mvbfit {MVB} | R Documentation |
fit multivariate Bernoulli logistic model using Newton-Raphson algorithm.
mvbfit(x, y, maxOrder = 2, output = 0, printIter = 100)
x |
input design matrix. |
y |
output binary matrix with number of columns equal to the number of outcomes per observation. |
maxOrder |
maximum order of interactions to be considered in outcomes. |
output |
with values 0 or 1, indicating whether the fitting process is muted or not. |
printIter |
Number of iterations to be printed if output is true. |
The mvbfit
utilize the class structure of the underlying C++
code and fitted the model with Newton-Raphson algorithm.
An object of class mvbfit
, for which some methods are
available.
mvblps
, unifit
, stepfit
, mvb.simu
# fit a simple MVB log-linear model n <- 1000 p <- 5 kk <- 2 tt <- NULL alter <- 1 for (i in 1:kk) { vec <- rep(0, p) vec[i] <- alter alter <- alter * (-1) tt <- cbind(tt, vec) } tt <- 1.5 * tt tt <- cbind(tt, c(rep(0, p - 1), 1)) x <- matrix(rnorm(n * p, 0, 4), n, p) res <- mvb.simu(tt, x, K = kk, rep(.5, 2)) fitMVB <- mvbfit(x, res$response, output = 1)