This post mainly focused on how to decipher the underlying mechanism of doubly robust estimators via logical operators, which was introduced in causal inference II course.

The third term has just passed, and I would like to continue my last post on the discussion of some asymptotic properties and geometric interpretations for unbiased estimators.

I have taken the course Statistical Theory instructed by Prof.Constantine this term, focusing on the connection among decision theory, sufficient statistics, likelihood principle and evidence, and unbiased estimators and information bound.

Neurohacking is the continuous process of using, improving and designing the simplest open source scripted software that depends on the minimum number of software platforms and is dedicated to improving the correctness, reproducibility, and speed of neuroimage data analysis.

Consider you are fitting a linear regression on the given dataset, and draw the scatter plot of residuals vs predicted values. However, you might feel confused when you get the following interesting plots.