plotPath: Coefficients path plot
In MarcooLopez/SFSI_data: Sparse Family and Selection Index

Description Usage Arguments Author(s) Examples

Plot the coefficients evolution path along the regularization parameter

1 2	plotPath(fm, Z = NULL, K = NULL, indexK = NULL, tst = NULL, title = NULL, maxCor = 0.85)

`fm`	An object of the 'LASSO' or 'SSI' class
`Z`	Design matrix for the random effects. When `Z=NULL` an identity matrix is considered (default) thus G = K; otherwise G = Z K Z' is used
`K`	Kinship relationships matrix. This can be a name of a binary file where the matrix is stored. Only needed when a `fm` object of the class 'SSI' is provided
`indexK`	Vector of integers indicating which columns and rows will be read when `K` is the name of a binary file. Default `indexK=NULL` will read the whole matrix
`tst`	Vector of integers indicating which individuals are in testing set and must be contained in `fm$tst`. Default `tst=NULL` will consider the whole vector `fm$tst` to plot
`title`	A 'character' type string for the plot title
`maxCor`	Maximum correlation allowed for two different coefficients. A group of coeffcients with a correlation greater than `maxCor` are likely to overlap in the plot thus only one is kept

Marco Lopez-Cruz (lopezcru@msu.edu) and Gustavo de los Campos

  require(SFSI)
  data(wheatHTP)
  X = scale(X[1:300,])         # Subset and scale markers
  G = tcrossprod(X)/ncol(X)    # Genomic relationship matrix
  y = scale(Y[1:300,"YLD"])    # Subset response variable
  WL = scale(WL[1:300,])       # Reflectance data
  
  # Sparse phenotypic regression
  fm1 = lars2(var(WL),cov(y,WL))
  
  # Sparse family index
  fm2 = SSI(y,K=G,tst=1:15,trn=16:length(y))
  
  ## Not run: 
  plotPath(fm1)
  plotPath(fm2,maxCor=0.6)
  plotPath(fm2,K=G,maxCor=0.6)
  
## End(Not run)
  
  # Path plot for the first individual in testing set for the SSI
  plotPath(fm2,K=G,tst=fm2$tst[1])