D1                      Computing each element of the function
                        c_weight_1
DD1                     Computing each element of the function
                        c_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
DS1                     Sensitivity function of c-optimality criterion
                        for the EDp
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
Deff                    Obtaining D-efficiency for estimating model
                        parameters
Dp                      Target dose, EDp
DsOPT                   Search Ds-optimal design for estimating the
                        asymmetric factor under the 5-parameter
                        logistic model.
Dseff                   Obtaining Ds-efficiency for estimating the
                        asymmetric factor under the 5-parameter
                        logistic model.
EDpOPT                  Search c-optimal designs for estimating the EDp
                        under the 5-parameter logistic model
EDpeff                  Obtaining c-efficiency for estimating the EDp
                        under the 5-parameter logistic model.
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
S_weight                Newton Raphson method to get optimal weights
Trans                   Transpose of a matrix
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
d11                     Computing each element of the function
                        DD_weight_1
dd11                    Computing each element of the function
                        DD_weight_2
ds11                    Sensitivity function of Ds-optimality criterion
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
sMultiple               Multiply a constant to 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
upinfor                 Obtain normalized Fisher information matrix
