deconvolve function

Deconvolves Thermogravimetric Data

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.

Returns

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

Examples

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,
                     height_2 = 0.006, skew_2 = -0.15, position_2 = 320, width_2 = 30,
                     height_3 = 0.001, skew_3 = -0.15, position_3 = 390, width_3 = 200)
output <- deconvolve(tmp, n_peaks = 3, start_vec = my_starting_vec)