learn what analysis of variance (ANOVA) is, how it works, and when to use it. See how it helps compare means across multiple data groups in statistics and research.

Choices between immediate smaller reward and long-term larger reward are referred to as intertemporal choice. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural ...

fviz_eig(pca_model, addlabels = TRUE) # Scree Plot with factoextra package get_pca(pca_model2, "ind")$coord[1, ] # get Scores from pca Model pca_model2$scores[1 ...