Statistical Inference in a Simple Linear Model Under Microaggregation

A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is microaggregation, a technique where observations are grouped and replaced with their corresponding group means. However, while reducing the disclosure risk of a data file, microaggregation also affects the results of statistical analyses. We focus on the effect of microaggregation on a simple linear model. In a previous paper we have shown how to correct for the aggregation bias of the naive least-squares estimator that occurs when the dependent variable is used to group the data. The present paper deals with the asymptotic variance of the corrected least-squares estimator and with the asymptotic variance of the naive least-squares estimator when either the dependent variable or the regressor is used to group the data. We derive asymptotic confidence intervals for the slope parameter. Furthermore, we show how to test for the significance of the slope parameter by analyzing the effect of microaggregation on the asymptotic power function of the naive t-test

Consistent Estimation of a Simple Linear Model Under Microaggregation

A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata to is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is microaggregation, a technique where observations are grouped and replaced with their corresponding group means. However, while reducing the disclosure risk of a data file, microaggregation also affects the results of statistical analyses. The paper deals with the impact of microaggregation on a simple linear model. We show that parameter estimates are biased if the dependent variable is used to group the data. It turns out that the bias of the slope parameter estimate is a non-monotonic function of this parameter. By means of this non-monotonic relationship we develop a method for consistently estimating the model parameters

BitPar

Statistical parse

Ciradian dysrhythmias in the EEG of children with clonazepam treatment

The effects of different anticonvulsants on the system of cir-cadian and ultradian rhythms in the EEG of children was investigated in ten 24*-h recordings of children with different forms of epilepsy. Circadian dysrhythmias could be found in children with Clonazepam treatment

Counter Attack on Byzantine Generals: Parameterized Model Checking of Fault-tolerant Distributed Algorithms

We introduce an automated parameterized verification method for fault-tolerant distributed algorithms (FTDA). FTDAs are parameterized by both the number of processes and the assumed maximum number of Byzantine faulty processes. At the center of our technique is a parametric interval abstraction (PIA) where the interval boundaries are arithmetic expressions over parameters. Using PIA for both data abstraction and a new form of counter abstraction, we reduce the parameterized problem to finite-state model checking. We demonstrate the practical feasibility of our method by verifying several variants of the well-known distributed algorithm by Srikanth and Toueg. Our semi-decision procedures are complemented and motivated by an undecidability proof for FTDA verification which holds even in the absence of interprocess communication. To the best of our knowledge, this is the first paper to achieve parameterized automated verification of Byzantine FTDA

EU Ecolabel for food and feed products – feasibility study

The environmental impacts of the production and processing of food, feed and drinks make up between 20% and 30% of the total environmental impacts of consumable goods in the EU. In the case of eutrophication (the accumulation of nutrients in water causing a reduction in oxygen availability) they account for as much as 58% of the total impacts. The EU Ecolabel is a voluntary scheme that forms part of overall EU policy to encourage more sustainable consumption and production. To date, the EU Ecolabel scheme has developed criteria for products in the non-food sector. The Regulation that governs the scheme (66/2010) aims to extend the EU Ecolabel into new product categories including food. However, the Regulation stipulates that before extending to the food sector, a feasibility study should be undertaken