Random coe cient regression models have been applied in di erent elds and they constitute a unifying setup for many statistical problems. The nonparametric study of this model started with Beran and Hall (1992) and it has become a fruitful framework. In this paper we propose and study statistics for testing a basic hypothesis concerning this model: the constancy of coe cients. The asymptotic be...

Polyvinyl alcohol and calcium oxide composites appeared by casting technique. The calcium oxide added to polyvinyl alcohol with different weight percentages are (0,1,2 and 3) wt.%. Results showed that the absorbance increases with increase the weight percentage of calcium oxide. The absorption coefficient, extinction coefficient, refractive index and real and imaginary parts of dielectric const...

We propose in this work a generalization of the functional linear model in which an additional real variable influences smoothly the functional coefficient. This leads us to build a varying-coefficient regressionmodel for functional data. We propose two estimators based respectively on conditional functional principal regression and on local penalized regression splines and prove their pointwis...

C06FKF Circular convolution or correlation of two real vectors, extra workspace for greater speed C06FPF Multiple one-dimensional real discrete Fourier transforms C06FQF Multiple one-dimensional Hermitian discrete Fourier transforms C06FRF Multiple one-dimensional complex discrete Fourier transforms C06FUF Two-dimensional complex discrete Fourier transform C06FXF Three-dimensional complex discr...

Two general random intersection graph models (active and passive) were introduced by Godehardt and Jaworski (Exploratory Data Analysis in Empirical Research, Springer, Berlin, Heidelberg, New York, pp. 68–81, 2002). Recently the models have been shown to have wide real life applications. The two most important ones are: non-metric data analysis and real life network analysis. Within both contex...

We propose a novel method to generate scale-free networks with discretely tunable clustering coefficient in order to model real social networks. Recently several methods were introduced to generate networks with power law degree distribution. Most of them are based on preferential attachment, but in these networks the average clustering coefficient is low opposite to the real social networks. B...

We consider an N-dimensional real integral, indexed by a parameter that specifies the power of a Vandermonde determinant. For two particular values of the parameter, this integral arises from matrix integrals, over real symmetric and complex Hermitian N × N matrices. When it is normalized, it gives the expectation of an arbitrary power of the determinant. The results are given as finite summati...

In complex networks it is common to model a network or generate a surrogate network based on the conservation of the network’s degree distribution. We provide an alternative network model based on the conservation of connection density within a set of nodes. This density is measure by the rich–club coefficient. We present a method to generate surrogates networks with a given rich–club coefficie...