plotly
This is an updated visualization function for ise.npEM
. For more technical details, please refer to ise.npEM
.
plotly_ise.npEM(npEMout, component=1, block=1, truepdf=dnorm, lower=-Inf,
upper=Inf, plots = TRUE ,
col = NULL , width = 3,
title = NULL , title.size = 15 , title.x = 0.5 , title.y = 0.95,
xlab = "t" , xlab.size = 15 , xtick.size = 15,
ylab = "" , ylab.size = 15 , ytick.size = 15,
legend.text = "" , legend.text.size = 15 , legend.size = 15, ...)
Just as for the integrate
function,
a list of class "integrate"
with components
the final estimate of the integral.
estimate of the modulus of the absolute error.
the number of subintervals produced in the subdivision process.
"OK"
or a character string giving the error message.
the matched call.
An object of class npEM
such as the output
of the npEM
function
Component and block of particular density to analyze
from npEMout
.
an R function taking a numeric first argument and returning a numeric vector of the same length. Returning a non-finite element will generate an error.
the limits of integration. Can be infinite.
logical: Should plots be produced?
additional arguments to be passed to truepdf
(and that may be mandatory like, e.g., the df =
argument of dt
).
Remember to use argument names not matching those of ise.npRM
.
Color of traces.
Line width of traces.
Text of the main title.
Size of the main title.
Horsizontal position of the main title.
Vertical posotion of the main title.
Label of X-axis.
Size of the lable of X-axis.
Size of tick lables of X-axis.
Label of Y-axis.
Size of the lable of Y-axis.
Size of tick lables of Y-axis.
Title of legend.
Size of the legend title.
Size of legend.
This function calls the wkde
(weighted kernel
density estimate) function.
Benaglia, T., Chauveau, D., and Hunter, D. R. (2009), An EM-like algorithm for semi- and non-parametric estimation in multivariate mixtures, Journal of Computational and Graphical Statistics, 18, 505-526.
Benaglia, T., Chauveau, D., Hunter, D. R., and Young, D. (2009), mixtools: An R package for analyzing finite mixture models. Journal of Statistical Software, 32(6):1-29.
npEM
, wkde
, integrate
, ise.npEM
if (FALSE) {
data(Waterdata)
set.seed(100)
a <- npEM(Waterdata[,3:10], mu0=3, bw=4) # Assume indep but not iid
plotly_ise.npEM(a , plots = TRUE)
}
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