Compute coefficients v0, tempt and kappa of a mixed model fit to a linexp function with one grouping variable
A data frame with columns
The value of pnlsTol at the initial iteration.
For both models, there are 3 variants
A list of class nlme_gastempt with elements
coef, summary, plot, pnlsTol, message
coef is a data frame with columns:
record Record descriptor, e.g. patient ID
v0 Initial volume at t=0
tempt Emptying time constant
model = linexp
model = powexp
t50 Half-time of emptying
slope_t50 Slope in t50; typically in units of ml/minute
On error, coef is NULL
nlme_result Result of the nlme fit; can be used for addition
processing, e.g. to plot residuals or via
summary to extract AIC.
On error, nlme_result is NULL.
plot A ggplot graph of data and prediction. Plot of raw data is
returned even when convergence was not achieved.
pnlsTol Effective value of pnlsTo after convergence or failure.
message String "Ok" on success, and the error message of
nlme on failure.
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set.seed(4711) d = simulate_gastempt(n_record = 10, kappa_mean = 0.9, kappa_std = 0.3, model = linexp)$data fit_d = nlme_gastempt(d) # fit_d$coef # direct access coef(fit_d) # better use accessor function coef(fit_d, signif = 3) # Can also set number of digits # Avoid ugly ggplot shading (not really needed...) library(ggplot2) theme_set(theme_bw() + theme(panel.spacing = grid::unit(0,"lines"))) # fit_d$plot # direct access is possible plot(fit_d) # better use accessor function
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