R: Many exponential regressions

Many exponential regressions {Rfast} | R Documentation

## Many exponential regressions

### Description

Many exponential regressions.

### Usage

    expregs(y, x, di, tol = 1e-09, logged = FALSE)

### Arguments

`y` | A vector with positive data (including zeros).
`x` | A numerical matrix with the predictor variables.
`di` | A vector of size equal to that of y with 0s and 1s indicating censoring or not respectively.
`tol` | The tolerance value to stop the newton-Raphson iterations. It is set to 1e-09 by default.
`logged` | A boolean variable; it will return the logarithm of the pvalue if set to TRUE.

### Details

We have implemented the newton-Raphson in order to avoid unnecessary calculations.

### Value

A matrix with three columns, the test statistic, its associated (logged) p-value and the BIC of each model.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.

### References

McCullagh, Peter, and John A. Nelder. Generalized linear models. CRC press, USA, 2nd edition, 1989.

### See Also

`univglms, score.glms, logistic_only, poisson_only, regression`

### Examples

    ## 200 variables, hence 200 univariate regressions are to be fitted
    x <- matrnorm(100, 100)
    y <- rexp(100, 4)
    system.time( expregs(y, x, di = rep(1, length(y))) )
    x <- NULL

[Package Rfast version 2.0.0 Index]