in this paper, presenting two simple methods for ranking of efficient dmus in dea models that included to add one virtual dmu as ideal dmu and is using the additive model. note that, we use an ideal point just for comparing efficient dmus with. although these methods are simple, they have ability for ranking all efficient dmus, extreme points and the others, also they are capable of ranking the...

The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate ...

The density of minke whales (Balaenoptera acutorostrata) in the western North Pacific was examined using a generalized additive model order to investigate spatial and temporal distribution patterns. data used were subset JARPN sightings collected from 1994 1999. process for estimating divided into two parts: detection estimation effective search half-width; encounter rate. Model selection carri...

In spline regression models, the smoothness of the tted model depends on the knots via their location and how many knots there are. An alternative to knot selection is to keep all the knots, but to restrict their in uence on the tted model, that is, to constrain the values of these coe cients which correspond to the spline basis functions. For example, we can bound the squared L2 norm by some c...

The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as linearity of the predictor or the proportional hazards property. Also, one is often interested in jointly estimating the baseline hazard together ...

Recurrent events data are rising in all areas of biomedical research. We present a model for recurrent events data with the same link for the intensity and mean functions. Simple interpretations of the covariate effects on both the intensity and mean functions lead to a better understanding of the covariate effects on the recurrent events process. We use partial likelihood and empirical Bayes m...

Graphical methods for model diagnostics are an essential part of the model fitting procedure. However, in survival analysis, the plotting is always hampered by the presence of censoring. Although model specific solutions do exist and are commonly used, we present a more general approach that covers all the models using the same framework. The pseudo-observations enable us to calculate residuals...

Consider the model φ(S(z|X)) = β(z)t ~ X, where φ is a known link function, S(·|X) is the survival function of a response Y given a covariate X, ~ X = (1,X,X2, . . . ,Xp) and β(z) = (β0(z), . . . , βp(z)) t is an unknown vector of time-dependent regression coefficients. The response is subject to left truncation and right censoring. Under this model, which reduces for special choices of φ to e....