MFx | R Documentation |
Generic method for MFx
, a function denoted MF(x,t)
for
x
% Multiplication Factor at time t
.
The function MFx
, x
% Multiplication Factor at time t
, (MF(x,t)
),
is used to compute the multiplication factor
applied to the concentration exposure profile in order to
reduce by x
% (argument X
) the survival probability at a
specified test duration t
(argument time_MFx
) (default is the maximum
time point of the experiment).
Mathematical definition of x
% Multiplication Factor at time t
(at the end of a time series T = \{0, \dots, t\}
),
denoted MF(x,t)
, is given by:
S(MF(x,t) * C_w(\tau \in T), t) = S( C_w(\tau \in T), t)*(1- x/100)
,
where C_w(\tau \in T)
is the initial exposure profile without
multiplication factor. And so the expression S(MF(x,t)* C_w(\tau \in T), t)
is the survival probability after an exposure profile
MF(x,t)* C_w(\tau \in T)
at time t
.
This is a method
to replace function MFx
used on survFit
object when computing issues happen. MFx_ode
uses the deSolve
library to improve robustness. However, time to compute may be longer.
The function MFx_ode
, x
% Multiplication Factor at time t
, (MF(x,t)
),
is used to compute the multiplication factor
applied to the concentration exposure profile in order to
reduce by x
% (argument X
) the survival probability at a
specified test duration t
(argument time_MFx
) (default is the maximum
time point of the experiment).
Mathematical definition of x
% Multiplication Factor at time t
(at the end of a time series T = \{0, \dots, t\}
),
denoted MF(x,t)
, is given by:
S(MF(x,t) * C_w(\tau \in T), t) = S( C_w(\tau \in T), t)*(1- x/100)
,
where C_w(\tau \in T)
is the initial exposure profile without
multiplication factor. And so the expression S(MF(x,t)* C_w(\tau \in T), t)
is the survival probability after an exposure profile
MF(x,t)* C_w(\tau \in T)
at time t
.
MFx(object, ...)
## S3 method for class 'survFit'
MFx(
object,
data_predict,
X = 50,
time_MFx = NULL,
MFx_range = c(0, 1000),
mcmc_size = 1000,
hb_value = TRUE,
spaghetti = FALSE,
accuracy = 0.01,
quiet = FALSE,
threshold_iter = 100,
hb_valueFORCED = 0,
ode = TRUE,
interpolate_length = NULL,
interpolate_method = "linear",
...
)
MFx_ode(object, ...)
## S3 method for class 'survFit'
MFx_ode(
object,
data_predict,
X = 50,
time_MFx = NULL,
MFx_range = c(0, 1000),
mcmc_size = 1000,
hb_value = TRUE,
spaghetti = FALSE,
accuracy = 0.01,
quiet = FALSE,
threshold_iter = 100,
hb_valueFORCED = 0,
interpolate_length = NULL,
interpolate_method = "linear",
...
)
object |
An object of class |
... |
Further arguments to be passed to generic methods |
data_predict |
A dataframe with two columns |
X |
Percentage of survival change (e.g., |
time_MFx |
A number giving the time at which |
MFx_range |
A vector from which lower and upper bound of the range of the
multiplication factor |
mcmc_size |
Can be used to reduce the number of MCMC samples in order to speed up the computation. The default is 1000. |
hb_value |
If |
spaghetti |
If |
accuracy |
Accuracy of the multiplication factor. The default is 0.01. |
quiet |
If |
threshold_iter |
Threshold number of iteration. |
hb_valueFORCED |
If |
ode |
IF |
interpolate_length |
Length of the time sequence for which output is wanted. |
interpolate_method |
The interpolation method for concentration. See package |
When class of object
is survFit
, see MFx.survFit.
returns an object of class MFx
The function returns an object of class MFx
, which is a list
with the following information:
X_prop |
Survival probability for |
X_prop_provided |
A number giving the proportion of reduction in survival. |
time_MFx |
A number giving the time at which |
df_MFx |
A |
df_dose |
A |
MFx_tested |
A vector of all multiplication factors computed. |
ls_predict |
A list of all object of class |
The function returns an object of class MFx
, which is a list
with the following information:
X_prop |
Survival probability for |
X_prop_provided |
A number giving the proportion of reduction in survival. |
time_MFx |
A number giving the time at which |
df_MFx |
A |
df_dose |
A |
MFx_tested |
A vector of all multiplication factors computed. |
ls_predict |
A list of all object of class |
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