This function will obtain the coefficients (and associated statistics) for each model in the mable.
library(fable)
library(tsibbledata)
olympic_running %>%
model(lm = TSLM(log(Time) ~ trend())) %>%
tidy()
#> # A tibble: 28 × 8
#> Length Sex .model term estimate std.error statistic p.value
#> <int> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 100 men lm (Intercept) 2.41 0.00813 297. 2.01e-47
#> 2 100 men lm trend() -0.00482 0.000429 -11.2 1.78e-11
#> 3 100 women lm (Intercept) 2.52 0.0143 176. 5.28e-32
#> 4 100 women lm trend() -0.00501 0.000657 -7.62 3.41e- 7
#> 5 200 men lm (Intercept) 3.11 0.00664 468. 8.18e-51
#> 6 200 men lm trend() -0.00479 0.000344 -14.0 2.66e-13
#> 7 200 women lm (Intercept) 3.24 0.0229 142. 3.21e-26
#> 8 200 women lm trend() -0.00590 0.000992 -5.94 2.07e- 5
#> 9 400 men lm (Intercept) 3.92 0.00885 443. 5.98e-52
#> 10 400 men lm trend() -0.00551 0.000467 -11.8 6.04e-12
#> # ℹ 18 more rows