tef_control | R Documentation |
TEfit
internal
tef_control(
quietErrs = F,
suppressWarnings = F,
nTries = 200,
y_lim = c(-1e+07, 1e+07),
rate_lim = c(0, 0),
shape_lim = c(0, 0),
expBase = 2,
rateBase = 2,
pFix = c(),
penalizeMean = T,
penalizeRate = F,
convergeTol = 0.05,
stepwise_asym = F,
explicit = ""
)
quietErrs |
logical. Should errors be printed to the Console? |
suppressWarnings |
logical. Should warnings be printed to the Console? |
nTries |
Numeric. What is the maximum number of optimization runs that should be attempted? |
y_lim |
Numeric vector of length 2. Lower and upper bounds of permitted predicted values. |
rate_lim |
Numeric vector of length 2. Lower and upper bounds of permitted rate values [log time constants]. |
shape_lim |
Numeric vector of length 2. Lower and upper bounds of permitted shape parameter values (i.e., for Weibull). |
expBase |
For change functions with an exponential component, what should the base of the exponent be? |
rateBase |
What should the base of the rate exponent be? |
pFix |
Named numeric vector allowing specific parameters to be fixed to a constant (i.e., not estimated) |
penalizeMean |
Logical. Should the time-evolving model be penalized if the mean of the time-evolving predicted values diverges from the mean of the null [non-time-evolving] predicted values? |
penalizeRate |
Logical. Should the time-evolving model be penalized if the rate parameter is very near a boundary? |
convergeTol |
Convergence is extremely roughly defined in |
stepwise_asym |
Logical. If a function will saturate by the end of the measurement time, this option allows the asymptote to be estimated from this time period (i.e., as stationary). |
explicit |
Character. Rather than using any of the pre-defined change or link functions, enter the specific function you want to test. |
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