Displaying similar documents to “Structural breaks in dependent, heteroscedastic, and extremal panel data”

Tests for profile analysis based on two-step monotone missing data

Mizuki Onozawa, Sho Takahashi, Takashi Seo (2013)

Discussiones Mathematicae Probability and Statistics

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In this paper, we consider profile analysis for the observations with two-step monotone missing data. There exist three interesting hypotheses - the parallelism hypothesis, level hypothesis, and flatness hypothesis - when comparing the profiles of some groups. The T²-type statistics and their asymptotic null distributions for the three hypotheses are given for two-sample profile analysis. We propose the approximate upper percentiles of these test statistics. When the data do not have...

Protecting micro-data by micro-aggregation: the experience in Eurostat.

Daniel Defays (1997)

Qüestiió

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A natural strategy to protect the confidentiality of individual data is to aggregate them at the lowest possible level. Some studies realised in Eurostat on this topic will be presented: properties of classifications in clusters of fixed sizes, micro-aggregation as a generic method to protect the confidentiality of individual data, application to the Community Innovation Survey. The work performed in Eurostat will be put in line with other projects conducted at European level on the...

Detection of outlying observations using the Akaike information criterion

Andrzej Kornacki (2013)

Biometrical Letters

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For the detection of outliers (observations which are seemingly different from the others) the method of testing hypotheses is most often used. This approach, however, depends on the level of significance adopted by the investigator. Moreover, it can lead to the undesirable effect of “masking” of the outliers. This paper presents an alternative method of outlier detection based on the Akaike information criterion. The theory presented is applied to analysis of the results of beet leaf...