estimate_marginal: Estimate marginal distribution using ML
In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials
estimate_marginal R Documentation
Estimate marginal distribution using ML
Description
estimate_marginal() estimates the marginal distribution specified by
marginal_Y using maximum likelihood. The optimizer is Newton-Raphson.
Usage
estimate_marginal(Y, marginal_Y, starting_values)
Arguments
Y
Observations (continuous)
marginal_Y
List with the following five elements (in order):
Density function with first argument x and second argument para the parameter
vector for this distribution.
Distribution function with first argument x and second argument para.
Inverse distribution function with first argument p and second argument para.
The number of elements in para.
Starting values for para.
starting_values
Starting values for marginal_Y
Value
Estimated parameters
Surrogate documentation built on April 11, 2025, 6:09 p.m.
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| estimate_marginal | R Documentation |
Estimate marginal distribution using ML
Description
estimate_marginal() estimates the marginal distribution specified by
marginal_Y using maximum likelihood. The optimizer is Newton-Raphson.
Usage
estimate_marginal(Y, marginal_Y, starting_values)
Arguments
Y |
Observations (continuous) |
marginal_Y |
List with the following five elements (in order):
|
starting_values |
Starting values for |
Value
Estimated parameters
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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