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Regression that includes two or more non-constant independent variables.

0 votes

Help need to write mathematical equation

I am not exactly sure about what you're exactly looking for, but is the following OK?: $$\log{V} = C_m + Y + C_a + C_a \cdot y + S$$ Where $V$ stands for Capital_value_psf, C_m represents Micro_Post …
David's user avatar
  • 2,665
4 votes

Why $Cov(\pmb{y}, \pmb{\hat{y}}) = \pmb{y}^T \pmb{\hat{y}}$?

That is simply not true! $y^T\hat{y}$ can take values larger than 1, and it's not that hard to come with an example. Try the data $x=(0,1,2,3)$ $y=(6,8.1,9.9,12)$ Estimate the regression model for …
David's user avatar
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2 votes

Assumptions for multiple regression

I am not exactly sure about what "variation of $x$" means, but if it is that different observations should have different values for $x$, it is pretty obvious: you can't predict how $y$ changes as a f …
David's user avatar
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-1 votes

How to denote a simple slope coefficient (interaction)?

I don't know what sslope is but it reminds me of linear regression, where we build a model $Y=\beta_0 + \beta_1 x + \epsilon$ where: $\beta_0$ is a constant. $\beta_1$ represents the slope of the li …
David's user avatar
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0 votes
0 answers
93 views

Interaction term when involved variables are colinear

Let's say I want to fit a model that relates a target variable $Y$ to a set of predictors $X_1, ...X_n$. Let's also assume that two of them ($X_1$ and $X_2$ for example) are correlated but allow for s …
David's user avatar
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1 vote
Accepted

Number of Regressors in a Regression

It is possible. There is no theoretical limit to how many regressors you can use in your model, as long as it stays below the number of observations. Nevertheless, if the number of variables gets clo …
David's user avatar
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-3 votes

Should one drop independent variables if they don't have linear relationship with the respon...

In principle, yes! If there is not a linear relationship between your predictor and your target, then there is no point in including your predictor into the model, as it will be one more parameter to …
David's user avatar
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0 votes
Accepted

Help in Binary logistic regression

First, a quick remark: plese stop using the buzz-word "big data" with $n= 168615$ I don't know if you expect to have trillions of patients in the future, but for now, this does not look like a big dat …
David's user avatar
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0 votes

What regression model should I use for this problem?

For what I've seen in the description, your problem is one of classification rather than regression. A logistic model is often appropriate unless there is some reason to suspect otherwise. The main r …
David's user avatar
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0 votes
Accepted

Modelling non event instead of event

Yes, you can choose the class that you prefer as "default" with the only consequence of zeros becoming ones and vice-versa. However, I don't see the advantage of having 1 non-default rather than 1 d …
David's user avatar
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1 vote

How to interpret regression function with categorical variable?

The category variable coefficients indicate how much your prediction is incremented if a given individual belongs to the corresponding category. What strikes me is that you have two different coeffic …
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