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minor docs
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DominiqueMakowski committed Mar 10, 2024
1 parent 8a42af7 commit df9391b
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20 changes: 10 additions & 10 deletions docs/make.jl
Original file line number Diff line number Diff line change
Expand Up @@ -4,29 +4,29 @@ using Turing
using Plots

makedocs(
warnonly = true,
sitename = "SequentialSamplingModels",
format = Documenter.HTML(
assets = [
warnonly=true,
sitename="SequentialSamplingModels",
format=Documenter.HTML(
assets=[
asset(
"https://fonts.googleapis.com/css?family=Montserrat|Source+Code+Pro&display=swap",
class = :css,
class=:css,
),
],
collapselevel = 1,
collapselevel=1,
),
modules = [
modules=[
SequentialSamplingModels,
Base.get_extension(SequentialSamplingModels, :TuringExt),
Base.get_extension(SequentialSamplingModels, :PlotsExt),
],
pages = [
pages=[
"Home" => "index.md",
"Models" => [
"Attentional Drift Diffusion (aDDM)" => "aDDM.md",
"Circular Drift Diffusion Model (CDDM)" => "cddm.md",
"Drift Diffusion Model (DDM)" => "DDM.md",
"Ex-Gaussian Distrbituion" => "ex_gaussian.md",
"Ex-Gaussian Distribution" => "ex_gaussian.md",
"Leaky Competing Accumulator (LCA)" => "lca.md",
"Linear Ballistic Accumulator (LBA)" => "lba.md",
"Lognormal Race Model (LNR)" => "lnr.md",
Expand All @@ -53,4 +53,4 @@ makedocs(
],
)

deploydocs(repo = "github.com/itsdfish/SequentialSamplingModels.jl.git")
deploydocs(repo="github.com/itsdfish/SequentialSamplingModels.jl.git")
4 changes: 2 additions & 2 deletions docs/src/ex_gaussian.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ In the code below, we will define parameters for the LBA and create a model obje

### Mean of Gaussian Component

The parameter $\mu$ represents the mean processing time of each accumulator in log space.
The parameter $\mu$ represents the mean processing time in log space.

```@example ex_gaussian
μ = .80
Expand All @@ -49,7 +49,7 @@ The parameter $\tau$ represents the mean of the exponential component.
```
### Ex-Gaussian Constructor

Now that values have been asigned to the parameters, we will pass them to `ExGaussian` to generate the model object.
Now that values have been assigned to the parameters, we will pass them to `ExGaussian` to generate the model object.

```@example ex_gaussian
dist = ExGaussian(μ, σ, τ)
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