On the asymptotic distribution of \(T^2\)-type statistic with two-step monotone missing data
DOI10.1080/15598608.2018.1450795zbMath1425.62081OpenAlexW2796031399MaRDI QIDQ2321831
Takashi Seo, Tamae Kawasaki, Nobumichi Shutoh
Publication date: 23 August 2019
Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/15598608.2018.1450795
asymptotic expansionMonte Carlo simulationstochastic expansiondataBartlett correctionchi-squared approximationtwo-step monotone missing
Multivariate distribution of statistics (62H10) Hypothesis testing in multivariate analysis (62H15) Monte Carlo methods (65C05)
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Cites Work
- Unnamed Item
- Kurtosis tests for multivariate normality with monotone incomplete data
- An asymptotic approximation for EPMC in linear discriminant analysis based on monotone missing data
- Finite-sample inference with monotone incomplete multivariate normal data. I.
- Finite-sample inference with monotone incomplete multivariate normal data. II
- Asymptotic properties of a correlation matrix under a two-step monotone incomplete sample
- Maximum-likelihood estimation of the parameters of a multivariate normal distribution
- Transformations with improved chi-squared approximations
- Testing Equality of Means and Simultaneous Confidence Intervals in Repeated Measures with Missing Data
- Some Basic Properties of the Mle's for a Multivariate Normal Distribution with Monotone Missing Data
- A Method for Improving the Large-Sample Chi-Squared Approximations to Some Multivariate Test Statistics
- An asymptotic expansion for the distribution of the linear discriminant function based on monotone missing data
- Bias correction forT2type statistic with two-step monotone missing data
- Testing block‐diagonal covariance structure for high‐dimensional data
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