calc_phiA | R Documentation |

Calculate the loss function of the A-optimal design

```
calc_phiA(design, theta, FUN, tt, A)
```

`design` |
The resulted design that contains the design points and the associated weights |

`theta` |
The parameter value of the model |

`FUN` |
The function to calculate the derivative of the given model. |

`tt` |
The level of skewness |

`A` |
The calculated covariance matrix |

This function calculates the loss function of the design problem under the A-optimality. The loss function under A-optimality is defined as the trace of the inverse of the Fisher information matrix

The loss of the model at each design points

```
my_design <- data.frame(location = c(0, 180), weight = c(1/2, 1/2))
theta <- c(0.05, 0.5)
peleg <- function(xi, theta){
deno <- (theta[1] + xi * theta[2])^2
rbind(-xi/deno, -xi^2/deno)
}
A <- matrix(c(1, 0, 0, 0, 0.2116, 1.3116, 0, 1.3116, 15.462521), byrow = TRUE, ncol = 3)
res <- calc_phiA(my_design, theta, peleg, 0, A)
res
```

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