how do you compute the model with a minimum residual after fitting probability distributions on a dataset

Guest Jul 9, 2019

#1**0 **

Hello Guest... This is a sad suggestion, but heres a couple of links:

https://www.khanacademy.org/math/ap-statistics/random-variables-ap/discrete-random-variables/v/discrete-probability-distribution

https://www.khanacademy.org/math/ap-statistics/random-variables-ap#discrete-random-variables

I think the second link is a bit more helpful.

I don't have much time right now, sorry for the terrible answer.

PEACE:

\(tommarvoloriddle\)

.tommarvoloriddle Jul 9, 2019

#4**0 **

It was an attempt to help. When I asked a question like this, you said you had to ask something with numbers.

tommarvoloriddle
Jul 9, 2019

#6**0 **

BTW, it's tom. I posted it because I felt like the asker should find the answer themselves, and so I provided links. The links were supposed to help a bit. I am sorry that my answers cannot meet your standards.

tommarvoloriddle
Jul 10, 2019

#7**0 **

**They didn’t meet your standards either; yet you posted them**.

You referred to your own post as a “sad suggestion” then apologized for the “terrible answer” before you actually made the post. Isn’t that like dumping a big pile of raw bullshit on someone’s garden after being asked for blue and red roses?

Here’s a hypothetical:

Question: I have a garden that has white roses. Does anyone know where I can get blue and red roses and how to grow them?

Answer (from Tom): I’m not sure what roses are, except that they are plants. I know that fertilizer makes them grow good. And I have some raw bullshit that’s terrible (because it will burn your plants). So here, let me dump it on your garden.

Sorry I had to dump this bullshit on your garden, because I wanted to help, and I know this makes good fertilizer. Some day it will, I hope

--------------

**There is** **nothing** **to indicate** you are **sorry**; so you can take your attempts at emotional manipulation, along with the **excess** amounts of **bullshit **that you seem to have, and dump it in the sewer. Translation

GA

GingerAle
Jul 10, 2019

#8**0 **

How is the answer from me If I didn't write it? The part about roses?

tommarvoloriddle
Jul 10, 2019

#9**0 **

I would also direct you to websites like:

https://www.harmonygardens.net/

So, this might be helpful. You would click the designing garden button and...

There- that is a tom solution.

tommarvoloriddle
Jul 10, 2019

#10**0 **

the ... is because right now, I don't have time to type it out, I would type it out a bit more if I had time rn... But, I would come back to it, edit it, and make it a little "b******t."

tommarvoloriddle
Jul 10, 2019

#3**+3 **

This is also a terrible **question**.

*how do you compute the model with a minimum residual after fitting probability distributions on a dataset*

I can tell by the question that either you are in a master’s level statistic class, or a master’s level science class that requires these skills to complete assignments. My guess is the latter, because in a statistics class, you could ask and receive reasonable answers from your classmates or professor.

I can also tell by your posted question that you probably should not be in that class. Your posted question indicates a lack of communication skills, short-sighted thinking skills, and just plain laziness. If you posted this on stack exchange, it would be deleted, but not before you were mocked for being brain-dead.

The answer to your question is not difficult, but the actual process can be difficult. Start by using known data models that process the type of data you have. If it’s climate data then use climate models; if it’s biomedical data then use biomedical models. There are plenty of boxed models available for either of these types of data sets.

After computing the data using several boxed models, select the top (N) models that have the best fit based on Least squares and Chi squared statistics. To minimize the **residual**, you will need to analyze the residual. This “residue” is often referred to as “noise” in statistics and it’s composed of measurement errors, rounding errors, or random errors, and it can be false noise because the data falls outside the models measurement process.

To correct for noise and false noise, use **inverse** modeling. This is accomplished by setting one or more data elements for each multidimensional data point to an average, then rerunning the altered data using the same models that generated it. The outputs of this will start indicating from which dimensional parameters the noise is originating or where valid data is not utilized. After identifying the parameters of interests adjustments are made to accommodate or restrict the processing of the data in the original set.

Note the complexity of **inverse** modeling increases well beyond the exponential if your data points (P_{x}) have large numbers of dimensional parameters in its composite form; if some of the parameters have high dependency on other parameters, then it will increase more.

Some boxed model programs have Big O notations approximating the time needed for various inverse modeling procedures. It’s not unusual for the time to exceed thousands of hours on fast, highly optimized computers.

I think you should do it manually. This will give you an appreciation for what the computer is doing.

GA

GingerAle Jul 9, 2019

#11**0 **

Ginger is harsh Tom but she is also right.

You are offering answers to questions that you know nothing at all about.

You say people should find their own answers and I agree but showing them irrelevant websites is not helpful.

When you answer a question the asker has a fair expectation that you know something helpful.

It can be incredibly frustrating, to an asker, when someone , who cannot answer, pretends that they can.

I really like your level of enthusiasm and I do not want to dampen it too much, or for too long.

But please stay within your knowledge base.

Melody Jul 11, 2019