A diagonally switchable 4-cycle system of order n, briefly DS4CS(n), is a 4-cycle system in which by replacing each 4-cycle (a, b, c, d) covering pairs ab, bc, cd, da by either of the 4-cycles (a, c, b, d) or (a, b, d, c) another 4-cycle system is obtained. We prove that a DS4CS(n) exists if and only if n ≡ 1 (mod 8), n ≥ 17 with the possible exception of n = 17. AMS classification: 05B30

Abstract. Semiparametric model is a statistical model consisting of both parametric and nonparametric components, which can be looked on as a mixture model. The theoretical properties of this model have been studied extensively, such as large-sample property. However, most researches are based on scalar value, in which the dimension of the observation is one at each moment. In the fields of spa...

A method for lip tracking intended to support personal verification is presented in this paper. Lip contours are represented by means of quadratic Bsplines. The lips are automatically localised in the original image and an elliptic B-spline is generated to start up tracking. Lip localisation exploits grey-level gradient projections as well as chromaticity models to find the lips in an automatic...

A general methodology for modeling loss data depending on covariates is developed. The parameters of the frequency and severity distributions of the losses may depend on covariates. The loss frequency over time is modeled via a non-homogeneous Poisson process with integrated rate function depending on the covariates. This corresponds to a generalized additive model which can be estimated with s...

Many imputation methods are based on statistical models that assume that the variable of interest is a noisy observation of a function of the auxiliary variables or covariates. Misspecification of this model may lead to severe errors in estimates and to misleading conclusions. A new imputation method for item nonresponse in surveys is proposed based on a nonparametric estimation of the function...

Statistical shape models learn valid variability from example shapes, making large training sets favorable. Methods for automatic training set generation use transforms obtained by registration to propagate atlas landmarks to new samples. Algorithms based on B-spline transforms and mutual information (MI) were successfully employed for the cardiac anatomy in CT and MRI. For single-modality data...

Scientists need appropriate spatial-statistical models to account for the unique features of stream network data. Recent advances provide a growing methodological toolbox for modelling these data, but general-purpose statistical software has only recently emerged, with little information about when to use different approaches. We implemented a simulation study to evaluate and validate geostatis...

Head movements can greatly affect swallowing accelerometry signals. In this paper, we implement a spline-based approach to remove low frequency components associated with these motions. Our approach was tested using both synthetic and real data. Synthetic signals were used to perform a comparative analysis of the spline-based approach with other similar techniques. Real data, obtained data from...

This article proposes a new nonparametric procedure for estimating log spectra. This procedure consists of three major components: (1) a novel statistical model for modelling the unknown target log spectrum, (2) an AIC-based model selection criterion for choosing a ‘best’ 7tting model, and (3) a genetic algorithm for e8ectively searching the ‘best’ 7tting model. Numerical experiments are conduc...

We investigate posterior contraction rates for priors on multivariate functions that are constructed using tensor-product B-spline expansions. We prove that using a hierarchical prior with an appropriate prior distribution on the partition size and Gaussian prior weights on the Bspline coefficients, procedures can be obtained that adapt to the degree of smoothness of the unknown function up to ...