Patches and recent notes

Fixed bug fitting multivariate model when no records have all traits present.Added !AISING qualifier to better manage singularities n the AI matrix. Thank-you to those users who find issues with Echidna and let me know. Arthur

Fixed bug limiting pedigree to 400000 individualsAdd !SGIV qualifier to PEDIGREE file line

Fixed serious bug calculating the Residual Score in multivariate models when missing value pattern differs among traits.Fixed issue of some jobs failing with Factor !I factor type Fixed issue parsing at(Tr,2).( A -B)Added new sparse binary .sgiv input option

Fixed issue with Factor !A !L names.txtFixed issues with .xml files

Refined plot of RvE for binary dataAdded !HINV qualifier to merge a Genomic relationship matrix with a Numerator relationship matrix to form Hinverse. Various bug fixes

More components allowed in VPREDICT Fixed bug (crash( reporting long integer class names in PREDICTAdded ANTE variance structure . ante1(access) as R and GSome changes to STEPSZ and SLOW tuning have slightly modified some convergence sequences. Added ar1h(access) as R and GFixed ante1(access $VarG) where […]

Added PREDICT … !CONTRAST coeffs to facilitate testing treatment contrasts Small Speed up of SCORE calculation in bivariate analysis Fixed bug reporting solutions in 1.61

Fixed bug parsing a long (>200characters) !ASSIGN listFixed bug associated with settng specific variances to zero.Added !NCZ qualifier to !MBF as alternative to setting columns in function 2nd argument. If you are not at least using build 1.60, update now.

Fix recent (1.59) bug in processing with !GDENSE qualifier.Fix recent (1.58) bug reporting labels of class levels in .ess/.etb files From build 1.58, if Echidna is invoked with no arguments, it entersa MenuMode with options to and edit an existing command file,create a command file […]

This build incorporates faster processing of larger jobs achieved by using block processing of the mixed model equation for absorption and inversion. The gain depends on the sparsity pattern of the mixed model equations and is greatest with less sparse patterns.