# lol.sims.cross: Cross In lolR: Linear Optimal Low-Rank Projection

## Description

A simulation for the cross experiment, in which the two classes have orthogonal covariant dimensions and the same means.

## Usage

 `1` ```lol.sims.cross(n, d, rotate = FALSE, priors = NULL, a = 1, b = 0.25, K = 2) ```

## Arguments

 `n` the number of samples of simulated data. `d` the dimensionality of the simulated data. `rotate` With random rotataion matrix `Q`, `mu = Q*mu`, and `S = Q*S*Q`. Defaults to `FALSE`. `priors` the priors for each class. If `NULL`, class priors are all equal. If not null, should be `|priors| = K`, a length `K` vector for `K` classes. Defaults to `NULL`. `a` scalar for the magnitude of the variance that is high within the particular class. Defaults to `1`. `b` scalar for the magnitude of the varaince that is not high within the particular class. Defaults to `2`. `K` the number of classes. Defaults to `2`.

## Value

A list of class `simulation` with the following:

 `X` `[n, d]` the `n` data points in `d` dimensions as a matrix. `Y` `[n]` the `n` labels as an array. `mus` `[d, K]` the `K` class means in `d` dimensions. `Sigmas` `[d, d, K]` the `K` class covariance matrices in `d` dimensions. `priors` `[K]` the priors for each of the `K` classes. `simtype` The name of the simulation. `params` Any extraneous parameters the simulation was created with.

## Details

For more details see the help vignette: `vignette("sims", package = "lolR")`

Eric Bridgeford

## Examples

 ```1 2 3``` ```library(lolR) data <- lol.sims.cross(n=200, d=30) # 200 examples of 30 dimensions X <- data\$X; Y <- data\$Y ```

lolR documentation built on July 8, 2020, 7:35 p.m.