# A print facility for feNmlm objects. It can compute different types of standard errors.

### Description

This function is very similar to usual `summary`

functions as it provides the table of coefficients along with other information on the fit of the estimation.

### Usage

1 2 |

### Arguments

`x` |
A feNmlm object. |

`sd` |
Character scalar. Which kind of standard error should be prompted: “standard” (default), “White”, or “cluster”? |

`cluster` |
A list of vectors. Used only if |

`...` |
Currently unused. |

### Author(s)

Laurent Berge

### See Also

See also `feNmlm`

.

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
#The data
n = 100
x = rnorm(n,1,5)**2
y = rnorm(n,-1,5)**2
z = rpois(n,x*y)
base = data.frame(x,y,z)
#Comparing the results of a 'linear' function
est0L = feNmlm(z~0,base,~log(x)+log(y),family="poi")
est0NL = feNmlm(z~a*log(x)+b*log(y),base,start = list(a=0,b=0),
family="poisson", linear.fml=~1)
print(est0L)
print(est0NL)
#Generating a non-linear relation
z2 = rpois(n,x + y)
base$z2 = z2
#Using a non-linear form
est1L = feNmlm(z2~0,base,~log(x)+log(y),family="poi")
est1NL = feNmlm(z2~log(a*x + b*y),base,start = list(a=1,b=2),family="poisson")
``` |