A projection pursuit framework for testing general high-dimensional hypothesis

Understand

This article develops a framework for testing general hypothesis in high-dimensional models where the number of variables may far exceed the number of observations.

• Existing literature has considered less than a handful of hypotheses, such as testing individual coordinates of the model parameter.
• However, the problem of testing general and complex hypotheses remains widely open.
• We propose a new inference method developed around the hypothesis adaptive projection pursuit framework, which solves the testing problems in the most general case.