v 0.1.12 # September 23, 2019 - Add packages to LinkingTo - Fix seg fault error due to int function not returning a value - restore configure files v 0.1.11 v 0.1.10 # June 4, 2019 - Make compatible with R 3.6.0 v 0.1.9 # April 5, 2017 - Fix small bug in p-values from wald(). Make sure Sigma is symmetric v 0.1.8 # August 26, 2015 - Add documentation that was dropped from the last version v 0.1.7 # July 10, 2015 - Remove formula.tools dependency due to error caused by v1.5.4 v 0.1.6 # January, 29, 2015 - Fix issue in convertToBinary() where the function would fail if relative file paths were used v 0.1.5 # September 9, 2014 - Fix issue checking is.nil for big.matrix for some functions v 0.1.4 # July 31, 2014 - In read.fam() / read.tfam(), can now read file with arbitrary extension - convertToBinary() now supports sample names (i.e. row names) - functions getAlleleFreq(), getMissingCount(), getAlleleVariance(), getMACHrsq() now assign names for each entry - Add more information to _alleles file produced by convertToBinary() and simpleAnnotation - Fix issue with set_missing_to_mean() when the number of missing values is 1 for all columns. Use foreach() instead of sapply() v 0.1.3 # July 23, 2014 - Improve error message in glmApply() and lrgprApply() when features is not a standard R matrix or a FileBacked big.matrix stored as doubles v 0.1.2 # July 21, 2014 - Fix glmApply() and lrgprApply() so that terms argument is used correctly. Previously there was a bug where it was ignored - Update convertToBinary() to give better description of why a files does not fit the specified format v 0.1.1 - Update error message for plot() of lrgpr() object - Update documentation to say that a big.matrix must be re-attached in each R session v 0.1.0 - Update documentation for glmApply2() v 0.0.9 - Update dependencies v 0.0.8 - Improve documentation - convertToBinary() writes file with coding of alleles v 0.0.7 - Fixed issue in convertToBinary() so that indels in TPED's are treated correctly - Fixed a bug where setting the number of threads to k for lrgprApply() or other functions incidentally restricted the number of threads by all subsequent functional calls v 0.0.6 - in criterion.lrgpr() and cv.lrgpr(), restrict rank to be less than ncol(features) and length(ord) v 0.0.5 - Update documentation - Fix error in getAlleleFreq, getAlleleVariance that made all returned values 1 - Add getMACHrsq to evaluate imputational quality using MACH's r^2 metric v 0.0.4 - specify columns of features to include/exclude from analysis glmApply() and lrgprApply() - lrgpr() and lrgprApply() now handle low rank SVD produced by svd() - lrgpr() is MUCH faster for large sample sizes - glmApply2() (experimental) implements faster linear regression - Backend changes to processing of binary matrix data on harddrive - Faster cv.lrgpr() and criterion.lrgpr() by not computing right singular vectors - These return objects now compatible with plot() v 0.0.3 - graceful exit from glmApply/lrgprApply when response is empty v 0.0.2 - Add option to suppress progress bar - Throw error when sub.big.matrix is passed as features. Only matrix and big.matrix are supported