Mortality modelling is a practical method for the government and various fields to obtain picture of mortality up specific age particular year. However, some information on phenomenon may remain in residual vector be unrevealed from models. We handle this issue by employing multivariate control chart discover substantial cohort changes behavior that models still need address. The Hotelling T2 a...

Abstract In environmental surveillance, cluster detection of black spots is major interest due to the adverse health effects pollutants, as well their known synergistic effect. Thus, this paper introduces three new spatial scan statistics for multivariate functional data, applicable detecting clusters abnormal air pollutants concentrations measured spatially at a very fine scale in northern Fra...

BACKGROUND In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence.We use zero-mean unit variance normalization, prior ...

Voxel-based analyses of tissue characteristics such as volume and T2 are usually carried out in isolation. However, as the images are analysed in a common voxel-based framework, it is possible to directly assess the spatial relationships of abnormalities detected by each technique. We utilize this approach in well-characterized patients with unilateral temporal lobe epilepsy (TLE) with hippocam...

OBJECTIVE Receiver operating characteristic (ROC) methodology was used to compare the performance of different statistics in the automatic detection of multiple auditory steady-state responses (MSSR) and click auditory brainstem responses (cABR). STUDY SAMPLE Thirty-five healthy newborns tested within the first two weeks of birth. DESIGN In each case cABR and MSSR (0.5 and 2 kHz) were recor...

This paper presents a novel methodology to detect a set of more suitable attributes that may potentially contribute to emerging faults of a wind turbine. The set of attributes were selected from one-year historical data for analysis. The methodology uses the k-means clustering method to process outlier data and verifies the clustering results by comparing quartiles of boxplots, and applies the ...

While researchers and practitioners may seamlessly develop methods of detecting outliers in control charts under a univariate setup, screening multivariate pose serious challenges. In this study, we propose robust chart based on the Stahel-Donoho estimator (SDRE), whilst process parameters are estimated from phase-I. Through intensive Monte-Carlo simulation, study presents how estimation presen...