Internal kernel, semiparametric-related, and miscellaneous functions for the package mixtools
.
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)
A vector of values to which local modeling techniques are applied.
An n-vector of data values.
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.
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.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
See updated arguments in the npMSL
function.
Data, possibly multivariate, fed to the mixturegram
function.
The number of classes, inputted based on number of components in the mixturegram
function.
The score vector from LDA used in constructing a mixturegram.
A vector of mixture proportions, should sum to one.
A vector of mixture component rates.
Argument for dexpmixt
.
A proportion for which to calculate the logit function; i.e., log(mu / (1 - mu))
.
Any real value for which to calculate the inverse logit function;
i.e., 1 / (1 + exp(eta))
.
Argument for HRkde
.
Argument for HRkde
.
Argument for KMintegrate
.
Argument for rlnormscalemix
.
Argument for rlnormscalemix
.
These are usually not to be called by the user.
npMSL