# spv: Calculate the Scaled Prediction Variance (or SPV) In vdg: Variance Dispersion Graphs and Fraction of Design Space Plots

 spv R Documentation

## Calculate the Scaled Prediction Variance (or SPV)

### Description

Calculates the SPV for a sample of points in a design region of specified type. Sampling is done by calling `sampler`.

### Usage

```spv(
n,
design,
type = "spherical",
formula,
at = FALSE,
keepfun,
sample,
unscaled = FALSE,
...
)

## S3 method for class 'data.frame'
spv(
n,
design,
type = c("spherical", "cuboidal", "lhs", "mlhs", "slhs", "rslhs", "custom"),
formula,
at = FALSE,
keepfun,
sample,
unscaled = FALSE,
...
)

## S3 method for class 'list'
spv(
n,
design,
type = c("spherical", "cuboidal", "lhs", "mlhs", "slhs", "rslhs", "custom"),
formula,
at = FALSE,
keepfun,
sample,
unscaled = FALSE,
...
)

## S3 method for class 'matrix'
spv(
n,
design,
type = c("spherical", "cuboidal", "lhs", "mlhs", "slhs", "rslhs", "custom"),
formula,
at = FALSE,
keepfun,
sample,
unscaled = FALSE,
...
)
```

### Arguments

 `n` number of samples to take `design` a design or list of designs. Each design must be either a matrix or a data.frame or coercible to a data.frame. `type` type of sampling passed to `sampler` `formula` either a single model formula of a list of formulae `at` only used when type is `'spherical'` or `'cuboidal'` `keepfun` optional; function operating on the columns of a matrix with the same number of columns as design which return a logical value for including a specific point in the sample or not. Useful for rejection sampling for nonstandard design regions. `sample` optional; if not missing it should contain a matrix or data.frame containing points sampled over the required design region. If it is not missing, no further sampling will be done: the SPV is simply evaluated at these points. `unscaled` logical indicating whether to use the unscaled prediction variance (UPV) instead of the scale prediction variance (SPV) `...` additional arguments passed to `sampler`. This enables the used of user-specified sampling functions via the `custom.fun` argument to `sampler`.

### Value

Object of class 'spv', 'spvlist', 'spvforlist' or 'spvlistforlist', depending on whether single designs/formulas are passed or lists of these.

### Author(s)

Pieter C. Schoonees

### References

Pieter C. Schoonees, Niel J. le Roux, Roelof L.J. Coetzer (2016). Flexible Graphical Assessment of Experimental Designs in R: The vdg Package. Journal of Statistical Software, 74(3), 1-22. doi: 10.18637/jss.v074.i03.

`plot.spv` for more examples

### Examples

```
# Single design (class 'spv')
library(rsm)
bbd3 <- as.data.frame(bbd(3)[,3:5])
colnames(bbd3) <- paste0("x", 1:3)
quad.3f <- formula(~(x1 + x2 + x3)^2 - x1:x2:x3)
out <- spv(n = 1000, design = bbd3, type = "spherical", formula = quad.3f)
out
```

vdg documentation built on July 8, 2022, 1:08 a.m.