pareto_LTMPS: MPS estimation of the left-truncated Pareto distribution
In ckatom/ltmps: MPS estimation for left-truncated heavy-tailed data
Description
Usage
Arguments
Value
Examples
Description
Apply MPS estimation to the left-truncated Pareto distribution.
Usage
1
pareto_LTMPS(data, init_value, u)
Arguments
data
Empirical data that is left-truncated.
init_value
The initial value of left-truncated Pareto distributions parameter shape and scale.
u
The left truncated point.
Value
A list contains the estimation result of parameters shape and scale, standard error, and covariance matrix of estimated parameters.
Examples
1
2
3
4
data0=rpareto(30000,0.5,3)
data = data0[data0>5]
fit = pareto_LTMPS(data = data,init_value = c(0.6,2),u=5)
fit$par.ests
ckatom/ltmps documentation built on Jan. 8, 2022, 1:38 p.m.
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Description Usage Arguments Value Examples
Description
Apply MPS estimation to the left-truncated Pareto distribution.
Usage
1 | pareto_LTMPS(data, init_value, u)
|
Arguments
data |
Empirical data that is left-truncated. |
init_value |
The initial value of left-truncated Pareto distributions parameter shape and scale. |
u |
The left truncated point. |
Value
A list contains the estimation result of parameters shape and scale, standard error, and covariance matrix of estimated parameters.
Examples
1 2 3 4 | data0=rpareto(30000,0.5,3)
data = data0[data0>5]
fit = pareto_LTMPS(data = data,init_value = c(0.6,2),u=5)
fit$par.ests
|
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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