# How to save Objects/Data in Julia?

How can one save objects in Julia? One easy way to do so it to use the JLD package. The following examples demonstrates how to save data objects in Julia and how to load the once they are saved. Continue reading How to save Objects/Data in Julia?

# How to set a Seed in Julia?

In Julia, you can set a seed to the random number generator using the srand() function. The code example below sets the seed to 1234. Generating a random variable with rand(1) after setting the seed to 1234 will always generate the same number, i.e. it will always return 0.5908446386657102. Continue reading How to set a Seed in Julia?

# Upgrade Debian 8 to 9

In this post I am going to explain how to upgrade Debian 8 to Debian 9. You can enter the following eight steps in your terminal: Continue reading Upgrade Debian 8 to 9

# Linear Regression in STATA

In STATA one can estimate a linear regression using the command  regress. In this post I will present how to use the STATA function regress to run OLS on the following model

$y = \alpha + \beta_{1} x_{1}$

# Cluster Robust Standard Errors in Stargazer

In a previous post, we discussed how to obtain clustered standard errors in R. While the previous post described how one can easily calculate cluster robust standard errors in R, this post shows how one can include cluster robust standard errors in stargazer and create nice tables including clustered standard errors.

# Robust Standard Errors in Stargazer

In a previous post, we discussed how to obtain robust standard errors in R. While the previous post described how one can easily calculate robust standard errors in R, this post shows how one can include robust standard errors in stargazer and create nice tables including robust standard errors.

# Multiple Regression in Julia

Julia presents various ways to carry out multiple regressions. One easy way is to use the lm() function of the GLM package. In this post I will present how to use the lm() and run OLS on the following model

$y = \alpha + \beta_{1} x_{1} + \beta_{2} x_{2} + \beta_{3} x_{3}$