#2.17.2
pin() does not work with asreml version 4 (should still
work with asreml version 3 model objects)
nadiv will not support this in the future as asreml v4
has vpredict()proLik4(), essentially the same as
proLik(), but works on asreml v4
proLik() is kept to retain compatibility with asreml v3
model objectsmakeM() creates mutational effects relatedness matrix
M directly
brms/JAGS etc. that
require relatedness matrices (not their inverse) in mixed modelsMatrix non-virtual subclasses
Matrix 1.4-2 and specifically
>=1.5-0prepPed() as often encountered/reported from
use in optiSel
makeMinv() creates the inverse of the (additive)
mutational effects relatedness matrix.makeT() creates the lower triangle of the cholesky
factor of the additive genetic numerator relatedness matrix.sparseMatrix() instead of Matrix()
ggcontrib() to internally use
makeT() to directly create a subset of the
T matrix (which the subset is Q for
the special setup for genetic groups).
geneDrop() conducts a gene dropping simulation down a
user-supplied pedigree.simGG() now simulates phenotypes with heterogeneous
additive genetic variances among the genetic groups (i.e., immigrant and
resident groups)
makeGGAinv() added as a new function to
construct genetic group-specific inverse relatedness matrices
(Ainv).
?makeGGAinv), but below is a basic example:ggPed <- Q1988[-c(3:7), c("id", "damGG", "sireGG")]
AinvOut <- makeGGAinv(ggPed, ggroups = 2)$Ainv #<-- list with 2 Ainv matricesmakeTinv() and makeDiiF() functions
fmakeGGAinv().makeDiiF() creates the D matrix of the
Cholesky factorization of the relatedness matrix below (i.e.,
A and the coefficients of inbreeding (diagonals-1 of
A)makeTinv() creates Tinv of the
Cholesky factorization of the inverse relatedness matrix below (i.e.,
Ainv)
1 / d_ii
Dinv <- D followed by
Dinv@x <- 1 / D@xmakeTinv(Mrode2)
makeDiiF(Mrode2)simPedDFC() to allow more flexibility in
designing pedigreesroxygen2 documentationmakeAinv() and makeS()
makeSd() and makeSdsim()
makeD() and
makeDsim() accomplish for autosomesproLik() improved/bug fixed to find confidence limits
optimize() quitting too early with
default tol argumentNA if confidence limits are not, in fact, found
(e.g., for boundary parameters, variances that are not significantly
greater than zero)plot.proLik() now includes vertical lines to better
visualize CIsmakeAinv() and makeD()genAssign() and prunePed()
genAssign.numPed() code (and to
some extent prunePed.numped())genAssign() and prunePed() are
frequently called in many nadiv functions which operate on class
‘numPed’, this will have modest, but significant performance
increasesprofvis for
bringing my attention to this!fuzz argument.makeAinv.Rd help file or by
running the following commands in R:?makeAinv # launches the help documentation
example(makeAinv) # runs the examples in the help documentation* Notably, fuzzy classification can be set to 'null', where each phantom parent is assigned to one genetic group with probability=1. This produces the same **Astar** matrix as regular genetic group methods (without fuzzy classification). See this demonstrated in the examples of the help documentation.makeAstarMult() function to create the inverse
numerator relationship matrix with genetic groups (and possibly also
fuzzy classification of genetic groups) through matrix multiplication
instead of using direct algorithms to set this up.
ggcontrib() and makeAinv() to create
Q and A^-1 directly, then multiplies
these in such a way as to obtain Astar.makeAstarMult.Rd help file or run them in R
with the command:?makeAstarMult # launches the help documentation
example(makeAstarMult) # runs the examples in the help documentationF2009 dataset
makeAinv())F2009.Rd or in R type:?F2009simGG() function to simulate pedigree and
phenotype when immigration occurs in a focal population
ggTutorial dataset (below)ggTutorial dataset
ggTutorial.Rd or in R type:?ggTutorialLRTest() is now an exported function to do
log-likelihood ratio testsmakeAinv().
fuzz argument
fuzz == NULL then dispatch the method
makeAinv.default()fuzz == "matrix" | fuzz == "Matrix" then dispatch
makeAinv.fuzzy()proLik() and the confidence interval
estimation
LRTest() as basis of constrainFun()
within proLik() so consistently define log-likelihood ratio
test statisticsggcontrib() can now incorporate fuzzy classification of
genetic groups
ggcontrib() have
been changed. For more information and examples, read the help
documentation ggcontrib.Rd or in R type:?ggcontrib # launches the help documentation
example(ggcontrib) # runs the examples in the help documentationmakeAinv()makeAinv() now can construct the augmented A-inverse
matrix for genetic groups
makeAinv(),
however, the defaults are set to produce the normal A-inverse. For more
information and examples, read the help documentation
makeAinv.Rd or in R type:?makeAinv # launches the help documentation
example("makeAinv") # runs the examples in the help documentationmakeAinv() - significant
speed-up!numPed for pedigrees constructed by
numPed().
is.numPed()) and re-ordering rows
(ronPed()) currently availablenumPed, use ronPed() instead of typical
subsetting operators (e.g., '[') to retain the class
attribute numPed. For example:nPed <- numPed(Mrode2)
is.numPed(nPed) # TRUE
# re-order using typical R functions
nPed_sub <- nPed[order(nPed[, 2], nPed[, 3]), ]
is.numPed(nPed_sub) # FALSE; see help via ?'[' about dropping attributes
class(nPed_sub) # matrix
nPed_subnadiv <- ronPed(nPed, order(nPed[, 2], nPed[, 3]))
is.numPed(nPed_subnadiv) # TRUE
class(nPed_subnadiv) # numPedwarcolak dataset.
sex are now "M" and
"F" instead of 0 & 1.warcolak.Rd.Q1988
from Quaas 1988 and (2) Mrode3 from Mrode (2005) chapter 3.
See their descriptions in Q1988.Rd and
Mrode3.Rd or in R type:?Q1988
?Mrode3Removed the default from the heterogametic argument
in makeS().
makeS(FG90)won’t work! Must now type:
makeS(FG90, heterogametic = "0")as a minimum
TDtT(), a function to take the
TDT’ Cholesky decomposition of a matrix (not currently
exported).founderLine() which traces all individuals back
to either the paternal or maternal foundergrfx() now has a new argument to allow user to supply
the standard normal deviates instead of generating them within the
function.
incidence = NULL... argument to drfx() so that
arguments for the internal use of grfx() can be supplied to
drfx().simPedHS() or
simPedDFC().ggcontrib(), default is “matrix”pcc() return FALSE if the object
(asreml) shows the log-likelihood did not convergesilent = FALSE argument to pcc() so
that the default can be changed to not show messages
proLik() so that profile likelihoods
should be “valleys” (instead of “hills”, as they were in versions
previous to 2.13.3)makeAinv()
makeA() to use inverse of
cholesky factorization of the A-inverse matrix
base::chol2inv() to obtain A
prepPed() to prepare pedigrees for use in
other functionsmakeAinv()ggcontrib() so that genetic group contributions
can be calculated
pin() and pcc() functions for
the delta method and parameter value convergence checking, respectively,
for asreml type REML models. Also added the pin.Rd and pcc.Rd
help/documentation files.
pin() is not exported in this version (need
nadiv:::pin() to use it)makeDufam(), but did not export it.
makeDomEpi() argument “Dinverse” to “invertD”
to be similar to makeD()pcc() checks to constrainFun() so
that only likelihood ratio test statistics of the constrained model
returned if both the loglikelihood & parameter estimates have
convergedfindDFC(), makeD(),
makeDsim()FindDFC() to
findDFC()