# forward

From statmod v1.4.32
by Gordon Smyth

##### Forward Selection of Covariates for Multiple Regression

Fit a multi-group negative-binomial model to SAGE data, with Pearson estimation of the common overdispersion parameter.

- Keywords
- regression

##### Usage

`forward(y, x, xkept=NULL, intercept=TRUE, nvar=ncol(x))`

##### Arguments

- y
numeric response vector.

- x
numeric matrix of covariates, candidates to be added to the regression.

- xkept
numeric matrix of covariates to be included in the starting regression.

- intercept
logical, should an intercept be added to

`xkept`

?- nvar
integer, number of covariates from

`x`

to add to the regression.

##### Details

This function has the advantage that `x`

can have many more columns than the length of `y`

.

##### Value

Integer vector of length `nvar`

, giving the order in which columns of `x`

are added to the regression.

##### See Also

##### Examples

```
# NOT RUN {
y <- rnorm(10)
x <- matrix(rnorm(10*5),10,5)
forward(y,x)
# }
```

*Documentation reproduced from package statmod, version 1.4.32, License: GPL-2 | GPL-3*

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