This function is similar to `print.feNmlm`

. It provides the table of coefficients along with other information on the fit of the estimation. It can compute different types of standard errors. The new variance covariance matrix is an object returned.

1 2 3 |

`object` |
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 |

`dof_correction` |
Logical. Should a finite sample correcton be applied? (Default is |

`...` |
Currently unused. |

The same values as a `feMmlm`

object plus:

`vcov` |
The variance-covariance matrix whose type is the one requested by the user. |

Laurent Berge

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
#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)
# Displaying the summary
summary(est0L,sd="white")
myWhiteVcov = summary(est0L,sd="white")$vcov
``` |

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