ppmlasso-internal: Internal ppmlasso functions

In ppmlasso: Point Process Models with LASSO-Type Penalties

Internal ppmlasso functions

Description

These are internal functions called by the main functions of ppmlasso, but are not generally used directly by the user.

Usage

blocks(n.blocks, block.scale, dat, seed = 1)
calculateGCV(y, X, ob.wt, b.lasso, lambda, alpha = alpha, 
unp.likelihood = unp.likelihood, penalty = TRUE, family = "poisson", 
mu.min = 1.e-16, mu.max = 1.e16, eta.min = log(1.e-16), eta.max = log(1.e16),
tol = 1.e-9, area.int = FALSE)
calculateLikelihood(X, family, ob.wt, mu, y, alpha, lambda, beta, penalty = FALSE)
calculateUnpenalisedLikelihood(ob.wt, y, mu)
catConvert(env.frame)
catFrame(cat.mat)
decimalCount(x, max.dec = max(10, max(nchar(x))), tol = 0.1)
etaFromMu(mu, family, mu.min = 1.e-16, mu.max = 1/mu.min, eta.min, eta.max)
interp(sp.xy, sp.scale, f, back.xy, coord = c("X", "Y"))
irlsUpdate(y, X, ob.wt, is.in, signs, eta, mu, alpha, lambda, beta.old, 
penalty = FALSE, family, mu.min = 1.e-16, mu.max = 1/mu.min, eta.min, 
eta.max, tol = tol)
makeMask(dat.ppm)
muFromEta(eta, family, mu.min = 1.e-16, mu.max = 1/mu.min)
polyNames(X)
ppmSpatstat(fit)
scoreIntercept(y, X.des, ob.wt = rep(1, length(y)), area.int = FALSE, int = NA, family)
singleLasso(y, X, lamb, ob.wt = rep(1, length(y)), alpha = 1, b.init = NA,
intercept = NA, family = "gaussian", tol = 1.e-9, gamma = 0, init.coef = NA, 
mu.min = 1.e-16, mu.max = 1/mu.min, area.int = FALSE, interactions, max.it = 25,
standardise = TRUE)
spatRes(env.grid, coord = c("X", "Y"))
standardiseX(mat)
weights(sp.xy, quad.xy, coord = c("X", "Y"))
zapCoord(x, numdec = decimalCount(x))

Details

These are generally not called by the user.

Author(s)

Ian W. Renner

ppmlasso documentation built on Dec. 1, 2022, 5:09 p.m.