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), ...

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.

Right now, YouTube marketing has become even more important with all the changes happening in the current digital landscape. What is also important is keeping up with trends and strategies to ensure ...

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.

An illustration of a magnifying glass. An illustration of a magnifying glass.