20 citations · 33 across the 10 of their papers we have counts for
4 papers · 1 filter
Non-asymptotic results for Cornish--Fisher expansions
V. V. Ulyanov, M. Aoshima, Y. Fujikoshi
We get the computable error bounds for generalized Cornish-Fisher expansions for quantiles of statistics provided that the computable error bounds for Edgeworth-Chebyshev type expa…
Two-sample tests for high-dimension, strongly spiked eigenvalue models
Makoto Aoshima, Kazuyoshi Yata
We consider two-sample tests for high-dimensional data under two disjoint models: the strongly spiked eigenvalue (SSE) model and the non-SSE (NSSE) model. We provide a general test…
Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context
Aki Ishii, Kazuyoshi Yata, Makoto Aoshima
A common feature of high-dimensional data is that the data dimension is high, however, the sample size is relatively low. We call such data HDLSS data. In this paper, we study asym…
Principal component analysis based clustering for high-dimension, low-sample-size data
Kazuyoshi Yata, Makoto Aoshima
In this paper, we consider clustering based on principal component analysis (PCA) for high-dimension, low-sample-size (HDLSS) data. We give theoretical reasons why PCA is effective…