R: Examples for 'broom::tidy.nls'

### ** Examples


# fit model
n <- nls(mpg ~ k * e^wt, data = mtcars, start = list(k = 1, e = 2))

# summarize model fit with tidiers + visualization
tidy(n)

# A tibble: 2 × 5
  term  estimate std.error statistic  p.value
  <chr>    <dbl>     <dbl>     <dbl>    <dbl>
1 k       49.7      3.79        13.1 5.96e-14
2 e        0.746    0.0199      37.5 8.86e-27

augment(n)

# A tibble: 32 × 4
     mpg    wt .fitted .resid
   <dbl> <dbl>   <dbl>  <dbl>
 1  21    2.62    23.0 -2.01 
 2  21    2.88    21.4 -0.352
 3  22.8  2.32    25.1 -2.33 
 4  21.4  3.22    19.3  2.08 
 5  18.7  3.44    18.1  0.611
 6  18.1  3.46    18.0  0.117
 7  14.3  3.57    17.4 -3.11 
 8  24.4  3.19    19.5  4.93 
 9  22.8  3.15    19.7  3.10 
10  19.2  3.44    18.1  1.11 
# … with 22 more rows

glance(n)

# A tibble: 1 × 9
  sigma isConv     finTol logLik   AIC   BIC deviance df.residual  nobs
  <dbl> <lgl>       <dbl>  <dbl> <dbl> <dbl>    <dbl>       <int> <int>
1  2.67 TRUE   0.00000204  -75.8  158.  162.     214.          30    32

library(ggplot2)

ggplot(augment(n), aes(wt, mpg)) +
  geom_point() +
  geom_line(aes(y = .fitted))

newdata <- head(mtcars)
newdata$wt <- newdata$wt + 1

augment(n, newdata = newdata)

# A tibble: 6 × 13
  .rownames      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
  <chr>        <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Mazda RX4     21       6   160   110  3.9   3.62  16.5     0     1     4     4
2 Mazda RX4 W…  21       6   160   110  3.9   3.88  17.0     0     1     4     4
3 Datsun 710    22.8     4   108    93  3.85  3.32  18.6     1     1     4     1
4 Hornet 4 Dr…  21.4     6   258   110  3.08  4.22  19.4     1     0     3     1
5 Hornet Spor…  18.7     8   360   175  3.15  4.44  17.0     0     0     3     2
6 Valiant       18.1     6   225   105  2.76  4.46  20.2     1     0     3     1
# … with 1 more variable: .fitted <dbl>

Examples for 'broom::tidy.nls'

Tidy a(n) nls object