ggplot2 scatter plot regression line with function

When creating a ggplot2 scatter plot, you may want to add a regression line to visualize the relationship between two continuous variables. One way to do this is by using the `geom_smooth` function, which allows you to fit a linear model and display the result as a regression line.

The `ggplot2` package provides several options for customizing the appearance of your scatter plot. For instance, you can use the `color` aesthetic to change the color of the points, or the `size` aesthetic to adjust the size of the points. You can also use the `alpha` aesthetic to adjust the transparency of the points.

In addition to these aesthetics, you can also use the `geom_smooth` function to add a regression line to your scatter plot. This function takes several arguments, including `method`, which specifies the type of regression model to fit (e.g., linear, quadratic, etc.). You can also specify the `se` argument to include confidence intervals around the regression line.

Here's an example of how you might use the `geom_smooth` function to add a regression line to a ggplot2 scatter plot:

```R

ggplot(mtcars, aes(x = wt, y = mpg)) +

geom_point() +

geom_smooth(method = 'lm', se = FALSE)

```

In this example, we're using the `mtcars` dataset and creating a scatter plot of weight (wt) versus miles per gallon (mpg). We're then adding a regression line to the plot using the `geom_smooth` function with the `method` argument set to 'lm' (linear model).

The `geom_smooth` function also allows you to specify a custom function for calculating the regression line. This can be useful if you want to create a more complex regression model or use a different type of regression algorithm.

For example, here's how you might use a custom function to fit a non-linear regression model:

```R

ggplot(mtcars, aes(x = wt, y = mpg)) +

geom_point() +

geom_smooth(method = function(d) lm(mpg ~ poly(wt, 2), data = d))

```

In this example, we're using the `poly` function to create a polynomial regression model with degree 2. We're then passing this custom function to the `geom_smooth` function.

Overall, the `ggplot2` package provides a wide range of options for customizing the appearance and behavior of your scatter plots. By combining these options with the `geom_smooth` function, you can create powerful and informative visualizations that help you explore complex data sets.

Ggplot2 scatter plot regression line with function