Timeline for Which is better: predict ignoring past values or not?
Current License: CC BY-SA 3.0
13 events
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May 25, 2017 at 16:23 | history | edited | Dinidiniz | CC BY-SA 3.0 |
deleted 80 characters in body
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May 24, 2017 at 21:45 | answer | added | LmnICE | timeline score: 1 | |
May 24, 2017 at 21:33 | history | edited | Dinidiniz | CC BY-SA 3.0 |
added 80 characters in body
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May 24, 2017 at 21:04 | history | edited | Dinidiniz | CC BY-SA 3.0 |
Add example to the question
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May 24, 2017 at 20:58 | history | edited | Dinidiniz | CC BY-SA 3.0 |
Add example to the question
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May 24, 2017 at 20:56 | comment | added | Dinidiniz | I will edit with an example. I just want to know why normally we don't include $b_i$ in the models to predict $b_{i+1}$. Is it wrong in someway? | |
May 24, 2017 at 20:53 | comment | added | Dinidiniz | @MichaelChernick I am not a Statistician, so correct me if I am wrong. When we make the linear regression to understand the constant $\alpha$ or the growth rate, we will have a intercept and slope. In this case the intercept will "include" the error, thus making it expected value be zero. | |
May 24, 2017 at 20:39 | comment | added | LmnICE | I'm confused: if $b_i$ is an observed value, then it's by definition real life data. Are both $b_i$ and $x_i$ observed variables (i.e. they are measured separately), or is $x_i$ measured then used to calculate $b_i$ in conjunction with some prior knowledge about $\alpha$? | |
May 24, 2017 at 20:32 | comment | added | Michael R. Chernick | Where is the error term in the linear relationship? | |
May 24, 2017 at 20:31 | comment | added | Guilherme Marthe | Also from your third equation, a loglog regression seems to make sense. | |
May 24, 2017 at 20:30 | comment | added | Guilherme Marthe | Can't you create a meaningful series/variable using both x and b? | |
May 24, 2017 at 20:24 | review | First posts | |||
May 24, 2017 at 20:32 | |||||
May 24, 2017 at 20:21 | history | asked | Dinidiniz | CC BY-SA 3.0 |