You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Return diagonal of Mendelian sampling variance matrix in makeAinv() and makeS()
These (or their inverses?) can be used in JAGS or BUGS when running a quantitative genetic mixed model
Small changes
default action is to calculate log-determinant of matrices
switched from not calculating this by default
2.15.0
NEW
Functions to construct sex-chromosomal dominance relatedness matrices
makeSd() and makeSdsim()
These are similar to what makeD() and makeDsim() accomplish for autosomes
The ouptut contains the Sd and Sdsim dominance relatedness matrices
The inverses of these can be obtained from Sdinv and Sdsiminv and used in a mixed model
Small changes
proLik() improved/bug fixed to find confidence limits
previously would declare confidence limits found when they hadn't been
this was due to optimize() quitting too early with default tol argument
returns NA 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 CIs
use lower_bound algorithm for matrix lookup within c++ code
based on c++ std::lower_bound
affect makeAinv() and makeD()
greater speedup as A^-1 and D become more dense
create default and class 'numPed' methods for genAssign() and prunePed()
can greatly trim down genAssign.numPed() code (and to some extent prunePed.numped())
this speeds up/uses less memory
since genAssign() and prunePed() are frequently called in many nadiv functions which operate on class 'numPed', this will have modest, but significant performance increases
thanks to profvis for bringing my attention to this!