R: Optimal Designs for the 5-Parameter Logistic Model

# Optimal Designs for the 5-Parameter Logistic Model

## Documentation for package ‘Opt5PL’ version 0.1.1

- DESCRIPTION file

## Help Pages

c_weight | One iteration to run Newton Raphson to get c-optimal weights
c_weight_1 | The first derivative of the c-optimality criterion w.r.t the model parameters
c_weight_2 | The second derivative of the c-optimality criterion with respect to the model parameters
D1 | Computing each element of the function c_weight_1
d11 | Computing each element of the function DD_weight_1
DD1 | Computing each element of the function c_weight_2
dd11 | Computing each element of the function DD_weight_2
DD_weight | One iteration to run Newton Raphson to get Ds-optimal weights
DD_weight_1 | The first derivative of the Ds-optimality criterion with respect to the model parameters
DD_weight_2 | The second derivative of the Ds-optimality criterion with respect to the model parameters
Deff | Obtaining D-efficiency for estimating model parameters
Dp | Target dose, EDp
DS1 | Sensitivity function of c-optimality criterion for the EDp
ds11 | Sensitivity function of Ds-optimality criterion
Dseff | Obtaining Ds-efficiency for estimating the asymmetric factor under the 5-parameter logistic model.
DsOPT | Search Ds-optimal design for estimating the asymmetric factor under the 5-parameter logistic model.
D_weight | One iteration to run Newton Raphson to get D-optimal weights
D_weight_1 | The first derivative of the D-optimality criterion w.r.t the model parameters
D_weight_2 | The second derivative of the D-optimality criterion w.r.t the model parameters
EDpeff | Obtaining c-efficiency for estimating the EDp under the 5-parameter logistic model.
EDpOPT | Search c-optimal designs for estimating the EDp under the 5-parameter logistic model
f | Gradient of the mean function
g | Partial derivative of the EDp with respect to the model parameters
ginv | Generalized Inverse Matrix
infor | Obtain a information matrix at a single design point
Inv | Adjusting invere information matrix being not singular
Minus | Matrix subtraction
Multiple | Matrix multiplication
Plus | Matrix addition
RDOPT | Search the robust D-optimal designs for estimating model parameters
SDM | Summation of diagonal elements in a matrix
smalld1 | Sub-function of the function D_weight_1
smalldd1 | Sub-function of the function D_weight_2
smallds1 | Sensitivity function of D-optimality criterion
sMultiple | Multiply a constant to a matrix
S_weight | Newton Raphson method to get optimal weights
Trans | Transpose of a matrix
upinfor | Obtain normalized Fisher information matrix