force_find_lambdaz: Forceful estimation of terminal slope

Description

Estimates the terminal elimination rate constant (lambda_z) of a pharmacokinetic profile. The function first attempts to use the find_best_lambdaz method. If no valid estimate is obtained, it falls back to a simplified log-linear regression using progressively fewer data points to enforce a negative slope.

Usage

force_find_lambdaz(time, conc, ...)

Value

A list containing:

lambdaz: Estimated terminal elimination rate constant (1/time)
intercept: Intercept of the log-linear regression, used to extrapolate concentration at time zero
method: Method used (find_best_lambdaz or fallback regression)
UsedPoints: Number of time-concentration points used for estimation
adj.r.squared: Adjusted R-squared (available only when using find_best_lambdaz)
message: Diagnostic message summarizing the outcome
slopefit: Fitted linear model object

Arguments

time: Numeric vector of time points.
conc: Numeric vector of concentration values corresponding to time.
...: Additional arguments passed to find_best_lambdaz (e.g., nlastpoints).

Author

Zhonghui Huang

Details

This function implements a two-step strategy to ensure estimation of the terminal elimination slope:

First, it applies find_best_lambdaz to automatically select the best fitting terminal phase segment based on adjusted R-squared optimization.
If find_best_lambdaz fails (e.g., limited data), the function forcibly fits simplified linear models using progressively fewer points (starting from n-1 down to 2) until a negative slope is identified. In fallback mode, adjusted R-squared is not considered.

Examples

Run this code

time <- c(0.5, 1, 2, 4, 6, 8, 10)
conc <- c(12, 8, 5, 3, 2, 1.5, 1)
force_find_lambdaz(time, conc)

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