A note on the limit behaviour of extremal order statistics.
A note on the matrix Haffian.
This note contains a transparent presentation of the matrix Haffian. A basic theorem links this matrix and the differential ofthe matrix function under investigation, viz ∇F(X) and dF(X).Frequent use is being made of matrix derivatives as developed by Magnus and Neudecker.
A Note on the Maximum Probability Property of MLE's in Multiparameter Exponential Families.
A Note on the Multiple Indicator-Multiple Cause Model with Sevweral Latent Variables
A Note on the Optimality of k-Stage Tests.
A Note on the PARETO Distribution.
A note on the Poisson disorder problem
A note on the properties of generalised separable spatial autoregressive process.
A note on the rate of convergence of local polynomial estimators in regression models
Local polynomials are used to construct estimators for the value of the regression function and the values of the derivatives in a general class of nonparametric regression models. The covariables are allowed to be random or non-random. Only asymptotic conditions on the average distribution of the covariables are used as smoothness of the experimental design. This smoothness condition is discussed in detail. The optimal stochastic rate of convergence of the estimators is established. The results...
A note on the relations between two ternary balanced block designs and chemical balance weighing designs
The paper studied the problem of estimating of the weights of p objects in n weighings using a chemical balance weighing design under the restriction on the number of objects which can be placed on the right and left pans, respectively. Conditions under which the estimated weights are uncorrelated are given. The incidence matrices of two ternary balanced block designs which are used to construct chemical balance weighing designs satisfying these conditions are considered.
A note on the strong consistency of least squares estimates
The strong consistency of least squares estimates in multiples regression models with i.i.d. errors is obtained under assumptions on the design matrix and moment restrictions on the errors.
A note on the tail accuracy of the univariate saddlepoint approximation
A note on the third-order moment structure of bilinear model with non-independent shocks.
A Note on the Uniform Distribution on the Arcsin Points.
A Note on Three-Stage Confidence Intervals for the Difference of Locations: The Exponential Case.
A Note On Two-Units Standby Systems
A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization
This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained...
A novel robust principal component analysis method for image and video processing
The research on the robust principal component analysis has been attracting much attention recently. Generally, the model assumes sparse noise and characterizes the error term by the -norm. However, the sparse noise has clustering effect in practice so using a certain -norm simply is not appropriate for modeling. In this paper, we propose a novel method based on sparse Bayesian learning principles and Markov random fields. The method is proved to be very effective for low-rank matrix recovery...
A one-way ANOVA test for functional data with graphical interpretation
A new functional ANOVA test, with a graphical interpretation of the result, is presented. The test is an extension of the global envelope test introduced by Myllymäki et al. (2017, Global envelope tests for spatial processes, J. R. Statist. Soc. B 79, 381-404, doi: 10.1111/rssb.12172). The graphical interpretation is realized by a global envelope which is drawn jointly for all samples of functions. If a mean function computed from the empirical data is out of the given envelope, the null hypothesis...
A penalized bandit algorithm.