(hello, just advice

offtopic, but in school at 1st semester we had "econometry" and it was about installing Gretl software (i dont know if its free) and we try different data and looking st things like R^2 and p-value i clicked yt first video saga https://www.youtube.com/watch?v=lsWUy3ALDmw

i feel its more about testing "relationships" in your data mess. you jumped straight into prediction, you did fast choose for arima model family and now diving all direction withouse stable base

i mean, maybe start over and go step 1, 2, 3 (adding problems to problems is like running from solutions to technologies.

1. just set your description

2. then look and write few paragraph about each data (as you mentioned N=10 its very short length

3. then maybe set advices which data to try to use/involve

4. open prognostic part, write each paragraph why using some kind of model, why choosing parameters ...do fitting, write plot, check for info criteria, write conclusions on finding results

( in this stage you have good material for someone to look up and give advice or maybe its final stage as not enough data / you found "low correlation" / low forecast precision

good research is better > then none (advice based on data/findings is sometimes much better, it brings peace and stable ground for next)

but i do think after you do these 4 parts and gain cleer sight and organization and little pause, you can start building trustworthy models

(just from my point your goal is more filter which data correlate with wanted one (as a lot of vectors are only 10-30 length

(its just my point of view :-)

(hello, just advice

offtopic, but in school at 1st semester we had "econometry" and it was about installing Gretl software (i dont know if its free) and we try different data and looking st things like R^2 and p-value i clicked yt first video saga https://www.youtube.com/watch?v=lsWUy3ALDmw

i feel its more about testing "relationships" in your data mess. you jumped straight into prediction, you did fast choose for arima model family and now diving all direction withouse stable base

i mean, maybe start over and go step 1, 2, 3 (adding problems to problems is like running from solutions to technologies.

1. just set your description

2. then look and write few paragraph about each data (as you mentioned N=10 its very short length

3. then maybe set advices which data to try to use/involve

4. open prognostic part, write each paragraph why using some kind of model, why choosing parameters ...do fitting, write plot, check for info criteria, write conclusions on finding results

( in this stage you have good material for someone to look up and give advice or maybe its final stage as not enough data / you found "low correlation" / low forecast precision

good research is better > then none (advice based on data/findings is sometimes much better, it brings peace and stable ground for next)

but i do think after you do these 4 parts and gain cleer sight and organization and little pause, you can start building trustworthy models

(just from my point your goal is more filter which data correlate with wanted one (as a lot of vectors are only 10-30 length

(its just my point of view :-)

edit1:

can I ask, is only for school purpose or for work? I mean, you can model data with linear regression and build simple arima model for prediction (I mean, if you strugle deliver solution at high level, you can create/build really good solution at easy/medium :-)