Hi,

how can I do an error in variables regression in Julia? I didn‘t find anything online about this and I don‘t know what to do with the measurement uncertainties when I want to fit my model.

Have a nice day and thank you for all replies.

Hi,

how can I do an error in variables regression in Julia? I didn‘t find anything online about this and I don‘t know what to do with the measurement uncertainties when I want to fit my model.

Have a nice day and thank you for all replies.

1 Like

You could use

https://github.com/baggepinnen/TotalLeastSquares.jl

but it’s a rather low-level interface

1 Like

I haven’t registered in the Julia package registry, but it is quite ready to use. It implements a specific estimator/algorithm (mainly compact genetic algorithm optimization based).

Here is the repository:

And will be registered soon. README.md file is a good start while we are generating a more comprehensive documentary. You can install it by typing

```
julia> ]
add https://github.com/jbytecode/ErrorsInVariables.jl
```

Edit:

```
julia> ]
add ErrorsInVariables
```

now works!

Sorry for asking, but is this an instrumental variable (or 2SLS) approach?

1 Like

Thanks for the question, no worries.

The package simply implements the algorithm (estimator) defined in the paper

```
@article{satman2015reducing,
title={Reducing errors-in-variables bias in linear regression using compact genetic algorithms},
author={Satman, M Hakan and Diyarbakirlioglu, Erkin},
journal={Journal of Statistical Computation and Simulation},
volume={85},
number={16},
pages={3216--3235},
year={2015},
publisher={Taylor \& Francis}
}
```

It is similar to 2SLS but the exploratory variables are automatically generated to reduce mean square error of regression estimators by reducing the bias with a smaller increase on the variance. Results are compared with the OLS counterparts by simulations.

Thanks. This means that I have to read up, but probably after my teaching period. My initial *guess* would be that IV/2SLS/the new stuff could all fit in such a package. Just to give the users some options. But, as I said, I really should read up before saying too much…

1 Like

You’re totally right. Mainly, the R package eive (CRAN - Package eive) was the reference implementation for this estimator. But Julia package naming conventions didn’t allow me to select Eive.jl as the name. So I finally ended up with `ErrorsInVariable.jl`

.

Your contributions are welcome.