You can find the spreadsheets for this video and some additional materials here: drive.google.com/drive/folders/1sP40IW0p0w5IETCgo464uhDFfdyR6rh7 Please consider supporting NEDL on Patreon: www.patreon.com/NEDLeducation
Hi Saava, I am new to your channel been learning really allot, Great work. firstly wanted to get in touch with you if that's possible. secondly wanted to ask about the value which came up as the likely hood which was predicted 4263.23 was it next day or yearly ?
Hi Rustu and many thanks for your feedback! As for the Laplace distribution, the original video (th-cam.com/video/zR_liKniGOc/w-d-xo.html) already has the maximum likelihood parameter estimation. The catch is the following: if you solve the log-likelihood maximisation problem analytically, you will arrive at the solution that the location parameter m is equal to the sample median and the scale parameter b is equal to absolute average deviation.
You can find the spreadsheets for this video and some additional materials here: drive.google.com/drive/folders/1sP40IW0p0w5IETCgo464uhDFfdyR6rh7
Please consider supporting NEDL on Patreon: www.patreon.com/NEDLeducation
That was very well done! Very easy to follow.
Hi Saava,
I am new to your channel been learning really allot, Great work.
firstly wanted to get in touch with you if that's possible. secondly wanted to ask about the value which came up as the likely hood which was predicted 4263.23 was it next day or yearly ?
Very good tut! Keep going on like this! Thnx. Can we have it same for Laplace too?
Hi Rustu and many thanks for your feedback! As for the Laplace distribution, the original video (th-cam.com/video/zR_liKniGOc/w-d-xo.html) already has the maximum likelihood parameter estimation. The catch is the following: if you solve the log-likelihood maximisation problem analytically, you will arrive at the solution that the location parameter m is equal to the sample median and the scale parameter b is equal to absolute average deviation.