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rxode2 5.0.1

rxode2 5.0.0

rxode2 4.1.1

rxode2 4.1.0

rxode2 4.0.3

rxode2 4.0.2

rxode2 4.0.1

rxode2 4.0.0

rxode2 3.0.4

rxode2 3.0.3

rxode2 3.0.2

rxode2 3.0.1

rxode2 3.0.0

Breaking Changes

Possible breakingchanges (though unlikely)

New features

Bug fixes

Big change

rxode2et (no changes beforemerge)

rxode2et 2.0.13

rxode2et 2.0.12

rxode2et 2.0.11

rxode2et 2.0.10

rxode2et 2.0.9

rxode2random (before merge)

rxode2random 2.1.0

rxode2random 2.0.13

rxode2random 2.0.12

rxode2random 2.0.11

rxode2random 2.0.10

rxode2random 2.0.9

rxode2parse (fixed beforemerging)

rxode2parse 2.0.19

rxode2parse 2.0.18

rxode2parse 2.0.17

rxode2parse 2.0.16

rxode2parse 2.0.15

rxode2parse 2.0.14

rxode2parse 2.0.13

rxode2parse 2.0.12

rxode2parse 2.0.11

rxode2parse 2.0.10

rxode2parse 2.0.9

rxode2 2.1.3

Bug fixes

New features

Other changes

rxode2 2.1.2

Other changes

rxode2 2.1.0

Breaking changes

New features

cl<-exp(tcl+ eta.cl+ wt_cl*log(WT/70.5))

Instead of the

cl<-exp(tcl+ eta.cl+ wt_cl* log.WT.div.70.5)

That was previously required (wherelog.WT.div.70.5 wascalculated in the data) for mu expressions. Theui now hasmore information to allow transformation of data internally andtransformation to the old mu-referencing style to run theoptimization.

Internal new features

Bug fixes

Maintenance fixes

rxode2 2.0.14

rxode2 2.0.13

Bug fixes

New features

Internal changes

rxode2 2.0.11

rxode2 2.0.10

rxode2 2.0.9

rxode2 2.0.8

Breaking changes

New features

Bug fixes

New features

rxode2 2.0.7

rxode2 2.0.6

Breaking changes

Solving controls

Simulations

Other breaking changes

Additional features

Internal changes

Bug fixes

RxODE 1.1.3

RxODE 1.1.2

RxODE 1.1.1

RxODE 1.1.0

RxODE 1.0.9

RxODE 1.0.8

RxODE 1.0.7

RxODE 1.0.6

RxODE 1.0.5

RxODE 1.0.4

Breaking changes

New features

Each of these are similar to the Rlag,lead,first,last anddiff. However when undefined, it returnsNA

mod1<-RxODE({    KA=2.94E-01;    CL=1.86E+01;    V2=4.02E+01;    Q=1.05E+01;    V3=2.97E+02;    Kin=1;    Kout=1;    EC50=200;    C2= centr/V2;    C3= peri/V3;    d/dt(depot)=-KA*depot;    d/dt(centr)= KA*depot- CL*C2- Q*C2+ Q*C3;    d/dt(peri)=                    Q*C2- Q*C3;    d/dt(eff)= Kin- Kout*(1-C2/(EC50+C2))*eff;if (!is.na(amt)){        tdose<- time    }else {        tad<- time- tdose    }})

It is still simpler to use:

mod1<-RxODE({    KA=2.94E-01;    CL=1.86E+01;    V2=4.02E+01;    Q=1.05E+01;    V3=2.97E+02;    Kin=1;    Kout=1;    EC50=200;    C2= centr/V2;    C3= peri/V3;    d/dt(depot)=-KA*depot;    d/dt(centr)= KA*depot- CL*C2- Q*C2+ Q*C3;    d/dt(peri)=                    Q*C2- Q*C3;    d/dt(eff)= Kin- Kout*(1-C2/(EC50+C2))*eff;    tad<- time- tlast})

If thelhs parameters haven’t been defined yet, they areNA

All these change the solving to single thread by default to make surethe simulation is reproducible. With high loads/difficult problems therandom number generator may be on a different thread and give adifferent number than another computer/try.

Also please note that theclang andgcccompiler use different methods to create the more complex randomnumbers. ThereforeMacOS random numbers will be differentthanLinux/Windows at this time (with theexception of uniform numbers).

These numbers are still non-correlated random numbers (based on thesitmo test) with the exception of the vandercorput distributions, so ifyou increase the number of threads (cores=…) the results should still bevalid, though maybe harder to reproduce. The faster the random numbergeneration, the more likely these results will be reproduced acrossplatforms.

Engine changes

Bug fixes:

RxODE v0.9.2-0

RxODE v0.9.1-9

RxODE v0.9.1-8


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