The function compile_wisle_summary() extracts results from various
lists that are generated during the wisle estimation and compiles a
summary data frame.
compile_wisle_summary(
data,
batch_vbl,
rl,
poi_list,
icpt_list,
wcsl_list,
wcb_list,
limits_list,
poi_ich,
xform = c("no", "no"),
shift = c(0, 0)
)A list with two element is returned, containing the following elements:
A data frame of the worst case intercepts of each of the four fitted models.
A data frame of the intercepts, the differences between release and shelf life limits, the WCSLs, the expiry and release specification limits, the shelf lives and POI values.
Structure of the POI data frame:
The intercept of the worst case batch of the cics model.
The intercept of the worst case batch of the dics model.
The intercept of the worst case batch of the dids model with pooled mean square error (pmse).
The intercept of the worst case batch of the dids model obtained by fitting individual models to the data of each batch.
Absolute difference between the release and and the shelf life specification of the cics model.
Absolute difference between the release and and the shelf life specification of the dics model.
Absolute difference between the release and and the shelf life specification of the dids model with pooled mean square error (pmse).
Absolute difference between the release and and the shelf life specification of the dids model obtained by fitting individual models to the data of each batch.
WCSL of the cics model.
WCSL of the dics model.
WCSL of the dids model with pooled mean square error (pmse).
WCSL of the dids model obtained by fitting individual models to the data of each batch.
The (expiry) specification, i.e. the specification which is relevant for the determination of the expiry.
The calculated release specification.
The estimated shelf life of the cics model.
The estimated shelf life of the dics model.
The estimated shelf life of the dids model with pooled mean square error (pmse).
The estimated shelf life of the dids model obtained by fitting individual models to the data of each batch.
The POI of the cics model.
The POI of the dics model.
The POI of the dids model with pooled mean square error (pmse).
The POI of the dids model obtained by fitting individual models to the data of each batch.
A data frame with the columns specified by response_vbl,
time_vbl and batch_vbl.
A character string that specifies the column in data
with the grouping information (i.e. a factorial variable) for the
differentiation of the observations of the various batches.
A list of four elements named cics, dics,
dids.pmse and dids with the points of intersection (POI)
of each linear regression model and batch. The cics, dics
and dids.pmse elements are NA if data of only a single
batch is available.
A list of four elements named cics, dics,
dids.pmse and dids with the intercepts of each linear
regression model and batch. The cics, dics and
dids.pmse elements are NA if data of only a single batch
is available.
A list of four elements named cics, dics,
dids.pmse and dids with the worst case scenario limits
of each batch and linear regression model. The cics, dics
and dids.pmse elements are NA if data of only a single
batch is available.
A list of four elements named cics, dics,
dids.pmse and dids with the indices of the worst case
batches. The cics, dics and dids.pmse elements are
NA if data of only a single batch is available.
A list returned by the set_limits() function.
A numeric named vector of the POI values of the worst case batches of each model.
A vector of two character strings that specifies the
transformation of the response and the time variable. The default is
“no” transformation, i.e. c("no", "no"), where the first
element specifies the transformation of the \(x\) variable and the
second element the transformation of the \(y\) variable. Valid
alternatives for \(x\) and/or \(y\) variable transformation are
"log" (natural logarithm), "sqrt" (square root) and
"sq" (square).
A vector of two values which will be added to the variables
\(x\) and/or \(y\) before they are transformed as specified by the
xform parameter, where the first element will be added to the
\(x\) variable and the second element to the \(y\) variable. The
purpose is to prevent an undefined state which could arise when variables
with values of \(\leq 0\) are log or square root transformed. The
default is c(0, 0).
Information stored in multiple lists that are generated during the “what-if shelf life estimation” is extracted and compiled in a single data frame.
extract_wc_x, extract_from_ll_wcsl,
expirest_wisle.