Internal 'mixtools' Functions

Internal kernel, semiparametric-related, and miscellaneous functions for the package mixtools.

Usage

dexpmixt(t, lam, rate)
HRkde(cpd, u = cpd[,1], kernelft = triang_wkde, 
      bw = rep(bw.nrd0(as.vector(cpd[,1])), length(cpd[,1])))
inv.logit(eta)
kern.B(x, xi, h, g = 0)
kern.C(x, xi, h)
kern.G(x, xi, h)
kern.O(x, xi, h)
kern.T(x, xi, h)
kfoldCV(h, x, nbsets = 2, w = rep(1, length(x)), 
        lower = mean(x) - 5*sd(x), upper = mean(x) + 5*sd(x))
KMintegrate(s) 
KMod(cpd, already.ordered = TRUE)
ldc(data, class, score)
logit(mu)
npMSL_old(x, mu0, blockid = 1:ncol(x),
          bw=bw.nrd0(as.vector(as.matrix(x))), samebw = TRUE,
          h=bw, eps=1e-8, maxiter=500, bwiter = maxiter,
          ngrid = 200, post = NULL, verb = TRUE)
plotseq(x, ...)
rlnormscalemix(n, lambda=1, meanlog=1, sdlog=1, scale=0.1)
splitsample(n, nbsets = 2)
triang_wkde(t, u=t, w=rep(1/length(t),length(t)), bw=rep(bw.nrd0(t), length(t)))
wbw.kCV(x, nbfold = 5, w = rep(1, length(x)), 
        hmin = 0.1*hmax, hmax = NULL)

Arguments

x: A vector of values to which local modeling techniques are applied.
xi: An n-vector of data values.
h: The bandwidth controlling the size of the window used for the local estimation around x. This pertains to its usage in the kernel functionns kern.B, kern.C, kern.G, kern.O, and kern.T. For its usage in the kfoldCV function, see updated arguments in the npMSL function.
g: A shape parameter required for the symmetric beta kernel. The default is g = 0 which yields the uniform kernel. Some common values are g = 1 for the Epanechnikov kernel, g = 2 for the biweight kernel, and g = 3 for the triweight kernel.
mu0: See updated arguments in the npMSL function.
blockid: See updated arguments in the npMSL function.
bw: See updated arguments in the npMSL function.
samebw: See updated arguments in the npMSL function.
eps: See updated arguments in the npMSL function.
maxiter: See updated arguments in the npMSL function.
bwiter: See updated arguments in the npMSL function.
ngrid: See updated arguments in the npMSL function.
post: See updated arguments in the npMSL function.
verb: See updated arguments in the npMSL function.
n: See updated arguments in the npMSL function.
nbsets: See updated arguments in the npMSL function.
w: See updated arguments in the npMSL function.
lower: See updated arguments in the npMSL function.
upper: See updated arguments in the npMSL function.
nbfold: See updated arguments in the npMSL function.
hmin: See updated arguments in the npMSL function.
hmax: See updated arguments in the npMSL function.
data: Data, possibly multivariate, fed to the mixturegram function.
class: The number of classes, inputted based on number of components in the mixturegram function.
score: The score vector from LDA used in constructing a mixturegram.
lam: A vector of mixture proportions, should sum to one.
rate: A vector of mixture component rates.
t: Argument for dexpmixt.
mu: A proportion for which to calculate the logit function; i.e., log(mu / (1 - mu)).
eta: Any real value for which to calculate the inverse logit function; i.e., 1 / (1 + exp(eta)).
cpd: Argument for HRkde.
kernelft: Argument for HRkde.
s: Argument for KMintegrate.
meanlog: Argument for rlnormscalemix.
sdlog: Argument for rlnormscalemix.

Details

These are usually not to be called by the user.

Usage

Arguments

Details

See also