# OrderComparisons: Functions to perform simple order comparisons In adaptTest: Adaptive two-stage tests

## Description

These functions perform simple order comparisons for two arguments, dealing with the machine inaccuracy for floating point arithmetics.

## Usage

 ```1 2 3 4 5 6``` ```eq(x, y, tol = .Machine\$double.eps^0.5) ne(x, y, tol = .Machine\$double.eps^0.5) ge(x, y, tol = .Machine\$double.eps^0.5) gt(x, y, tol = .Machine\$double.eps^0.5) le(x, y, tol = .Machine\$double.eps^0.5) lt(x, y, tol = .Machine\$double.eps^0.5) ```

## Arguments

 `x` first argument (must be a numeric scalar) `y` second argument (must be a numeric scalar) `tol` comparison tolerance; differences smaller than `tol` are not considered.

## Details

When comparing two numeric scalars (e.g., for equality), machine inaccuracy can be the source of obviously erroneous results. These functions perform binary order comparisons that are tolerant towards machine inaccuracy, as an alternative to the standard comparators `==`, `!=`, `>=`, `>`, `<=` and `<`.

## Value

The functions return a logical `TRUE` if their condition holds, and a logical `FALSE` otherwise.

`eq(x, y)` checks whether `x` is equal to `y`

`ne(x, y)` checks whether `x` is not equal to `y`

`ge(x, y)` checks whether `x` is greater than or equal to `y`

`gt(x, y)` checks whether `x` is greater than `y`

`le(x, y)` checks whether `x` is less than or equal to `y`

`lt(x, y)` checks whether `x` is less than `y`

## Note

These functions cannot be used in a vectorized fashion.

## Author(s)

Marc Vandemeulebroecke

`identical`, `all.equal`
 ```1 2 3``` ``` v <- seq(0.7, 0.8, by=0.1) v[2]==0.8 eq(v[2], 0.8) ```