Testing Forecast Rationality for Measures of Central Tendency

Measures of Central Tendency and Dispersion.

On central tendency and dispersion measures for intervals and hypercubes

The uncertainty or the variability of the data may be treated by considering, rather than a single value for each data, the interval of values in which it may fall. This paper studies the derivation of basic description statistics for interval-valued datasets. We propose a geometrical approach in the determination of summary statistics (central tendency and dispersion measures) for interval-val...

Modern robust data analysis methods: measures of central tendency.

Various statistical methods, developed after 1970, offer the opportunity to substantially improve upon the power and accuracy of the conventional t test and analysis of variance methods for a wide range of commonly occurring situations. The authors briefly review some of the more fundamental problems with conventional methods based on means; provide some indication of why recent advances, based...

Assessing Forecast Accuracy Measures

This paper looks into the issue of evaluating forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form of the chosen measure. We propose wellmotivated Kullback-Leibler Divergence based accuracy measures. In the empirical direction, we study the perfo...

Word frequency, repetition, and lexicality effects in word recognition tasks: beyond measures of central tendency.

Response time (RT) distributions obtained from 3 word recognition experiments were analyzed by fitting an ex-Gaussian function to the empirical data to determine the main effects and interactive influences of word frequency, repetition, and lexicality on the nature of the underlying distributions. The ex-Gaussian analysis allows one to determine if a manipulation simply shifts the response time...