Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure-response relationship. Here we develop the family of distributed lag non-linear models (DLNM), a modelling framework that can simultaneously represent non-linear exposure-response dependencies and delayed ...

in dea to obtain an efficient representation in ccr andbcc models for each dmu only one linear plan would be solved; however,it is possible in centralized resource allocation (cra) to solve allthe dmus by one linear planning. in this paper, models of centralizedresource allocation in input-oriented and in dynamic case will be offeredand by using dynamic sbm, the representation of dmus in each t...

The statistical methodology for the design and analysis of clinical Phase II dose-response studies, with related software implementation, is well developed for the case of a normally distributed, homoscedastic response considered for a single timepoint in parallel group study designs. In practice, however, binary, count, or time-to-event endpoints are encountered, typically measured repeatedly ...

in this research genetic and phenotypic parameters were estimated using linear and threshold models, for reproductive traits, data from 6 large industrial dairy herd of east azerbaijan province collected by agriculture jihad organization during 10 years (2001-2010). best linear unbiased predictions of traits breeding values were estimated using restricted maximum likelihood method by wombat sof...

The aim of this paper is to propose some diagnostic methods in linear ridge measurement error models with stochastic linear restrictions using the corrected likelihood. Based on the bias-corrected estimation of model parameters, diagnostic measures are developed to identify outlying and influential observations. In addition, we derive the corrected score test statistic for outliers detection ba...

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

Partial linear model is very flexible when the relation between the covariates and responses, either parametric and nonparametric. However, estimation of the regression coefficients is challenging since one must also estimate the nonparametric component simultaneously. As a remedy, the differencing approach, to eliminate the nonparametric component and estimate the regression coefficients, can ...

We formulate and study analytically and computationally two families of piecewise linear degree one circle maps. These families offer the rare advantage of being non-trivial but essentially solvable models for the phenomenon of mode locking and the quasiperiodic transition to chaos. For instance, for these families, we obtain complete solutions to several questions still largely unanswered for ...

We have recently proposed a dual-route model of the effect of head orientation on perceived gaze direction (Otsuka, Mareschal, Calder, & Clifford, 2014; Otsuka, Mareschal, & Clifford, 2015), which computes perceived gaze direction as a linear combination of eye orientation and head orientation. By parametrically manipulating eye orientation and head orientation, we tested the adequacy of a line...