fun.plot.fit | R Documentation |
This function is designed for univariate generalised lambda distribution fits only.
fun.plot.fit(fit.obj, data, nclass = 50, xlab = "", name = "", param.vec,
ylab="Density", main="")
fit.obj |
Fitted object from |
data |
Dataset to be plotted. |
nclass |
Number of class of histogram, the default is 50. |
xlab |
Label on the x axis. |
name |
Naming the type of distribution fits. |
param.vec |
A vector describing the type of generalised lambda
distribution used in the |
ylab |
Label on the y axis. |
main |
Title of the graph. |
A graphical output showing the data and the resulting distributional fits.
If the distribution fits over fits the peak of the distribution, it can be difficult to see the actual data set.
Steve Su
fun.plot.fit.bm
, fun.data.fit.ml
,
fun.data.fit.hs
, fun.data.fit.hs.nw
,
fun.RPRS.ml
, fun.RMFMKL.ml
,
fun.RPRS.hs
, fun.RMFMKL.hs
,
fun.RPRS.hs.nw
, fun.RMFMKL.hs.nw
# Generate Normally distribute random numbers as dataset
junk<-rnorm(1000,3,2)
# Fit the data set using fun.data.fit.ml.
# Also, fun.data.fit.hs or fun.data.fit.hs.nw can be used.
obj.fit<-fun.data.fit.ml(junk)
# Plot the resulting fits
fun.plot.fit(obj.fit,junk,xlab="x",name=".ML",param.vec=c("rs","fmkl","fmkl"))
# This function also works for singular fits such as those by fun.RPRS.ml,
# fun.RMFMKL.ml, fun.RPRS.hs, fun.RMFMKL.hs, fun.RPRS.hs.nw, fun.RMFMKL.hs.nw
junk<-rnorm(1000,3,2)
obj.fit<-fun.RPRS.ml(junk)
fun.plot.fit(obj.fit,junk,xlab="x",name="RPRS.ML",param.vec=c("rs"))
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