Multivariate statistical inference encompasses methods that evaluate multiple outcomes or parameters jointly, allowing researchers to understand complex interdependencies within data. Permutation ...

Multivariate longitudinal data are common in medical, industrial, and social science research. However, statistical analysis of such data in the current literature is restricted to linear or ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

In this note we examine the bias and small sample efficiency of certain estimators for the parameters of a linear regression function when some observations are missing. The estimators studies in this ...

"Big data" and the ability to discover patterns and make predictions from large amounts of data is revolutionizing almost every other scientific and technical field. The Data and Predictive Analytics ...

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

I actively involve in professional and academic activities such as serving as frequent referees for peer-reviewed statistical journals such as: Journal of the Royal Statistical Society (Series B and C ...

Here is a list of the best free statistical analysis software for Windows 11/10. If you have a large dataset of numerical data and want to evaluate and analyze it, this guide is for you. In this ...