isoapqmodel: S4 class to represent a nonlinear mixed effects model based...
In mstaniak/SharedPeptidesIso:

S4 class to represent a nonlinear mixed effects model based on isotopic distribution

Fit a nonlinear mixed effects model based on isotopic distribution

1	IsoAPQModel(model_formula, model_data, ...)

`model_formula`	formula that specifies the model. Special notation '..' denotes all protein variables
`model_data`	input data - data.table with columns: intensity, iso_prob or isoDistr, sequence, rep, precursor_scan, charge_in_scan and protein indicator columns.
`additional`	parameters to the model fitting function (currently stats::optim)

object of class IsoAPQModel

model_design: object of class IsoAPQModelDesign that describes experimental design reflected in the model
fitted_model_raw: usually list (output of stats::optim), potentially could be a different object with raw outputs of function used to fit a model
coef: numeric vector of model coefficient in the following order: standard deviation of the error, parameters that describe random effects, protein abundances, fixed effects
sigma: standard deviation of the random error
random_effects_var: numeric vector of estimated variances of random effects
protein_abundance: numeric vector of estimated protein abundances
fixed_effects: numeric vector of estimated fixed effects
fitted: numeric vector of fitted values
residuals: numeric vector of residuals
hessian: hessian of the negative log-likelihood
loglik: log-likelihood calculated at the solution
message: message indicating if the model converged