Calculate non linear regression models.

Calculates non linear regression models by performing an iterative grid search within the coordinate bounds provided by lower and upper vectors, starting at start_lower and start_upper. Intermediate models are scored by the AIC value until convergence has been achieved as to the defaults of nls.multstart.

flip(
  projectDir = getwd(),
  plotFormat = "png",
  filePattern = "*_fip.tsv",
  dataPlots = TRUE,
  minPrecursorCollisionEnergy = 0,
  start_lower,
  start_upper,
  lower,
  upper,
  trainModel = FALSE,
  minDataPoints = 0,
  max_iter = 500
)

Arguments

projectDir	the path to the project directory containing the '_fip.tsv' files as input.
plotFormat	the plot format, as supported by ggplot2::ggsave.
filePattern	the file pattern for 'fip' files.
dataPlots	whether data plots (diagnostics) should be created.
minPrecursorCollisionEnergy	the minimum precursor collision energy to consider for model training.
start_lower	the lower bound to start the parameter grid search, argument is passed to nls_multstart.
start_upper	the upper bound to start the parameter grid search, argument is passed to nls_multstart.
lower	the lower bound for the parameter estimates, argument is passed to nlsLM.
upper	the upper bound for the parameter estimates, argument is passed to nlsLM.
trainModel	whether the model should be calculated.
minDataPoints	the minimum number of data points required per fragment / adduct / ppm combination to be considered for model calculation.
max_iter	the number of combinations for grid expansion starting parameters.

Value

The list of fit tables which includes in named element name the input file name for the model data, in named element fits a list with the named elements fits (nonlinear fits), params (parameters), CI (confidence intervals for params), preds (immediate predictions), nls.tibble.unfiltered (unfiltered input data), nls.tibble (data for calculation of fits), and preds_from_data (predictions from equidistantly resampled x-value range).