densityEst: Density estimation using logspline approach

In ThilakshaSilva/densityEst: Estimates a time series of density functions using logspline approach

Description

It nonparametrically estimates a time series of density functions using logspline approach considering the time ordering of the densities.

Usage

densityEst(y, x, ymargin, lbound, ubound, K, nymargin = 1000, log = TRUE,
  graphics = TRUE)

Arguments

y	a time series of data
x	a sequence of numbers from 1 to n where n is the number of time series
ymargin	data interval in the y-direction
lbound	lower bound for the support for the density
ubound	upper bound for the support for the density
K	number of initial number of knots
nymargin	desired length of the seqence
log	Does the logarithmic transformation apply to data? Default is TRUE.
graphics	A logical argument for plots

Examples

l <- 20
n <- 2000
z <- seq(1000,5000,length.out=n)
mean <- seq(mean(z)-400,mean(z)+200,length.out=l)
sd <- seq(200,400,length.out=l)
y <- lapply(1:l, function(X) rnorm(z,mean[X],sd[X]))
x <- c(1:l)
densityEst(y,x)

ThilakshaSilva/densityEst documentation built on May 20, 2019, 8:47 a.m.