Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Parametric bootstrapping in a generalized extreme value regression model
  for binary response   Generalized extreme value (GEV) regression is often more adapted when we
investigate a relationship between a binary response variable $Y$ which
represents a rare event and potentiel predictors $\mathbf{X}$. In particular,
we use the quantile function of the GEV distribution as link function.
Bootstrapping assigns measures of accuracy (bias, variance, confidence
intervals, prediction error, test of hypothesis) to sample estimates. This
technique allows estimation of the sampling distribution of almost any
statistic using random sampling methods. Bootstrapping estimates the properties
of an estimator by measuring those properties when sampling from an
approximating distribution. In this paper, we fitted the generalized extreme
value regression model, then we performed parametric bootstrap method for
testing hupthesis, estimating confidence interval of parameters for generalized
extreme value regression model and a real data application.

4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
1
The categories of this paper are: cs
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
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The categories of this paper are: math
15
The categories of this paper are: nucl-ex