| Version 2.5 (R14SP3) Financial Toolbox™ Software Release Notes |   |
Version 2.5 (R14SP3) Financial Toolbox Software
This table summarizes what's new in Version 2.5 (R14SP3).
| New Features and Changes | Version
Compatibility Considerations | Fixed Bugs and Known Problems | Related Documentation at Web Site |
|---|
Yes
Details below | No | Bug
Reports | No |
New Statistical Functions
Version 2.5 introduces a set of financial statistical computation
routines that compute values, such as mean and covariance, when there
are missing data elements within a larger data set. These routines
implement the Expectation Conditional Maximization (ECM) algorithm
with various options that depend on the percentage of missing at random
(MAR) data within the data set. The table below lists the functions
that implement the ECM algorithm in Financial Toolbox software.
The following ECM functions have been added at this release.
Expectation Conditional Maximization
| ecmnfish | Fisher information matrix |
| ecmnhess | Hessian of negative log-likelihood function |
| ecmninit | Initial mean and covariance |
| ecmnmle | Mean and covariance of incomplete multivariate normal data |
| ecmnobj | Negative log-likelihood function |
| ecmnstd | Standard errors for mean and covariance of incomplete data |
| Version 3.0 (R2006a) Financial Toolbox Software | | Compatibility Summary for Financial Toolbox Software | |