Functional quadratic regression models postulate a polynomial relationship rather than linear one between scalar response and functional covariate. As in regression, vertical especially high–leverage outliers may affect the classical estimators. For that reason, providing reliable estimators such situations is an important issue. Taking into account model equivalent to of same order principal c...

using monthly test day records the genetic parameters of iranian holstein cattle in first lactation were studied. data of 277400 test-day milk records from 65320 cows and 2210 sires were analyzed by an animal random regression model using restricted maximum likelihood methodology. the model included herd-test-date, interaction between year-season of calving, days in milk (linear and quadratic) ...

We consider support recovery in the quadratic logistic regression setting – where the target depends on both p linear terms xi and up to p quadratic terms xixj . Quadratic terms enable prediction/modeling of higher-order effects between features and the target, but when incorporated naively may involve solving a very large regression problem. We consider the sparse case, where at most s terms (...

Using monthly test day records the genetic parameters of Iranian Holstein cattle in first lactation were studied. Data of 277400 test-day milk records from 65320 cows and 2210 sires were analyzed by an animal random regression model using restricted maximum likelihood methodology. The model included herd-test-date, interaction between year-season of calving, days in milk (linear and quadratic) ...

a number of 5558 lambing records of 2245 mehraban ewes, collected during years 1995 to 2010 were utilized to estimate the variance components and heritability for the number of lambs per lambing,  making use of b-spline random regression models. the fixed factors affecting the studied trait were identified using general linear model analysis as well as sas software, where flock-year-season and ...

Quadratic regression goes beyond the linear model by simultaneously including main effects and interactions between covariates. The problem of interaction estimation in high dimensional quadratic has received extensive attention past decade. In this article we introduce a novel method which allows us to estimate separately. Unlike existing methods for ultrahigh regressions, our proposal does no...