Department of Mathematics,
Graduate School of Science, Kobe University
Division : Applied Mathematics
|Building B, Room 214|
|Research Field :
Mathematical statistics, Missing data analysis, and
High-dimensional data analysis.
|Research Summary :
We consider the statistical hypothesis testing procedures
with missing data. By obtaining Bartlett-type correction of
the test statistics, we propose the testing procedures
which perform better even if the sample size is small.
Furthermore, we also extend the above-mentioned results
to the case of elliptically contoured distributions.
|Primary Publications :|
N. Shutoh .
Effect of nonnormality on tests for a mean vector
with missing data under an elliptically contoured
pattern-mixture model, Communications in Statistics -
Theory and Methods, 50, 4448-4469. (2021)
T. Kawasaki, N. Shutoh, T. Seo .
On the asymptotic distribution of $T^2$-type statistic
with two-step monotone missing data,
Journal of Statistical Theory and Practice,
12, 657-668. (2018)
N. Shutoh, T. Nishiyama, M. Hyodo.
Bartlett correction to the likelihood ratio test for
MCAR with two-step monotone sample, Statistica Neerlandica,
71, 184-199. (2017)
S. Takahashi, N. Shutoh .
Tests for parallelism and flatness hypotheses of
two mean vectors in high-dimensional settings,
Journal of Statistical Computation and Simulation,
86, 1150-1165. (2016)
M. Hyodo, N. Shutoh, T. Nishiyama, T. Pavlenko (2015).
Testing block-diagonal covariance structure for high-dimensional data,
Statistica Neerlandica, 69, 460-482.
- N. Shutoh .
An asymptotic approximation for EPMC in linear discriminant
analysis based on monotone missing data,
Journal of Statistical Planning and Inference,
142, 110-125. (2012)