asympt.var: Compute the asymptotical variance-covariance (AVAR) matrix of...
In ULL-STAT/RepetPlan: Repetitive Design of Failure-Censored Sampling Plans with Prior Distribution
Description
Usage
Arguments
Value
Examples
Description
This function calculates the AVAR matrix of the maximum likelihood estimators of the location and scale
parameters of normal and extreme value distributions.
Usage
1
asympt.var(q, dist = "normal")
Arguments
q
Censoring degree (0 ≤ q < 1)
dist
Location and scale distribution name ("normal"= normal, "ev" = extreme-value).
Default value is "normal".
Value
A list composed by q (censoring degree), dist (distribution) and mat (AVAR matrix of parameters estimators computed as the inverse of the Fisher information matrix).
Examples
1
asympt.var(0.5)
ULL-STAT/RepetPlan documentation built on Dec. 18, 2021, 5:15 p.m.
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Description Usage Arguments Value Examples
Description
This function calculates the AVAR matrix of the maximum likelihood estimators of the location and scale parameters of normal and extreme value distributions.
Usage
1 | asympt.var(q, dist = "normal")
|
Arguments
q |
Censoring degree (0 ≤ q < 1) |
dist |
Location and scale distribution name ("normal"= normal, "ev" = extreme-value). Default value is "normal". |
Value
A list composed by q (censoring degree), dist (distribution) and mat (AVAR matrix of parameters estimators computed as the inverse of the Fisher information matrix).
Examples
1 | asympt.var(0.5)
|
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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