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
)
process object obtained from process function
lower temperature bound to crop dataset, default to 120
upper temperature bound to crop dataset, default to 700
random seed for nloptr optimiser
number of curves optional specification
vector of starting values for nls function. Only specify this vector if you have selected the number of curves in the n_peaks parameter.
vector of lower bound values for nls. Only specify this vector if you have selected the number of curves in the n_peaks parameter.
vector of upper bound values for nls. Only specify this vector if you have selected the number of curves in the n_peaks parameter.
decon list containing amended dataframe, temperature bounds, minpack.lm model fit, the number of curves fit, and estimated component weights
# \donttest{
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)
# }