Some warnings were fixed in the documentation as required by CRAN.
Fixed bugs in functions 'fitBLUP', 'SGP', 'getGenCov': an error was produced if 'y' has 2 dimensions but it is a 'data.frame'. This was fixed by using 'as.matrix(y)'
Fixed bug in 'multitrait.plot' function
Fixed bug in checkpoint in function 'fitBLUP': an error was produced whenever Z = NULL & K = NULL & ntraits > 1. This error is not produced if an EVD is provided
Version 1.4 (Jun-19-2024)
Changes in function names: SSI -> SGP, SSI.CV -> SGP.CV. Results from both functions are of the class "SGP" standing for "sparse genomic prediction"
Training and testing sets in function 'SGP' can now be defined using integer vectors as 'SGP(...,trn, tst)'. In the former version this was defined as 'SSI(..., trn_tst)', where 'trn_tst' was be a vector with 0's (for tst) and 1's (for trn)
In cross-validation, training set is defined as 'SGP.CV(...,trn)'. In the former version this was 'SSI.CV(...,trn_tst)'
Method 'fitted' is replaced by method 'predict'
A multi-trait analysis can be performed using the function 'SGP' with argument 'y' being either a matrix or a vector. In the later case, different genotypes and traits are specified by arguments 'ID_geno' and 'ID_trait', respectively
Likewise, for the 'getGenCov', arguments 'ID_geno' and 'ID_trait' can be also used if argument 'y' is a vector
Likewise, for the within-trait analysis of the function 'fitBLUP', arguments 'ID_geno' and 'ID_trait' can be also used if argument 'y' is a vector
Eigenvalues (d) and eigenvectors (U) in functions 'fitBLUP' and 'getGenCov' can be passed as argument 'EVD' being a list as per the function 'eigen'
Version 1.3.1 (Nov-17-2023)
Old dependencies R-packages were removed
Calls to functions 'Kronecker' and 'Kronecker_cov' from the tensorEVD R-package were added
Functions to work with triangular matrices were removed
Version 1.3.0 (Aug-15-2023)
New features
Function 'fitBLUP' allows the solution of the mixed model for multiple traits when input 'y' has more than one column
Function 'getGenCov' allows the calculation of all pairs of columns of input 'y' so a genetic covariance matrix can be formed
Function 'SSI' is extended to the multi-trait case if input 'y' has more than one column. In this case within-trait genetic/residual covariances varU and varE are calculated using function 'getGenCov' when are not provided
Arguments 'trn' and 'tst' in function 'SSI(...,trn,tst)' can be be now passed as 'SSI(...,trn_tst)', where 'trn_tst' can be a vector with 0's (for tst) and 1's (for trn)
New function 'prune' added (see manual)
New functions to work with triangular matrices added (see manual)
Version 1.2.0 (Aug-16-2022)
New features
Functions 'solveEN' and 'LARS' allow solving several regressions by iterating over columns of argument 'Gamma'
Function 'SSI' allows either saving or returning the coefficients through 'save.beta' and 'return.beta' arguments
Function 'SSI' returns also genetic values 'u' of testing subjects
Methods 'summary', 'fitted', and 'plot' can be implemented for a desired response variable 'y' different from the specified in object$y, e.g., fitted(object, y)
Version 1.1.0 (Mar-10-2022)
New features
Some problems were fixed in the documentation structure as required by CRAN.
Functions 'lars2', 'SSI_CV', 'plotNet', 'plotPath' changed their names to 'LARS', 'SSI.CV', 'net.plot', and 'path.plot', respectively.
Some arguments' functions changed their names to a more informative name (e.g., 'minLambda' => 'lambda.min')
More functionalities added to 'net.plot' function
Version 1.0.1 (Jan-26-2022)
New features
Functions 'SSI' and 'SSI_CV' allow providing either 'theta' (residual/genetic variances ratio) or the 'h2' (heritability)
Bug fixes
C-based routine associated to the 'readBinary' function now uses the 'Rf_allocMatrix' method to handle matrices whose length (number of rows x number of columns) exceed 2^31-1 = 2147483647
Version 1.0.0 (Sep-30-2021)
New features
Function 'solveEN' allows early stop when a user-provided number of non-zero predictors (at a given value of lambda) is reached (argument 'maxDF')
Functions 'solveEN' and 'lars2' return object 'beta' as matrix with predictors in rows (rather than in columns)
Function 'cov2cor2' allows multiplying the resulting correlation matrix times a constant 'a' (default is 'a=1')
Provided 'wheatHTP' dataset includes now an array of 4-folds partitions ('CV' column in object 'Y') and calculations of genetic and residual covariances between YLD and each of the wavelengths ('genCOV_xy' and 'resCOV_xy' objects), and among YLD from each environment ('genCOV_yy' object). Residuals covariances among YLD from each environment ('resCOV_yy' object) is also included
Bug fixes
Function 'fitBLUP' performs the new checking varU <= 2*var(y) to declare a possible error if FALSE
Function reshape2::melt is used instead of reshape::melt
Version 0.4.0 (May-12-2021)
New features
More detailed functions' documentation
Function 'fitBLUP' performs a quality control for very small or negatives eigenvalues
Function 'saveBinary' does not save columns' nor rows' names anymore
Function 'SSI' uses now a C-based routine called 'add2diag' created to add a numeric value to the diagonal of a symmetric matrix (single or double precision). This routine is not at the user level
Function 'getGenCov' has the argument 'warn' to whether show warnings from 'BLUP' analyses
Bug fixes
All C-based routines: a 'long long' variable type, instead of an 'int' type, was used for indexing arrays (matrices). This change allows dealing with matrices whose length (number of rows x number of columns) exceed 2^31-1 = 2147483647 (e.g., a matrix of 46341 x 46341)
Version 0.3.0 (Apr-29-2021)
Features
First released version
Function 'solveMixed' (from GitHub version) was renamed to 'fitBLUP'