climatic parameters in time and space scales of change are for many reasons of changes and how they should be based on observations using a statistical method to be determined. analysis of the most widely used statistical methods that assess potential climate change on hydrological time series, such series of precipitation, temperature and flow rate used. this study of 11 synoptic,rain gage and...

background : kernel smoothing method is a non-parametric or graphical method for statistical estimation. in the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. methods : by employing non-parametric regression methods, the curve estimation, may have some complexity.  in this article, four indices of epanechnikov, b...

background: colon cancer is the third cause of cancer deaths. although colon cancer survival time has increased in recent years, the mortality rate is still high. the cox model is the most common regression model often used in medical research in survival analysis, but most of the time the effect of at least one of the independent factors changes over time, so the model cannot be used. in the c...

In this paper, we discuss how to approximate the conditional expectation of a random variable Y given a random variable X, i.e. E(Y|X). We propose and compare two different non parametric methodologies to approximate E(Y|X). The first approach (namely the OLP method) is based on a suitable approximation of the σ-algebra generated by X. A second procedure is based on the well known kernel non-pa...

genotype by environment interaction is one of the most important subjects in crop improvement, so that different statistical measures have been proposed to estimate this interaction. in the present study, nine varieties and hybrids of spring rapeseed were evaluated in five warm dryland areas including sarpol-e-zahab, gonbad, gachsaran, pol-e-dukhtar and masjedsoliman in two growing seasons 2002...

Abstract We construct a new family of non-parametric statistical manifolds by means two-parameter class deformed exponential functions, that includes functions with power-law, linear and sublinear rates growth. The are modelled on weighted, mixed-norm Sobolev spaces especially suited to this purpose, in the sense an important nonlinear superposition operators (those used construction divergence...