Methods of Rubin (1983) for robust estimation of a mean and covariance matrix and associated parameters are extended to analyse data with missing values. The methods are maximum likelihood (ML) for ...

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.

We find that covariance matrix forecasts for an international interest rate portfolio generated by a model that incorporates interest-rate level volatility effects perform best with respect to ...