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56 changes: 56 additions & 0 deletions docs/src/examples.md
Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,62 @@ julia> round.(predict(ols), digits=5)
6.83333
```

### Without data as a DataFrame
Because a named tuple follows common table-interface defined in `Tables.jl`
(which is the one followed by a DataFrame), the problem can also be specified
with data in a named tuple as opposed to a `DataFrame`:
```jldoctetst
julia> using GLM

julia> X=[1,2,3]
3-element Vector{Int64}:
1
2
3

julia> Y=[2,4,7]
3-element Vector{Int64}:
2
4
7

julia> data = (;X, Y) # Equivalent to (X=X, Y=Y)
(X = [1, 2, 3], Y = [2, 4, 7])

julia> lm(@formula(Y~X), data)
StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Vector{Float64}}, GLM.DensePredChol{Float64, LinearAlgebra.CholeskyPivoted{Float64, Matrix{Float64}}}}, Matrix{Float64}}

Y ~ 1 + X

Coefficients:
─────────────────────────────────────────────────────────────────────────
Coef. Std. Error t Pr(>|t|) Lower 95% Upper 95%
─────────────────────────────────────────────────────────────────────────
(Intercept) -0.666667 0.62361 -1.07 0.4788 -8.59038 7.25704
X 2.5 0.288675 8.66 0.0732 -1.16797 6.16797
─────────────────────────────────────────────────────────────────────────
```

### Without intercept
To make a fit without an intercept (Going through `(0, 0)`), one can specify the fomula as follows:
```jldoctest
julia> X=[1,2,3]; Y=[2,4,7]; data = (;X, Y)
(X = [1, 2, 3], Y = [2, 4, 7])

julia> lm(@formula(Y~0+X), data)
StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Vector{Float64}}, GLM.DensePredChol{Float64, LinearAlgebra.CholeskyPivoted{Float64, Matrix{Float64}}}}, Matrix{Float64}}

Y ~ 0 + X

Coefficients:
─────────────────────────────────────────────────────────────
Coef. Std. Error t Pr(>|t|) Lower 95% Upper 95%
─────────────────────────────────────────────────────────────
X 2.21429 0.112938 19.61 0.0026 1.72835 2.70022
─────────────────────────────────────────────────────────────
```
To read more about the `@formula` syntax, check out [the documentation for `@formula`](https://juliastats.org/StatsModels.jl/stable/formula/#The-@formula-language)

## Probit regression
```jldoctest
julia> data = DataFrame(X=[1,2,2], Y=[1,0,1])
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