This function deconvolves thermogravimetric data using a Fraser-Suzuki mixture model

deconvolve(process_object, lower_temp = 120, upper_temp = 700, seed = 1,
  n_peaks = NULL, start_vec = NULL, lower_vec = NULL, upper_vec = NULL)

Arguments

process_object

process object obtained from process function

lower_temp

lower temperature bound to crop dataset, default to 120

upper_temp

upper temperature bound to crop dataset, default to 700

seed

random seed for nloptr optimiser

n_peaks

number of curves optional specification

start_vec

vector of starting values for nls function. Only specify this vector if you have selected the number of curves in the n_peaks parameter.

lower_vec

vector of lower bound values for nls. Only specify this vector if you have selected the number of curves in the n_peaks parameter.

upper_vec

vector of upper bound values for nls. Only specify this vector if you have selected the number of curves in the n_peaks parameter.

Value

decon list containing amended dataframe, temperature bounds, minpack.lm model fit, the number of curves fit, and estimated component weights

Examples

# NOT RUN {
data(juncus)
tmp <- process(juncus, init_mass = 18.96,
               temp = 'temp_C', mass_loss = 'mass_loss')
output <- deconvolve(tmp)
my_starting_vec <- c(height_1 = 0.003, skew_1 = -0.15, position_1 = 250, width_1 = 50,
output <- deconvolve(tmp, n_peaks = 3, start_vec = my_starting_vec)
# }