  We develop a general approach to valid inference after model selection. At
the core of our framework is a result that characterizes the distribution of a
post-selection estimator conditioned on the selection event. We specialize the
approach to model selection by the lasso to form valid confidence intervals for
the selected coefficients and test whether all relevant variables have been
included in the model.
