pprimarycensored {primarycensored} | R Documentation |
Compute the primary event censored CDF for delays
Description
This function computes the primary event censored cumulative distribution function (CDF) for a given set of quantiles. It adjusts the CDF of the primary event distribution by accounting for the delay distribution and potential truncation at a maximum delay (D). The function allows for custom primary event distributions and delay distributions.
Usage
pprimarycensored(
q,
pdist,
pwindow = 1,
D = Inf,
dprimary = stats::dunif,
dprimary_args = list(),
pdist_name = lifecycle::deprecated(),
dprimary_name = lifecycle::deprecated(),
...
)
ppcens(
q,
pdist,
pwindow = 1,
D = Inf,
dprimary = stats::dunif,
dprimary_args = list(),
pdist_name = lifecycle::deprecated(),
dprimary_name = lifecycle::deprecated(),
...
)
Arguments
q |
Vector of quantiles |
pdist |
Distribution function (CDF). The package can identify base R
distributions for potential analytical solutions. For non-base R functions,
users can apply |
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 |
dprimary_args |
List of additional arguments to be passed to
dprimary. For example, when using |
pdist_name |
|
dprimary_name |
|
... |
Additional arguments to be passed to pdist |
Details
The primary event censored CDF is computed by integrating the product of the delay distribution function (CDF) and the primary event distribution function (PDF) over the primary event window. The integration is adjusted for truncation if a finite maximum delay (D) is specified.
The primary event censored CDF, F_{\text{cens}}(q)
, is given by:
F_{\text{cens}}(q) = \int_{0}^{pwindow} F(q - p) \cdot f_{\text{primary}}(p)
\, dp
where F
is the CDF of the delay distribution,
f_{\text{primary}}
is the PDF of the primary event times, and
pwindow
is the primary event window.
If the maximum delay D
is finite, the CDF is normalized by dividing
by F_{\text{cens}}(D)
:
F_{\text{cens,norm}}(q) = \frac{F_{\text{cens}}(q)}{F_{\text{cens}}(D)}
where F_{\text{cens,norm}}(q)
is the normalized CDF.
This function creates a primarycensored
object using
new_pcens()
and then computes the primary event
censored CDF using pcens_cdf()
. This abstraction allows
for automatic use of analytical solutions when available, while
seamlessly falling back to numerical integration when necessary.
See methods(pcens_cdf)
for which combinations have analytical
solutions implemented.
Value
Vector of primary event censored CDFs, normalized by D if finite (truncation adjustment)
See Also
Primary event censored distribution functions
dprimarycensored()
,
qprimarycensored()
,
rprimarycensored()
Examples
# Example: Lognormal distribution with uniform primary events
pprimarycensored(c(0.1, 0.5, 1), plnorm, meanlog = 0, sdlog = 1)
# Example: Lognormal distribution with exponential growth primary events
pprimarycensored(
c(0.1, 0.5, 1), plnorm,
dprimary = dexpgrowth,
dprimary_args = list(r = 0.2), meanlog = 0, sdlog = 1
)