Keywords in Mlxtran

Some keywords manage the complexity of the deterministic computations. Since they are used by the language, these keywords are not available for re-definition or overloading.

Keywords used to define sections in the Mlxtran model file

Here is the list of keywords reserved for the sections definition:

<DESCRIPTION>: This is used for the description of the project. This can be interesting to use it when you share and/or when you want to keep the history of the projects. This section is optional.
<DESIGN>: This section is used for the definition of the design (administration and treatment). This section is optional.
<MODEL> : This section is used for the model description. It contains the structural model in [LONGITUDINAL] but can also contain [INDIVIDUAL], [COVARIATE]. This section is mandatory.
<OUTPUT>: This section is used to define the outputs you wan to look at. This defines the name and the time you want to see the outputs. This section is mandatory.
<PARAMETERS>: This section is used to define the parameters. This section is mandatory. However, the model exploration is done by playing with the parameters. Therefore, you always have it.
<RESULTS>: This section is used to define the graphical results. It defines the graphics proposed by Mlxplore and all the associated settings. This section is mandatory.
<SETTINGS>: This section is used to define the settings. It allows to define the iiv actions and the percentiles configurations. This section is mandatory.

Keywords used to define subsections

Here is the list of keywords reserved for the subsections definition:

[ADMINISTRATION]: This keyword is used to define administrations in section <DESIGN>.
[COVARIATE]: This keyword is used to open the section <MODEL> for the definition of the covariates in the model. Covariates are variables that are not part of the main experimental manipulation but has an effect on the dependent variable.
[GRAPHICS]: This keyword is used to define the graphics in the section <RESULTS> (to define what and how to display it) and in the section <SETTINGS> (to define the iiv actions and the percentiles configurations).
[INDIVIDUAL]: This keyword is used to open the section for the definition of the individual parameters in the section model <MODEL>.
[LONGITUDINAL]: This keyword is used to open the section for the structural model description in the section <MODEL>.
[TREATMENT]: This keyword is used to define treatments (concatenation of administrations) in section <DESIGN>.

Keywords used to define blocks

Here is the list of keywords reserved for elements in the subsections definition:

DEFINITION: For sections [INDIVIDUAL], [COVARIATE], this keyword allows the explicit definition-based descriptions of probability distributions in a block.
EQUATION: In each section, this keyword allows flexible equation-based descriptions implemented in a block.
PK: In section [LONGITUDINAL], this keyword allows the used of defined macros for PK models.
OUTPUT: In section [LONGITUDINAL], this keyword allows the definition of the outputs under consideration.

Dedicated keywords used in each section

Section <MODEL>
In this section, only the word file is used as a keyword. It is used as a keyword to make a link to an external model file as follows

file='./path to my model'

Full list of keywords

Here is the full list of keywords in Mlxtran except

the keywords defined in the top of the page,
the keywords used for distribution definition (that are listed here)
the keywords used for classical mathematical definition (that are listed here)

Name	Meaning	where can it be used ?	link
absorption	Macro used for defining the absorption process in a longitudinal model	In subsection [LONGITUDINAL] after PK:	link
adm	Type of administration (type and adm are equivalent).	In argument of the following macros: absorption, depot, iv and oral
amount	When it is used in the longitudinal model, it corresponds to the name of variable defined as the amount within the compartment When it is used in a treatment or an administration, it corresponds to the amount(s) of drug (in Mlxplore and Simulx).	In the first use, in argument of the following macros: compartment and peripheral In the second one, in the <DESIGN> section in Mlxplore and in the treatment definition in Simulx.	Mlxplore link, Simulx link
amtDose	Amount of the last administered dose. This is a step function and is null before the first dose.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
band	Extended logit error model $t(y) = \log(\frac{y-A}{B-y})$	In an error model, in subsection [LONGITUDINAL], in a definition EQUATION:	link
bsmm	Mixture of continuous observations. It is a mixture between subjects model mixtures (BSMM). It assumes no inter individual variabilities for the proportions of each group (ı.e. the probabilities to belong to the different groups). It is relevant only for Monolix.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:
categorical	Type of observation model.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type=	link
categories	List of the available ordered categories for a categorical observation. They are usually represented by increasing successive integers.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is a category	link
cmt	Label of the compartment.	In argument of the following macros: absorption, compartment, depot, effect, elimination, iv, oral
coefficient	Coefficient under consideration for a distribution definition dependaing on covariates	In any distribution definition in a block DEFINITION:	link
combined1	Combined error model $y = f + (a+b*f)e$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
combined1c	It corresponds to a combined error model $y = f + (a+b*f^c)e$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
combined2	Combined error model $y = f + ae_1+bf*e_2$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
combined2c	Combined error model $y = f + ae_1+bf^c*e_2$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
compartment	Macro used for defining a compartment	In subsection [LONGITUDINAL] after PK:	link
concentration	Name of the variable defined as the concentration within the compartment	In argument of the following macros: compartment, effect, peripheral
constant	Constant error model $y = f + a*e$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
continuous	Type of observation model.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type=	link
count	Type of observation model.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type=	link
covariate	Covariate under consideration for a distribution definition	In any distribution definition in a block DEFINITION:	link
delay	It corresponds to delay function to define DDE.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
dependence	It corresponds to the label used to defined that an observation variable for ordered categorical data modelled as a Markov chain.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is categorical	link
depot	It corresponds to an absorption targeting a depot. A component of an ODE system is defined as the target depot for the doses.	In subsection [LONGITUDINAL] after PK:	link
effect	This macro defines an effect compartment. It is linked to a simple compartment and used through the variable for its effect concentration.	In subsection [LONGITUDINAL] after PK:	link
elimination	This macro defines an elimination process.	In subsection [LONGITUDINAL] after PK:	link
else	It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end.	In a block EQUATION:
elseif	It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end.	In a block EQUATION:
end	It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end.	In a block EQUATION:
errorModel	It corresponds to the label to define an error model for a continuous observation model	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
event	Type of observation model.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type=	link
eventType	Label to define the event type for an event observation model. It allows to define if the exact time of the events or censored per interval is observed.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
exponential	Exponential error model $y = fe^{ae}$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
from	Label of the source compartment for the transfer.	In argument of the following macro: transfer	link
hazard	Hazard function	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
if	It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end.	In a block EQUATION:
inftDose	The keyword inftDose defines the infusion time of the last administered dose. This is a step function. The rate of the final absorption can be different from the rate of the administration process. It is null before the first dose.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
input	It corresponds to the definition of the inputs in a subsection	In subsections [LONGITUDINAL], [INDIVIDUAL], and [COVARIATE]	link
intervalCensored	Argument of eventType.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
intervalLength	Label to length of censoring intervals in an event observation model. It is useful for simulation only,	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
iv	The macro iv defines an absorption for intravenous doses. Doses without an administration rate or infusion time are instantaneously absorbed within the associated compartment, as an IV bolus.	In subsection [LONGITUDINAL] after PK:	link
linear	It is an argument of odeType= and allows to define the dynamical system as linear	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
Markov	It corresponds to the dependence of a categorical observation model. It allows to define that the observation model is based on a Markov chain	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a dependence=	link
maxEventNumber	Maximum number of events in an event observation model. It is useful for simulation only	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
mean	Mean of the associated normal distribution.	In any distribution definition in a block DEFINITION:	link
nonStiff	It is an argument of odeType= and allows to define the dynamical system is nonStiff and thus yields to an adapted numerical scheme for the resolution	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
odeType	It is the label that allows to define the type of ODE.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
oral	It is a macro used for defining the absorption process in a longitudinal model	In subsection [LONGITUDINAL] after PK:	link
output	It allows to define the outputs of a structural model	In the longitudinal model, in subsection [LONGITUDINAL], in a block OUTPUT:
P	The majuscule P corresponds to the definition of a probability	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:	link
p	It corresponds to the bio availability in an absorption process	In argument of the following macro: absorption, depot, iv, and oral
peripheral	The macro peripheral defines a peripheral compartment. It is equivalent to a simple compartment with two transfers of amount towards and from another compartment.	In subsection [LONGITUDINAL] after PK:	link
PK	It defines where the macros are defined	In subsection [LONGITUDINAL]	link
pkmodel	It defines the macro pkmodel	In subsection [LONGITUDINAL], in a block PK: or in a block EQUATION:	link
prediction	It corresponds to the name of the base prediction variable	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
proportional	It corresponds to a proportional error model $y = f +b*fe$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
proportionalc	It corresponds to a proportional error model $y = f +b*f^ce$	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous	link
regressor	It declares the input regression values.	In the longitudinal model, in subsection [LONGITUDINAL], after the input definition	link
rightCensoringTime	Right censoring time of events. It is useful for simulation only	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event	link
sd	Standard deviation of the associated normal distribution (standardDeviation and sd are synonymous keywords)	In any distribution definition in a block DEFINITION:	link
standardDeviation	Standard deviation of the associated normal distribution (standardDeviation and sd are synonymous keywords)	In any distribution definition in a block DEFINITION:	link
stiff	It is an argument of odeType= and allows to define the dynamical system is nonStiff and thus yields to an adapted numerical scheme for the resolution	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
t	time	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:
t_0	Initialization time for the equations	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:
t0	Initialization time for the equations	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:
table	This keywords declares the variables to record in tables.	In the longitudinal model, in subsection [LONGITUDINAL], in a block OUTPUT:
target	Name of the component of an ODE system that is shifted by the absorption.	In argument of the following macro: depot	link
tDose	The keyword tDose defines the time of the last administered dose. This is a step function. Its value is unaffected by any lag time Tlag. Indeed, a lag time targets the dose absorption. It is null before the first dose.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION:	link
to	Label of the target compartment for the transfer	In argument of the following macro: transfer	link
transfer	The macro transfer defines a transfer of amount from a first compartment to a second one.	In subsection [LONGITUDINAL] after PK:	link
transitionRate	Transition rate departing from a given category to another one. It is used in the definition of a categorical observation model.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:	link
type	It allows the type of observation model. It can be continuous, count, categorical, or event.	In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION:
typical	It corresponds to the typical value during a distribution definition	In any distribution definition in a block DEFINITION:	link
use	It allows to define the regressor in the longitudinal subsection. Regressors are defined as inputs at the beginning and thus are specified as regressors using use=	In the longitudinal model, in subsection [LONGITUDINAL], after the input definition	link
var	Variance of the associated normal distribution (variance and var are synonymous keywords)	In any distribution definition in a block DEFINITION:	link
variance	Variance of the associated normal distribution (variance and var are synonymous keywords)	In any distribution definition in a block DEFINITION:	link
volume	It corresponds to the name of predefined variable to use as the volume of the compartment	In argument of the following macros: compartment, effect, peripheral
wsmm	Mixture of continuous observations. It is a mixture within subjects.	In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: