Background Sperm preparation before assisted reproductive techniques is very important for obtaining successful fertilization and pregnancy. During ICSI technique, sperms are selected based on viability and morphology. But this selection did not guarantee integrity of sperm DNA. Therefore, novel sperm selection procedures are introduced for selection of sperm with low DNA damage. One of these p...

An important task in the application of Markov models to the analysis of ion channel data is the determination of the correct gating scheme of the ion channel under investigation. Some prior knowledge from other experiments can reduce significantly the number of possible models. If these models are standard statistical procedures nested like likelihood ratio testing, provide reliable selection ...

Abstract This paper explores forecasting using model selection and model averaging and attempts to draw conclusion both in the context of stationarity and non-stationarity. Model averaging tends to be viewed as a polar opposite of model selection; often the motivation for averaging is to avoid the pitfalls of selecting models. However, selection cannot be avoided since every possible model cann...

Semiparametric regression models are very useful for longitudinal data analysis. The complexity of semiparametric models and the structure of longitudinal data pose new challenges to parametric inferences and model selection that frequently arise from longitudinal data analysis. In this article, two new approaches are proposed for estimating the regression coefficients in a semiparametric model...

Model selection procedures often use a fixed penalty, such as Mallows’ Cp, to avoid choosing a model which fits a particular data set extremely well. These procedures are often devised to give an unbiased risk estimate when a particular chosen model is used to predict future responses. As a correction for not including the variability induced in model selection, generalized degrees of freedom i...

behaviour of the dilution characteristics of the coastal waters off tuticorin is presented in thebackground of setting up of a desalination plant. simulations of dispersion and spreading of the proposeddischarges has been carried out. scenarios of dilutions were assessed based on the results of a 2d model using the advection-dispersion theory. it is observed that under prevailing currents in th...

It is common practice in statistical data analysis to perform datadriven variable selection and derive statistical inference from the resulting model. Such inference enjoys none of the guarantees that classical statistical theory provides for tests and confidence intervals when the model has been chosen a priori. We propose to produce valid “post-selection inference” by reducing the problem to ...

A class of variable selection procedures for parametric models via nonconcave penalized likelihood was proposed in Fan and Li (2001a). It has been shown there that the resulting procedures perform as well as if the subset of significant variables were known in advance. Such a property is called an oracle property. The proposed procedures were illustrated in the context of linear regression, rob...

Although there are disadvantages associated with model building procedures such as backward, forward and stepwise procedures (e.g. multiple testing, arbitrary significance level used in dropping or acquiring variables), many analysts use these procedures and are not aware that alternative modeling selection methods exist. This paper focuses on model selection using the Akaike Information Criter...