# Data Transformation in predmicror

## Consistent Use of Natural Logarithm

In previous versions of `predmicror`, there was an inconsistency in the required data transformation for different models. Some models required the data to be in natural logarithm (`ln`) scale, while others required it to be in base-10 logarithm (`log10`) scale. This could lead to confusion and errors.

To address this issue, all models in `predmicror` have been harmonized to use the natural logarithm (`ln`) for the response variable `Y(t)`.

This means that users should always provide the microbial concentration in `ln` scale.

### Converting from `log10` to `ln`

If your data is in `log10` scale, you can easily convert it to `ln` scale using the following formula:

`ln(N) = log(10) * log10(N)`

Here is an example of how to convert a column in a data frame:

    # Create a sample data frame with log10 data
    my_data <- data.frame(
      Time = c(0, 1, 2, 3),
      log10N = c(2, 2.5, 3, 3.5)
    )

    # Convert the log10N column to lnN
    my_data$lnN <- log(10) * my_data$log10N

    # Print the updated data frame
    print(my_data)
    #>   Time log10N      lnN
    #> 1    0    2.0 4.605170
    #> 2    1    2.5 5.756463
    #> 3    2    3.0 6.907755
    #> 4    3    3.5 8.059048

By ensuring that all models use a consistent `ln` scale, `predmicror` is now more user-friendly and less prone to errors.