Calculates best model fits for all curves based on AIC criterion. The function fits polynomial functions with 1 to 20 coefficients and uses the Akaike Information
Criterion (AIC) to evaluate the goodness of the fits. A model is considered a good fit, when the percentage of change from one model to the next (e.g. a model with
6 coefficients to a model with 7 coefficients) is, e.g. < 5% when threshold = 5. The first for models meeting this criterion are plotted as colored graphs and the AICs of these models
are visualized in a second plot for each curve. All first four coefficients per curve that fulfill the criterion are stored and in the end, a histogram of how
often which coefficients were good fits is plotted as well. The function returns the numerical value of the coefficient that fulfilled the criterion of a good fit
in most curves.
find_best_fits(
df,
degrees = 1:20,
threshold = 5,
zero_threshold = NULL,
plot.to.screen = FALSE,
path.data = NULL,
path.plots = NULL,
show.progress = FALSE
)Returns the a numerical value representing the number of coefficient that was most often under the first 4 models that were followed by an
AIC-change <= 5% by the next model. Additionally, plots showing the model fits and a histogram of the coefficients that met the 5%-criterion can be
plotted to the plot device or saved as PDFs in path.plots.
The resulting tibble of the function avg_peaks(). See below for more details.
Numerical vector of polynomial degrees to test. Cannot be infinitely high - if two high, throws error: 'degree' must be less than number of unique points.
Default: 1:20.
Percentage of AIC change compared to previous degree to fit the good-fit-criteria (s.a.). Default: 5.
Either numerical or NULL: If numerical, the function checks if the graph of the current model starts and ends near zero,
e.g. below 0.2 if zero_threshold = 0.2. Default: NULL.
A logical value indicating if results should be
plotted in the current R plot device. Default: FALSE.
A string character defining where to save the results. If NULL,
data is not stored in a file. Default: NULL.
A string character defining where to save the plots. If NULL,
plots will not be saved to PDF files. Default: NULL.
A logical value indicating if progress should be
printed to the console. Default: FALSE.
#' This function expects a tibble made of three columns as df: species containing the species names,
index numerical column, e.g. time (but can be arbitrary continuous unit), for each species,
and force.norm.100 containing the averaged and rescaled curve of each species.
# Using the forceR::peaks.df.100.avg dataset:
# find smallest polynomial degree that best describes all curves
best.fit.poly <- find_best_fits(df = forceR::peaks.df.100.avg)
best.fit.poly
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