We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 62, No. 5 (NOVEMBER 2013), pp. 723-740 (18 pages) We explore a particular fully parametric approach to quantile regression ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

This is a preview. Log in through your library . Abstract The connection between the nonparametric problem of estimating an unknown continuous (or discrete) distribution function and the parametric ...

Parametric tests make assumptions that aspects of the data follow some sort of theoretical probability distribution. Non-parametric tests or distribution free methods do not, and are used when the ...

We have performed a genome scan using 25 nuclear families consisting of right-handed parents with at least two left-handed children. Handedness was assessed as a qualitative trait using a laterality ...