Nothing
# Define trust indicator values
trust_indicators <- list(
r = 'reliable',
u_inf = 'unreliable (infinite upper limit)',
u_never = 'unreliable (process never limiting)',
u_over = 'unreliable (insufficient DOF)'
)
# Determine a trust indicator for a parameter estimate
trust_value <- function(
unreliable_npts, # TRUE means that the corresponding process is never limiting at any point in the curve
unreliable_inf, # TRUE means that the upper confidence limit for the parameter is infinity
dof # non-positive value means that the fit was overparameterized
)
{
if (dof < 1.0) {
trust_indicators[['u_over']]
} else if (unreliable_npts) {
trust_indicators[['u_never']]
} else if (unreliable_inf) {
trust_indicators[['u_inf']]
} else {
trust_indicators[['r']]
}
}
# Decide whether to remove the estimated parameter value
remove_estimate <- function(trust, param_types_to_remove) {
if (trust %in% param_types_to_remove) {
TRUE
} else {
FALSE
}
}
# Check and/or convert the user input
convert_param_setting <- function(remove_unreliable_param) {
if (identical(remove_unreliable_param, 0)) {
c()
} else if (identical(remove_unreliable_param, 1)) {
c(
trust_indicators[['u_never']],
trust_indicators[['u_over']]
)
} else if (identical(remove_unreliable_param, 2)) {
c(
trust_indicators[['u_inf']],
trust_indicators[['u_never']],
trust_indicators[['u_over']]
)
} else {
type_okay <- sapply(remove_unreliable_param, function(param_type) {
param_type %in% as.character(trust_indicators)
})
if (any(!type_okay)) {
stop(
'If `remove_unreliable_param` is not 0, 1, or 2, its elements ',
'must each be one of the following: ',
paste0('`', as.character(trust_indicators), '`', collapse = ', '),
call. = FALSE
)
}
remove_unreliable_param
}
}
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