| nlme_gastempt | R Documentation |
Compute coefficients v0, tempt and kappa of a mixed model fit to a linexp function with one grouping variable
nlme_gastempt(d, pnlsTol = 0.001, model = linexp, variant = 1)
d |
A data frame with columns
|
pnlsTol |
The value of pnlsTol at the initial iteration.
See |
model |
|
variant |
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
kappa Parameter kappa for
model = linexp
beta Parameter beta for 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.
suppressWarnings(RNGversion("3.5.0"))
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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