Fit gastric emptying curves with Stan
stan_gastempt( d, model_name = "linexp_gastro_2b", lkj = 2, student_df = 5L, init_r = 0.2, chains = 1, iter = 2000, ... )
d  A data frame with columns


model_name  Name of predefined model in

lkj  LKJ prior for kappa/tempt correlation, only required for model linexp_gastro_2b. Values from 1.5 (strong correlation) to 50 (almost independent) are useful. 
student_df  Studentt degrees of freedom for residual error; default 5. Use 3 for strong outliers; values above 10 are close to gaussian residual distribution. 
init_r  for stan, default = 0.2; Stan's own default is 2, which often results in stuck chains. 
chains  for stan; default = 1 
iter  A positive integer specifying the number of iterations for each chain (including warmup). The default is 2000. 
...  Additional parameter passed to 
A list of class stan_gastempt with elements coef, fit, plot
coef
is a data frame with columns:
rec
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
Halftime of emptying
slope_t50
Slope in t50; typically in units of ml/minute
On error, coef
is NULL
fit
Result of class `stanfit`
plot
A ggplot graph of data and prediction. Plot of raw data is
returned even when convergence was not achieved.
# \donttest{ # Runs 30+ seconds on CRAN dd = simulate_gastempt(n_records = 6, seed = 471) d = dd$data ret = stan_gastempt(d) print(ret$coef)#> # A tibble: 6 x 7 #> record v0 kappa tempt t50 slope_t50 auc #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 rec_01 284. 0.504 67.5 77.7 1.43 28858. #> 2 rec_02 429. 0.615 78.7 77.7 1.43 28858. #> 3 rec_03 409. 0.401 77.0 77.7 1.43 28858. #> 4 rec_04 367. 0.846 78.0 77.7 1.43 28858. #> 5 rec_05 426. 0.255 57.4 77.7 1.43 28858. #> 6 rec_06 471. 0.259 63.8 77.7 1.43 28858.# }