fun.disc.estimation: Estimates the mean and variance after cutting up a vector of...
In GLDEX: Fitting Single and Mixture of Generalised Lambda Distributions
fun.disc.estimation R Documentation
Estimates the mean and variance after cutting up a vector of variable
into evenly spaced categories.
Description
This function supplements fun.nclass.e and it is not intended to
be used by the users directly.
Usage
fun.disc.estimation(x, nint)
Arguments
x
A vector of observations.
nint
Number of intervals to cut the vectors into.
Details
The function cuts the vector into evenly spaced categories and estimate
the mean and variance of
the actual data based on the categorisation.
Value
Two numerical values, the first being the mean and the second being the
variance.
Author(s)
Steve Su
See Also
fun.nclass.e
Examples
## Cut up a randomly normally distributed observations into 5 evenly spaced
## categories and estimate the mean and variance based on this cateogorisation.
junk<-rnorm(1000,3,2)
fun.disc.estimation(junk,5)
GLDEX documentation built on Aug. 21, 2023, 9:08 a.m.
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| fun.disc.estimation | R Documentation |
Estimates the mean and variance after cutting up a vector of variable into evenly spaced categories.
Description
This function supplements fun.nclass.e and it is not intended to
be used by the users directly.
Usage
fun.disc.estimation(x, nint)
Arguments
x |
A vector of observations. |
nint |
Number of intervals to cut the vectors into. |
Details
The function cuts the vector into evenly spaced categories and estimate the mean and variance of the actual data based on the categorisation.
Value
Two numerical values, the first being the mean and the second being the variance.
Author(s)
Steve Su
See Also
fun.nclass.e
Examples
## Cut up a randomly normally distributed observations into 5 evenly spaced
## categories and estimate the mean and variance based on this cateogorisation.
junk<-rnorm(1000,3,2)
fun.disc.estimation(junk,5)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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