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  1. Does every variable need to be statistically significant in a ...

    Oct 18, 2024 · I recently fit a regression model (ARIMAX) in which some variables (3) were statistically significant and some were not (1). I removed the statistically insignificant variables …

  2. Support Vector Regression vs. Linear Regression - Cross Validated

    Dec 5, 2023 · Linear regression can use the same kernels used in SVR, and SVR can also use the linear kernel. Given only the coefficients from such models, it would be impossible to …

  3. regression - Why do we say the outcome variable "is regressed …

    Apr 15, 2016 · The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x …

  4. regression - When is R squared negative? - Cross Validated

    Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is …

  5. How to describe or visualize a multiple linear regression model

    Then this simplified version can be visually shown as a simple regression as this: I'm confused on this in spite of going through appropriate material on this topic. Can someone please explain to …

  6. correlation - What is the difference between linear regression on y ...

    The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be …

  7. What is the lasso in regression analysis? - Cross Validated

    Oct 19, 2011 · LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously. This method uses a penalty which affects they value …

  8. What is the relationship between R-squared and p-value in a …

    Context - I'm performing OLS regression on a range of variables and am trying to develop the best explanatory functional form by producing a table containing the R-squared values …

  9. Simple linear regression output interpretation - Cross Validated

    I have run a simple linear regression of the natural log of 2 variables to determine if they correlate. My output is this: R^2 = 0.0893 slope = 0.851 p < 0.001 I am confused. Looking at the $...

  10. When conducting multiple regression, when should you center …

    Jun 5, 2012 · In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean …