Variance-based interaction index measuring heteroscedasticity

Total interaction index: A variance-based sensitivity index for second-order interaction screening

Sensitivity analysis aims at exploring which of a number of variables have an impact on a certain response. Not only are the individual variables of interest but also whether they interact or not. By analogy with the total sensitivity index, used to detect the most influential variables, a screening of interactions can be done efficiently with the so-called total interaction index (TII), define...

Measuring the interaction dimension of segregation: the Gini- Exposure index

We study the heterogeneity of social interaction profiles among individuals and define the extent of the interaction dimension of segregation. An interaction profile quantifies the probabilities that one individual has to interact with different social groups. It can be inferred, for instance, from observation of social ties through networks data. Heterogeneity is minimal if everybody exhibit t...

Semiparametric Estimation of Conditional Heteroscedasticity via Single-index Modeling.

We consider a single-index structure to study heteroscedasticity in regression with high-dimensional predictors. A general class of estimating equations is introduced, the resulting estimators remain consistent even when the structure of the variance function is misspecified. The proposed estimators also possess an adaptive property in an asymptotic sense. That is, they estimate the conditional...

A variance-based sensitivity index function for factor prioritization

Among the many uses for sensitivity analysis is factor prioritization—that is, the determination of which factor, once fixed to its true value, on average leads to the greatest reduction in the variance of an output. A key assumption is that a given factor can, through further research, be fixed to some point on its domain. In general, this is an optimistic assumption, which can lead to inappro...

Index for measuring health.