# Linear Regression in Julia 1.0

Julia presents various ways to carry out linear regressions. In this previous post, I explained how to run linear regression in Julia using the function linreg(). Unfortunately, linreg() is deprecated and no longer exists in Julia v1.0.

In this post I will present how to use the native function of Julia to run OLS on the following model

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

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# Generate Gamma Distributed Numbers in Julia

In Julia, one can generate random numbers that follow a Gamma distribution by using the Distribution package. Thereby one can use the rand() function that draws random numbers and specify the Gamma distribution by using the Gamma(a,b) command. The parameters a and b define the shape parameters of the Gamma distribution. This article provides a more generic overview of how to generate random numbers in Julia.

# 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.

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# How to set a Seed in Julia?

#### Julia v0.7 and older

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.

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# 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

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

Continue reading Multiple Regression in Julia

# Linear Regression in Julia

Unfortunately, linreg() is deprecated and no longer exists in Julia v1.0. In case you are using Julia v1.0 or above, check out this post. In case you use a version of Julia that is older than 1.0, i.e 0.7, 0.6, etc., the following post will show you how to run a linear regression in Julia.

Julia presents various ways to carry out linear regressions. In this post I will present how to use the native function linreg() to run OLS on the following model

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

# Why use Julia Language!

Julia has been around since a couple of years now and continues to attract new users. Julia Language uses concepts from well established programming languages in order to create an easy-to-use high performance software.

The official website describes Julia as

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# Mathematical Operations

What are the commands for the most important mathematical operations in Julia and R? The following table translates the most common Julia commands into R language.