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Nov 10, 2021
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Use markdown list to show arguments #46

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16 changes: 8 additions & 8 deletions src/Loess.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -23,12 +23,12 @@ end
Fit a loess model.

Args:
`xs`: A `n` by `m` matrix with `n` observations from `m` independent predictors
`ys`: A length `n` response vector.
`normalize`: Normalize the scale of each predicitor. (default true when `m > 1`)
`span`: The degree of smoothing, typically in [0,1]. Smaller values result in smaller
- `xs`: A `n` by `m` matrix with `n` observations from `m` independent predictors
- `ys`: A length `n` response vector.
- `normalize`: Normalize the scale of each predicitor. (default true when `m > 1`)
- `span`: The degree of smoothing, typically in [0,1]. Smaller values result in smaller
local context in fitting.
`degree`: Polynomial degree.
- `degree`: Polynomial degree.

Returns:
A fit `LoessModel`.
Expand Down Expand Up @@ -189,7 +189,7 @@ end
Tricubic weight function.

Args:
`u`: Distance between 0 and 1
- `u`: Distance between 0 and 1

Returns:
A weighting of the distance `u`
Expand Down Expand Up @@ -231,8 +231,8 @@ Default normalization procedure for predictors.
This simply normalizes by the mean of everything between the 10th an 90th percentiles.

Args:
`xs`: a matrix of predictors
`q`: cut the ends of at quantiles `q` and `1-q`
- `xs`: a matrix of predictors
- `q`: cut the ends of at quantiles `q` and `1-q`

Modifies:
`xs`
Expand Down