This is where a close reading of the documentation is essential.

```
help(lm.circular)
```

will give you the function signature and, importantly a description of the *results* object.

In the example

```
library(circular)
#>
#> Attaching package: 'circular'
#> The following objects are masked from 'package:stats':
#>
#> sd, var
x <- circular(runif(50, 0, 2*pi))
y <- atan2(0.15*cos(x) + 0.25*sin(x), 0.35*sin(x)) +
rvonmises(n=50, mu=circular(0), kappa=5)
circ.lm <- lm.circular(y, x, order=1)
# Fitted values
circ.lm$fitted
#> Circular Data:
#> Type = angles
#> Units = radians
#> Template = none
#> Modulo = asis
#> Zero = 0
#> Rotation = counter
#> 1 2 3 4 5 6
#> 3.584805191 5.036839325 3.827759844 1.860183750 1.012927134 0.623191891
#> 7 8 9 10 11 12
#> 0.684865489 2.173393246 1.463051394 5.831505475 1.034205699 5.112500596
#> 13 14 15 16 17 18
#> 4.246131160 3.750375687 2.443336747 3.573768858 1.044550019 0.966170053
#> 19 20 21 22 23 24
#> 0.006255199 0.716375074 5.111807016 3.671379396 1.690398526 5.716296738
#> 25 26 27 28 29 30
#> 4.883451500 5.010154295 4.687624648 4.196460592 2.531515232 3.701005477
#> 31 32 33 34 35 36
#> 0.867358506 0.692228271 1.445646671 5.242795991 5.073564066 3.408020213
#> 37 38 39 40 41 42
#> 5.921077493 5.675459227 6.249241839 2.061586508 4.062892956 0.333189224
#> 43 44 45 46 47 48
#> 4.413920236 1.301929594 3.643252066 5.071906724 0.128641440 2.200886117
#> 49 50
#> 4.520979456 4.885870701
# Residuals
circ.lm$residual
#> Circular Data:
#> Type = angles
#> Units = radians
#> Template = none
#> Modulo = asis
#> Zero = 0
#> Rotation = counter
#> 1 2 3 4 5 6
#> 0.264099077 0.045419128 0.007534907 5.650239152 5.831479349 0.886496312
#> 7 8 9 10 11 12
#> 6.218350599 0.473989862 0.589954179 0.222075881 5.623060335 1.027383327
#> 13 14 15 16 17 18
#> 0.145849820 0.106816333 5.515730408 6.250560505 0.536877341 5.812140644
#> 19 20 21 22 23 24
#> 0.405705429 5.541883729 6.221256118 0.364964105 5.362169950 0.512980044
#> 25 26 27 28 29 30
#> 5.979569932 6.123198428 5.955293469 0.249679836 0.437242471 0.073642262
#> 31 32 33 34 35 36
#> 6.214767619 5.243128299 0.107702241 0.580270656 5.577650810 0.581707762
#> 37 38 39 40 41 42
#> 0.449103551 5.920531055 5.752178725 5.780390855 0.430300811 5.951595177
#> 43 44 45 46 47 48
#> 0.052553097 0.322211203 0.081596574 0.268359964 6.188204993 1.176300684
#> 49 50
#> 5.807317576 5.727102545
# Coefficients
circ.lm$coefficients
#> [,1] [,2]
#> (Intercept) 0.1289833 -0.1553619
#> cos.x -0.1693289 0.6632196
#> sin.x 0.9156365 0.5102716
# p-values
circ.lm$p.values
#> [,1] [,2]
#> [1,] 0.8314844 0.02521169
```

^{Created on 2019-02-27 by the reprex package (v0.2.1)}

You have everything you need (intercept and data to calculate slope).

`plot.default`

is a base function that produces the points and has options to add lines.