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 | process object obtained from process function |
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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. |
decon list containing amended dataframe, temperature bounds, minpack.lm model fit, the number of curves fit, and estimated component weights
# 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) # }