k_ls: Preemption parameter estimation by least squares regression
In MLpreemption: Maximum Likelihood Estimation of the Niche Preemption Model
Description
Usage
Arguments
Value
Note
Author(s)
References
See Also
Examples
Description
Calculates the least-squares estimator for the geometric series.
Usage
1
k_ls(x)
Arguments
x
A vector of ordered counts (from large to small)
Value
khat
estimate of the preemption parameter
k.ll
lower limit of the confidence interval
k.ul
upper limit of the confidence interval
aic
Akaike's information criterion
logl
log-likelihoood
Note
counts should be ordered from large to small.
Author(s)
Jan Graffelman (jan.graffelman@upc.edu)
References
Magurran, A. 2004. Measuring biological diversity. Blackwell Publishing, Oxford, UK.
See Also
Examples
1
2
3
data("Ganeshaiah")
x <- Ganeshaiah[,2]
k_ls(x)
MLpreemption documentation built on Feb. 11, 2021, 5:07 p.m.
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.
Description Usage Arguments Value Note Author(s) References See Also Examples
Description
Calculates the least-squares estimator for the geometric series.
Usage
1 | k_ls(x)
|
Arguments
x |
A vector of ordered counts (from large to small) |
Value
khat |
estimate of the preemption parameter |
k.ll |
lower limit of the confidence interval |
k.ul |
upper limit of the confidence interval |
aic |
Akaike's information criterion |
logl |
log-likelihoood |
Note
counts should be ordered from large to small.
Author(s)
Jan Graffelman (jan.graffelman@upc.edu)
References
Magurran, A. 2004. Measuring biological diversity. Blackwell Publishing, Oxford, UK.
See Also
Examples
1 2 3 | data("Ganeshaiah")
x <- Ganeshaiah[,2]
k_ls(x)
|
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.