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LDOD (version 1.0)

Finding Locally D-optimal optimal designs for some nonlinear and generalized linear models.

Description

this package provides functions for Finding Locally D-optimal designs for Logistic, Negative Binomial, Poisson, Michaelis-Menten, Exponential, Log-Linear, Emax, Richards, Weibull and Inverse Quadratic regression models and also functions for auto-constructing Fisher information matrix and Frechet derivative based on some input variables and without user-interfere.

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Version

Install

install.packages('LDOD')

Monthly Downloads

4

Version

1.0

License

GPL (>= 2)

Maintainer

Ehsan Masoudi

Last Published

March 7th, 2013

Functions in LDOD (1.0)

eff

Calculation of D-efficiency with arbitrary precision
cfisher

Auto-constructing Fisher Information matrix
ldiq

Locally D-optimal designs for Inverse Quadratic model
ldexpdose

Locally D-optimal designs for Exponential dose-response model
ldloglin

Locally D-optimal designs for Log-linear model
ldnbinom

Locally D-optimal designs for Negative Binomial model
ldrichards

Locally D-optimal designs for Richards model
ldemax

Locally D-optimal designs for 3-parameter Emax model
LDOD-package

Finding Locally D-optimal optimal designs for some nonlinear and generalized linear models.
ldmm

Locally D-optimal designs for Michaelis-Menten model
ldpoisson

Locally D-optimal designs for Poisson model
cfderiv

Auto-constructing Frechet derivative of D-criterion based on general equivalence theorem
ldlogistic

Locally D-optimal designs for Logistic model
ldweibull

Locally D-optimal designs for Weibull model