pv.contour.ic: Contour plot of prediction variance for a design with...
In ALTopt: Optimal Experimental Designs for Accelerated Life Testing

Description Usage Arguments Value See Also Examples

View source: R/ALTopt.R

pv.contour.ic draws the contour plot of prediction variance for a given design with interval censoring plan. Either useCond or use region (useLower and useUpper) should be provided.

1 2	pv.contour.ic(design, xAxis, yAxis, t, k, nf, alpha, formula, coef, useCond = NULL, useLower = NULL, useUpper = NULL)

`design`	the data frame containing the coordinates and the number of allocation of each design point. The design created by either `altopt.rc` or `altopt.ic` or any design matrix with the same form as those can be provided for this argument.
`xAxis`	the name of the factor to be displayed in x axis.
`yAxis`	the name of the factor to be displayed in y axis.
`t`	the total testing time.
`k`	the number of time intervals.
`nf`	the number of stress factors.
`alpha`	the value of the shape parameter of Weibull distribution.
`formula`	the object of class formula which is the linear predictor model.
`coef`	the numeric vector containing the coefficients of each term in `formula`.
`useCond`	the vector of specified use condition. If it is provided, the contour line will be generated up to this point.
`useLower,useUpper`	the vector of the use region. If these are provided, the contour line will be generated up to this region. Note that either `useCond` or both of `useLower, useUpper` should be provided.

The contour plot of prediction variance for interval censoring.

altopt.ic

## Not run: 
# Contour plot of prediction variance of U optimal design with interval censoring.
Design <- altopt.ic("D", 100, 30, 5, 2, 1, formula = ~ x1 + x2 + x1:x2,
coef = c(0, -4.086, -1.476, 0.01), useCond = c(1.758, 3.159))

pv.contour.ic(Design$opt.design.rounded, x1, x2, 30, 5, 2, 1,
formula = ~ x1 + x2 + x1:x2, coef = c(0, -4.086, -1.476, 0.01), useCond = c(1.758, 3.159))

## End(Not run)