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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

1 vote
0 answers
54 views

Decomposing R^2 into independent variables

Consider a linear regression model: $$y = β_0 + β_1X_1 + β_2X_2 + ... + β_kX_k + ε$$ where $R^2 = 1 - (SSR/SST)$. …
JungleDiff's user avatar
0 votes
1 answer
183 views

Decomposing R squared or VIF

In the context of multi-regression, I am wondering if there is a way to decompose $$VIF_i = 1/(1-R_i^2)$$ where $R_i^2$ is the r squared obtained from the regression of dependent variable = i and independent …
JungleDiff's user avatar
1 vote
2 answers
96 views

Reducing the dependency between variables

I am trying to perform a multi linear regression model: $$y_i = β_0 + β_1x_{i1} + β_2x_{i2} +... + β_px_{ip} + ε_i$$ where $$x_{i1}, x_{i2}, ..., x_{ip}$$ are highly correlated with each other (VIFs …
JungleDiff's user avatar
0 votes
2 answers
45 views

Influence of a data point on the regression result?

Let's say I perform multiple regression where y = income, x1 = educaiton, x2 = sex, and x3 = religion from 2003 to 2018, where the data is measured daily. … Is there any way to quantify an impact of a single day data (e.x. 2005-07-01) on the regression result? …
JungleDiff's user avatar
2 votes
1 answer
1k views

How to choose variables for regression

I need to form multiple regression on the fund returns using the benchmarks returns as independent variables (i am allowed to form linear combination or manipulation of the indices or even non-linear combinations …
JungleDiff's user avatar