This function wraps the custom approach for fitting distributions to doubly censored data using fitdistrplus and primarycensored.
Arguments
- censdata
A data frame with columns 'left' and 'right' representing the lower and upper bounds of the censored observations. Unlike
fitdistrplus::fitdistcens()
NA
is not supported for either the upper or lower bounds.- distr
A character string naming the distribution to be fitted.
- pwindow
Primary event window
- D
Maximum delay (truncation point). If finite, the distribution is truncated at D. If set to Inf, no truncation is applied. Defaults to Inf.
- dprimary
Function to generate the probability density function (PDF) of primary event times. This function should take a value
x
and apwindow
parameter, and return a probability density. It should be normalized to integrate to 1 over [0, pwindow]. Defaults to a uniform distribution over [0, pwindow]. Users can provide custom functions or use helper functions likedexpgrowth
for an exponential growth distribution. Seeprimary_dists.R
for examples.- dprimary_name
A string specifying the name of the primary event distribution function. If NULL, the function name is extracted using
.extract_function_name()
. Used to determine if a analytical solution exists for the primary censored distribution. Must be set ifdprimary
is passed a pre-assigned variable rather than a function name.- dprimary_args
List of additional arguments to be passed to dprimary. For example, when using
dexpgrowth
, you would passlist(min = 0, max = pwindow, r = 0.2)
to set the minimum, maximum, and rate parameters- truncation_check_multiplier
Numeric multiplier to use for checking if the truncation time D is appropriate relative to the maximum delay. Set to NULL to skip the check. Default is 2.
- ...
Additional arguments to be passed to
fitdistrplus::fitdist()
.
Details
This function temporarily assigns and then removes functions from the global environment in order to work with fitdistr. Users should be aware of this behaviour, especially if they have existing functions with the same names in their global environment.
See also
Modelling wrappers for external fitting packages
pcd_as_stan_data()
,
pcd_cmdstan_model()
Examples
# Example with normal distribution
set.seed(123)
n <- 1000
true_mean <- 5
true_sd <- 2
pwindow <- 2
swindow <- 2
D <- 10
samples <- rprimarycensored(
n, rnorm,
mean = true_mean, sd = true_sd,
pwindow = pwindow, swindow = swindow, D = D
)
delay_data <- data.frame(
left = samples,
right = samples + swindow
)
fit_norm <- fitdistdoublecens(
delay_data,
distr = "norm",
start = list(mean = 0, sd = 1),
D = D, pwindow = pwindow
)
summary(fit_norm)
#> Fitting of the distribution ' pcens_dist ' by maximum likelihood
#> Parameters :
#> estimate Std. Error
#> mean 5.007126 0.07883554
#> sd 2.020160 0.06962184
#> Loglikelihood: -1398.874 AIC: 2801.747 BIC: 2811.563
#> Correlation matrix:
#> mean sd
#> mean 1.0000000 0.3248076
#> sd 0.3248076 1.0000000
#>