The plm package for R lets you run a number of common panel data models, including
- The fixed effects (or within) estimator
- The random effects GLS estimator
It also allows for general GLS estimation, as well as GMM estimation, and includes a feature for heteroscedasticity consistent covariance estimation.
It’s very easy to use, it simply requires that you use a special type of dataframe that specifies which variable is the individual and which variable is the cluster/group (this is done using the pdata.frame) command. Once this is done, you can estimate models using the plm command and its options.
See the documentation (PDF) for more.