Factor analysis as a dimension reduction technique is widely used with compositional data. Using the method for raw data or for improperly transformed data will, however, lead to biased results and consequently to misleading interpretations. Although some procedures, suitable for factor analysis with compositional data, were already developed, they require pre-knowledge of variable groups, or a...

The word robustness is frequently used in the literature, and is often stated with completely di®erent meaning. In this contribution robustness means to reduce the in°uence of \unusual" observations on statistical estimates. Such observations are frequently denoted as outliers, and are often thought to be extreme values caused by measurement or transcription errors. However, the notion of outli...

objective: the aim of this study is to explore the confirmatory factor analysis results of the persian adaptation of abbreviated math anxiety scale (amas), proposed by hopko, mahadevan, bare & hunt. method: the validity and reliability assessments of the scale were performed on 298 college students chosen randomly from tabriz university in iran. the confirmatory factor analysis (cfa) was carrie...

Identification of geochemical anomalies is a significant step during regional geochemical exploration. In this matter, new techniques have been developed based on deep learning networks. These simple-structure-networks act like our brains on processing the data by simulating deep layers of thinking. In this paper, a hybrid compositional-deep learning technique was applied to identify the anomal...