gam.iso {UCS} | R Documentation |

Computes iso-surfaces for a generalised association measure (GAM) in standard or ebo-coordinates.

gam.iso(name, gamma, f1, f2, N, bsearch.min=NULL, bsearch.max=NULL) gam.iso(name, gamme, e, b=1, N=1e6, bsearch.min=NULL, bsearch.max=NULL)

`name` |
name of a generalised association measure (GAM) |

`gamma` |
a numerical constant that determines the desired
iso-surface \{g = γ\} |

`f1, f2, N` |
numerical vectors specifying the `f1` and
`f2` coordinates of points in the standard coordinate space, as
well as the sample size `N` |

`e, b` |
numerical vectors specifying the `e` and `b`
coordinates of points in the ebo-coordinate space (if the
balance b is not specified, it defaults to `1` ) |

`N` |
optional numerical vector specifying the sample size N
when computing iso-surfaces for a GAM that is not size-invariant in
ebo-coordinates (defaults to `1e6` ) |

`bsearch.min` |
initial lower boundary for binary search algorithm, when no explicit equation for the iso-surface is available |

`bsearch.max` |
initial upper boundary for the binary search algorithm |

Note that all function arguments except for `name`

must be passed
explicitly by name in order to distinguish the two operating modes of
`gam.iso`

(standard vs. ebo-coordinates).

When ebo-coordinates are used, the argument `N`

(*sample
size*) can safely be omitted for any size-invariant GAM (in
ebo-coordinates). For other GAMs, a default value of `1e6`

will
be used, corresponding to the typical size of a co-occurrence data
set. The argument `b`

(*balance*) can be omitted for any
central GAMs. Otherwise, it defaults to a value of `1`

,
corresponding to the centralized version of the respective GAM.

Use `gamma.nbest`

to compute a suitable *γ* values for
n-best surfaces.

When no explicit equation for the iso-surface of a GAM is available,
the `gam.iso`

function uses a binary search algorithm to solve
the implicit equation *\{g = γ\}*. Since some GAMs are only
defined for valid frequency signatures (where all four cells of the
contingency table are non-negative), the binary search for the
`o`

coordinate is confined to the range from *0* to
*\min\{f_1, f_2\}*. When no solution can be found in this range,
`gam.iso`

returns `NA`

for the corresponding points. For
GAMs where it is safe to search a larger range (notably
`Poisson.pv`

and `log.likelihood`

), the boundaries of the
search interval can be adjusted with the `bsearch.min`

and
`bsearch.max`

parameters. Note that most other GAMs have
explicit iso-equations, so these parameters are rarely needed.

a vector of real numbers representing the `f`

or `o`

coordinates of the respective iso-surface; these are the values of
`f`

or `o`

that solve the implicit equation *\{g =
γ\}* for the specified values of `f1, f2, N`

or `e, b`

(and `N`

); this vector may contain missing values (`NA`

) for
points where no solution is found (see "Details" for more information)

`gam.score`

, `builtin.gams`

, `gamma.nbest`

e <- 10^seq(-2, 1, .1) # compute iso-line on logarithmic scale o <- gam.iso("t.score", 2, e=e) x <- 10^seq(0, 2, .1) # compute iso-surface over rectangular grid g <- expand.grid(f1=x, f2=x) g$f <- gam.iso("t.score", 2, f1=g$f1, f2=g$f2, N=1000) library(lattice) wireframe(f ~ f1 * f2, log(g))

[Package *UCS* version 0.5 Index]