Under typical assumptions of IID samples I can see how we get to asymptotically normal sampling distributions for estimates from MLE, and for sufficiently large samples we will have estimates with sampling distributions are that practically close enough to normal. It is not true in general that estimates from MLE will follow a normal distribution.
I have an exercise just on that topic, excellent timing!
brilliant, brilliant video, the way you explain the relationships between important concepts is gold to me
Good stuff. Keep it up!
tomorrow i have a machine learning exam, just on time 😂😂😂😂😂😂😂
good luck!
Great as always
Under typical assumptions of IID samples I can see how we get to asymptotically normal sampling distributions for estimates from MLE, and for sufficiently large samples we will have estimates with sampling distributions are that practically close enough to normal. It is not true in general that estimates from MLE will follow a normal distribution.
Yea you’re right. I’m speaking from the perspective that we can use those typical assumptions, not from a more general one
That likelihood is definitely not convex!
haha that’s definitely my poor manim skills showing
Could you please explain completeness or complete statistic