Fit Local polynomial regression to klassets_xy object
Arguments
- df
A object from
sim_xy.- ...
Options for
stats::loess.
Examples
df <- sim_xy()
df
#> # A tibble: 500 × 2
#> x y
#> <dbl> <dbl>
#> 1 2.36 3.73
#> 2 2.43 4.47
#> 3 2.48 3.23
#> 4 2.68 4.38
#> 5 2.77 4.36
#> 6 2.85 4.17
#> 7 2.86 3.64
#> 8 2.88 3.47
#> 9 2.95 4.40
#> 10 2.99 3.60
#> # … with 490 more rows
dfloess <- fit_loess(df)
dfloess
#> # A tibble: 500 × 3
#> x y prediction
#> <dbl> <dbl> <dbl>
#> 1 2.36 3.73 3.72
#> 2 2.43 4.47 3.80
#> 3 2.48 3.23 3.85
#> 4 2.68 4.38 4.05
#> 5 2.77 4.36 4.14
#> 6 2.85 4.17 4.21
#> 7 2.86 3.64 4.22
#> 8 2.88 3.47 4.24
#> 9 2.95 4.40 4.30
#> 10 2.99 3.60 4.34
#> # … with 490 more rows
plot(dfloess)
#> Warning: Removed 9 row(s) containing missing values (geom_path).
df <- sim_xy(n = 1000, x_dist = runif)
df <- dplyr::mutate(df, y = y + 2*sin(5 * x))
plot(df)
plot(fit_loess(df))
#> Warning: Removed 2 row(s) containing missing values (geom_path).
