Summarise a fit as a tibble

One row per coefficient for skmle and kee fits, and one row per (target time, coefficient) for kee_td, so a coefficient curve goes straight into ggplot2 without reshaping.

Usage

# S3 method for class 'skmle'
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

# S3 method for class 'kee'
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

# S3 method for class 'kee_td'
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

Arguments

x

A fitted skmle, kee or kee_td object.

conf.int

Logical, add conf.low and conf.high columns.

conf.level

Confidence level for those columns.

...

Unused.

Value

A tibble with columns term, estimate, std.error, statistic and p.value, preceded by time for a kee_td fit, and followed by conf.low and conf.high when conf.int = TRUE.

Examples

set.seed(1)
d <- sim_async_data(n = 150)
fit <- kee_async(d$y, d$x, y ~ x, id = id, time = time, h = 0.3)
tidy(fit, conf.int = TRUE)
#> # A tibble: 2 × 7
#>   term        estimate std.error statistic  p.value conf.low conf.high
#>   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
#> 1 (Intercept)    0.627    0.0972      6.45 1.13e-10    0.436     0.817
#> 2 x              1.41     0.1000     14.1  2.17e-45    1.22      1.61