Abstract
Distributional assumptions can be examined with multidimensional goodness-of-fit tests. We propose a conceptually simple test with an appealing logic and accessible asymptotic properties, which is generalizable to a variety of problems and appears to work well against diverse alternatives. To test whether a k-dimensional random sample X1, …, Xn follows the distribution G, consider a triangle formed by two randomly selected data points Xi and Xj and a variable Y ∼ G. Our statistic estimates the likelihood that the side formed by the line from Xi to Xj is the smallest, the middle, or the largest side of the triangle.
Original language | English (US) |
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Pages (from-to) | 577-586 |
Number of pages | 10 |
Journal | Journal of the American Statistical Association |
Volume | 92 |
Issue number | 438 |
DOIs | |
State | Published - Jun 1 1997 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty