# ANN: RegressionTables.jl produces publication-quality regression tables

**URL:** <https://discourse.julialang.org/t/ann-regressiontables-jl-produces-publication-quality-regression-tables/7516>\
**Category:** Data\
**Tags:** announcement\
**Created:** [December 5, 2017, 4:02am UTC](https://discourse.julialang.org/t/ann-regressiontables-jl-produces-publication-quality-regression-tables/7516 "2017-12-05T04:02:37Z")\
**Posts on this page:** 1\
**Showing post:** 33

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**Author:** ![jmboehm](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jmboehm/32/2263_2.png) [@jmboehm](https://discourse.julialang.org/u/jmboehm)\
**Post date:** [January 23, 2018, 1:37am UTC](https://discourse.julialang.org/t/ann-regressiontables-jl-produces-publication-quality-regression-tables/7516/33 "2018-01-23T01:37:40Z")

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Just create a new `RegressionResultFE` with your adjusted VCov matrix, e.g.

```julia
using RegressionTables, DataFrames, FixedEffectModels, RDatasets

df = dataset("datasets", "iris")
df[:SpeciesDummy] = pool(df[:Species])

rr1 = reg(df, @model(SepalLength ~ SepalWidth , fe = SpeciesDummy))

mynewvcovmatrix = Array{Float64,2}(1,1)
mynewvcovmatrix[1,1]=1.0

myrr = RegressionResultFE(rr1.coef, mynewvcovmatrix, rr1.esample, rr1.augmentdf, rr1.coefnames, rr1.yname, rr1.formula, rr1.feformula, rr1.nobs, rr1.df_residual, rr1.r2, rr1.r2_a, rr1.r2_within, rr1.F, rr1.p, rr1.iterations, rr1.converged)

regtable(myrr)

```

or similarly with whatever result struct you’re using.

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