# Data Mining Algorithms In R/Packages/gausspred/data gau

## Description edit

Data generation and processing.

## Usage edit

*gen_bayesgau (n,p,G,tau_nu=1,tau_mu=1,p_tau_x=c(2,1)).*

*order_features (features, response).*

## Arguments edit

*n*, the number of cases.

*p*, the number of features.

*G*, the number of groups.

*tau_nu*, the inverse of variance of Gaussian distribution for generating ν.

*tau_mu*, the inverse of variance of Gaussian distribution for generating µ.

*p_tau_x*, a vector of 2 numbers, specifying the Gamma distribution as prior for the inverse of the variance for the distribution of features, the ﬁrst number is shape, the second is rate.

*features*, the features, with the rows for the cases.

*response*, the response values.

## Value edit

The function gendata_bayesgau returns the following items:

*X*, the features, with the row standing for the cases.

*y*, the response values.

*mu*, the values of mu, with columns for groups.

*sigmas*, the variance generating features.

*nu*, the value of nu for features.

*vars*, the indice of features, in decreasing order of F-statistic.

*fstats*, the values of F-statistic for features indexed by vars.

## Example edit

data <- gen_bayesgau (n = 100,p = 100,G = 2, tau_nu=100,tau_mu = 100, p_tau_x = c(4,1)) i_sel <- order_features (data$X, data$y)