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 ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variable under consideration. Multivariate analysis techniques may be used for several ...

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 ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

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 ...