View source: R/PulseWaveform.R
model2.ChiSq4 | R Documentation |
model2.ChiSq4 is a clone of model2.ChiSq3. It differs by providing additional measures of goodness of fit besides reduced ChiSq for the inputted batch. These are listed below.
model2.ChiSq4(data, params, debug=FALSE, beats, beat, a = NULL, plot = FALSE, renal_param, dias_param, sys_time, w)
data |
section of ppg time series |
params |
model parameters |
debug |
logical, currently redundant |
beats |
list of number of inputted beats, there beginnings in the time series, and their endings |
beat |
dataframe of model parameters |
a |
the combined matrix used in the downhill simplex routine (alternative source of parameters) |
plot |
logical, if set to true plots model generated waveform against original waveform |
renal_param |
the starting parameter for 1st reflectance peak timing (inputted to prevent drastic deviations from this value) |
dias_param |
the starting parameter for 2nd reflectance peak timing (inputted to prevent drastic deviations from this value) |
sys_time |
the starting parameter for systolic peak timing (inputted to prevent drastic deviations from this value) |
w |
the timing of the 1st derivative peaks on the ppg time series |
fit |
list consisting of: |
ts_fit |
total reduced ChiSq value summed across all beats inputted |
beat_fit |
list of reduced ChiSq values for each individual beat |
max_error |
residual of greatest value for each individual beat |
NRMSE |
Normalised root mean square error (see supplementary material) |
aNRMSE |
alternative normalised root mean square error (see supplementary material) |
fit_check[[k]] <- model2.ChiSq4(data = ppg, params = NULL, beats = beat_vector, beat = new_beat, a = sim[1, ], plot = FALSE, renal_param = renal_param, dias_param = dias_param, sys_time = sys_time, w = w)
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