Hello, I have some problem understing the Gaussian regression and the way it works.
Could you please explain to me some things?
The first thing I don't understand is why this regression does it use the joint/multivariate probability to get new value of the Y?
I have red this in the website:
MCMC is a family of sampling algorithms, which means given a distribution, these algorithms return samples according to this distribution. Many problem, bayesian posterior inference for instance, require you compute the posterior distribution P(θ|D), most of...
''However, with large sample size and a larger average counts,''
What do you mean with ''large average counts'' ? sorry not native-english... Can you make an example?
''many say around 8 or larger, the Poisson begins to approximate a normal distribution and a linear model can be...
Hello here is my problem.
I am analizying some tennis matches, and I am able to see the highest odd (bookmaker's odd) reached by that tennis player in N-matches (N is number of matches)
Then I take all the highest odds reached by that tennis player during his N-matches , and...
Hello I want to ask you, before to making a regression should we understand which distribution follow the datas?
Let's take an example: if the data have a poisson distribution, then I will run a Poisson regression?
If the data follow a gaussian then one should use...
Example I saw this discussion:
This guy asked to stack exange:
(My personal question which I would ask to you, are Question n1 and Question n2)
Hi, I have a set of data. Those data are based on data mining from my website. I have the number of users per month who go to my website ( X ) , and the time they spent on the website on each webpage ( y ) .
Now with this dataset as an example, could you...
Hi, after a regression is necessary to make an analisy of residuals to know if the model were accurate? ù
Noob here, could you explaine me please, why you could do an analisy of residuals and for which purpose does it serve?
In a dice every event has the same odds to happen (1/6).
I was asking how would it be the bernoulli distribution if the events would have different probabilities to happen
Let's keep the example of a black swan when no one has never seen it before. How do you trasfrom...
Hi I was studying probability density and on a site I read this example
Mr. Rossi waits for a phone call from Mr. Bianchi who has announced that he will call, in an unspecified instant, between 4:00 pm and 6:00 pm. Mr. Rossi must however be away from 4.45 pm to 5.00 pm. What is the probability...
Thank you very much. Yes you can have an approximate idea of the linear correlation/non linear correlation between two variables.
There is somenthing in statistic field to do extrapolation in a more accurate than linear regression?
I have red about robust statistic