Description Details Legal Mumbo Jumbo Note Author(s) References
Exact Post Selection Inference with Applications to the Lasso.
This simple package supports the simple procedure outlined in Lee et al. where one observes a normal random variable, then performs inference conditional on some linear inequalities.
Suppose y is multivariate normal with mean μ and covariance Σ. Conditional on Ay <= b, one can perform inference on eta'mu by transforming y to a truncated normal. Similarly one can invert this procedure and find confidence intervals on eta'mu.
epsiwal is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
This package is maintained as a hobby.
Steven E. Pav shabbychef@gmail.com
Lee, J. D., Sun, D. L., Sun, Y. and Taylor, J. E. "Exact post-selection inference, with application to the Lasso." Ann. Statist. 44, no. 3 (2016): 907-927. doi:10.1214/15-AOS1371. https://arxiv.org/abs/1311.6238
Pav, S. E. "Conditional inference on the asset with maximum Sharpe ratio." Arxiv e-print (2019). http://arxiv.org/abs/1906.00573
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