# Proof Gauss Markov Theorem

From a previous posts on the Gauss Markov Theorem and OLS we know that the assumption of unbiasedness must full fill the following condition Continue reading Proof Gauss Markov Theorem

# CLRM – Assumption 2: Full Rank of Matrix X

Assumption 2 requires the matrix of explanatory variables $X$ to have full rank. This means that in case matrix $X$ is a $N \times K$ matrix the rank of matrix $X$ is $K$. Namely, $Rank(X) = K$

# How to Enable Gui Root Login in Debian 8

In this post I am going to explain how to enable GUI root access on Debian 8. Instructions for Debian 9 a similar and can be found here. At this point I should warn you that using the root account is dangerous as you can ruin your whole system.  Try to follow this guide exactly.

# CLRM – Assumption 1: Linear Parameter and correct model specification

Assumption 1 requires that the dependent variable $\textbf{y}$ is a linear combination of the explanatory variables $\textbf{X}$ and the error terms $\epsilon$. Assumption 1 requires the specified model to be linear in parameters, but it does not require the model to be linear in variables. Equation 1 and 2 depict a model which is both, linear in parameter and variables. Note that Equation 1 and 2 show the same model in different notation.