g: moment function generator
In SonmezOzan/mmfit:
Description
If we need to estimate n parameters, we can use Moment Generating Function to get from E[x] to E[X^n] in order to obtain n equations
The value meanb is our estimate in the currently iteration of the mean of the beta distribution,
while x is our data. The gmm() function, in calling our g(), will calculate the average of m1 (m2, m3) over
all our data, and then in setting that average to 0, we are equating our parametric estimate of the
population mean to our sample mean, exactly what MM is supposed to do.
Usage
1
Arguments
type
the type of distribution. It take a value from "Poisson", "power law", "Gamma", "Beta", mixture of "2Poissons", and "2Exponential"
SonmezOzan/mmfit documentation built on May 9, 2019, 9:57 p.m.
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Description
If we need to estimate n parameters, we can use Moment Generating Function to get from E[x] to E[X^n] in order to obtain n equations The value meanb is our estimate in the currently iteration of the mean of the beta distribution, while x is our data. The gmm() function, in calling our g(), will calculate the average of m1 (m2, m3) over all our data, and then in setting that average to 0, we are equating our parametric estimate of the population mean to our sample mean, exactly what MM is supposed to do.
Usage
1 |
Arguments
type |
the type of distribution. It take a value from "Poisson", "power law", "Gamma", "Beta", mixture of "2Poissons", and "2Exponential" |
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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