glmTrain_fun {pathwayPCA} | R Documentation |
Model statistics for Generalized Linear Model (GLM) regression by gene
glmTrain_fun(x, y, family = binomial)
x |
An p \times n predictor matrix. |
y |
A response vector. |
family |
A description of the error distribution and link function to
be used in the model. The default is |
While this function currently supports any GLM family from the
family
function, this function is only called in the
model fitting step (via the internal superpc.train
) function
and not in the test statistic calculation step (in the
superpc.st
function). We would like to support Poisson
regression through the glm
function, as well as n-ary
classification through multinom
and ordinal logistic
regression through polr
.
The slope coefficient from the GLM for each gene.
# DO NOT CALL THIS FUNCTION DIRECTLY. # Use SuperPCA_pVals() instead ## Not run: p <- 500 n <- 50 x_mat <- matrix(rnorm(n * p), nrow = p, ncol = n) obs_logi <- sample( c(FALSE, TRUE), size = n, replace = TRUE, prob = c(0.2, 0.8) ) glmTrain_fun( x = x_mat, y = obs_logi ) ## End(Not run)