pgsfit.obj is a S3 class to store PGS fitting results. Internally used by
grid.err: cross-validation error grid
lam.sel.vect: vector of selected lambda for each Pm
beta.shrink: list of beta after shrinkage for each Pm
var.sand: list of sandwich variance of beta for each Pm
hat.R: list of estimated working correlation matrix for each Pm
convergenceError: convergence error when iteration stopped for each Pm
iterationNumber: iteration times when converged for each Pm
which.best: index of the best Pm and lambda among convergent results
which.bestGlobal: index of the best Pm and lambda among all results (including non-convergent results)
convergenceThreshold: threshold of convergence error (i.e.
maxIteration: maximum iteration number allowed (i.e.
Pm.vect: working vector of tunning parameter Pm
lam.vect: working vector of tunning parameter lambda
scale.info: scaling information of y.vect, M, and COV to transfer beta estimate back to original scale
sis.name: name (id) of genomic mark from sure independent screening results, truncated at
convergeMessage: "Converged!", "Not converged!", or "Conditionally converged!
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pgsfit.obj(grid.err, lam.sel.vect, beta.shrink.corr.list, var.sand.corr.list, hat.R.list, flag.stop.corr.vect, iter.n.corr.vect, best.ind, bestall.ind, eps, iter.n, Pm.vect, lam.vect, scale.info, sis.dn, ConvergeMessage) ## S3 method for class 'pgsfit.obj' print(pgsfit.obj) ## S3 method for class 'pgsfit.obj' plot(pgsfit.obj, IQR.times = 1.5, text.size = 4, xlab.size = 14, ylab.size = 14) ## S3 method for class 'pgsfit.obj' coef(pgsfit.obj, pm.ind = NULL, p.threshold = 0.05, nonzero = TRUE)
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## Print PGS object: pgsfit.obj ## Plot PGS object (a heat map visualizes the grid search errors): plot(pgsfit.obj) #Other parameters: #IQR.times: cross-validation errors greater than IQR.times * IQR of the errors will be replaced by "NA" (represented by grey blocks). Default = 1.5. #text.size: size of the text in grid. Default = 4. #xlab.size: size of the x-axis labels. Default = 14. #ylab.size: size of the y-axis labels. Default = 14. ## Return coefficients from PGS object: coef(pgsfit.obj) #Other parameters: #whcih: an interger between 1 to pm.n specifying results at which Pm level to be returned. Defaul = NULL. If NULL, return the best results. #p.threshold: threshold of p-values to filter out non-significant variables. Default = 0.05. #nonzero: logical. If TRUE, only variables with non-zero beta results are returned. Default = TRUE. #For more information, please visit: https://github.com/YinanZheng/PGS/wiki/Example:-miRNA-expression-and-lung-function
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