Problems That May Occur in Time Series Multiple Regression

Multicollinearity. If one independent variable is excessively linearly correlated with another independent variable, then it will be impossible to determine their separate influences.  The problem is with the data and not with the regression model itself and will be signified three schemes: (1) a high R^2 with low values for the t statistics, (2)  high … Continue reading Problems That May Occur in Time Series Multiple Regression

What is the difference between L1 and L2 regularization?

From Quora https://www.quora.com/What-is-the-difference-between-L1-and-L2-regularization Justin Solomon has a great answer on the difference between L1 and L2 norms and the implications for regularization. ℓ1 vs ℓ2 for signal estimation: Here is what a signal that is sparse or approximately sparse i.e. that belongs to the ell-1 ball looks like. It becomes extremely unlikely that an ℓ2 penalty … Continue reading What is the difference between L1 and L2 regularization?

A Complete Tutorial on Ridge and Lasso Regression in Python

AARSHAY JAIN , JANUARY 28, 2016 / 39 Introduction When we talk about Regression, we often end up discussing Linear and Logistics Regression. But, that’s not the end. Do you know there are 7 types of Regressions ? Linear and logistic regression is just the most loved members from the family of regressions.  Last week, I saw a recorded … Continue reading A Complete Tutorial on Ridge and Lasso Regression in Python

Correlation between A, B and C

A strong correlation between A and B. Strong correlation between B and C. No correlation between A and C. Is this possible? Suppose that the correlation ρABρAB between AA and BB and the correlation ρBCρBC between BB andCC are both the same number ρρ. Then ρACρAC lies between 2ρ2−12ρ2−1 and 11, the light blue shaded … Continue reading Correlation between A, B and C