If this were the case, wouldn’t you expect the mean of the code steering vectors to also be a good code steering vector? But in fact, Jacob says that this is not case. Edit: Actually it does work when scaled—see nostalgebraist’s comment.
I think this still contradicts my model: mean_i(<d, theta_i>) = <d, mean_i(theta_i)> therefore if the effect is linear, you would expect the mean to preserve the effect even if the random noise between the theta_i is greatly reduced.
If this were the case, wouldn’t you expect the mean of the code steering vectors to also be a good code steering vector?
But in fact, Jacob says that this is not case.Edit: Actually it does work when scaled—see nostalgebraist’s comment.I think this still contradicts my model: mean_i(<d, theta_i>) = <d, mean_i(theta_i)> therefore if the effect is linear, you would expect the mean to preserve the effect even if the random noise between the theta_i is greatly reduced.
Good catch. I had missed that. This suggest something non-linear stuff is happening.