Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Fumitake Sakaori"'
Autor:
Tadashi Imaizumi, Akinori Okada, Sadaaki Miyamoto, Fumitake Sakaori, Yoshiro Yamamoto, Maurizio Vichi
This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783319949437
In recent years, lifestyle diseases have become a serious problem in Japan. According to a survey by the Ministry of Health, Labour and Welfare, more than half the causes of death in FY 2005 were attributed to lifestyle diseases. To prevent lifestyle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d86746857167f8c29673d6e936a7d539
https://doi.org/10.1007/978-3-319-94944-4_24
https://doi.org/10.1007/978-3-319-94944-4_24
Autor:
Fumitake Sakaori, Heewon Park
Publikováno v:
Communications for Statistical Applications and Methods. 21:471-486
This study introduces a new type of symbolic data, a candle chart-valued time series. We aggregate four stock indices (i.e., open, close, highest and lowest) as a one data point to summarize a huge amount of data. In other words, we consider a candle
Publikováno v:
Journal of Statistical Computation and Simulation. 84:1596-1607
There is currently much discussion about lasso-type regularized regression which is a useful tool for simultaneous estimation and variable selection. Although the lasso-type regularization has several advantages in regression modelling, owing to its
Autor:
Heewon Park, Fumitake Sakaori
Publikováno v:
Computational Statistics. 28:493-504
The adaptive lasso can consistently identify the true model in regression model. However, the adaptive lasso cannot account for lag effects, which are essential for a time series model. Consequently, the adaptive lasso can not reflect certain propert
Autor:
Fumitake Sakaori
Publikováno v:
TRENDS IN THE SCIENCES. 23:12_59-12_59
Publikováno v:
Computational Statistics & Data Analysis. 51:4707-4716
We investigate a correlation coefficient of principal components from two sets of variables. Using perturbation expansion, we get a limiting distribution of the correlation. In addition, we obtain a limiting distribution of the Fisher's z transformat
Publikováno v:
Computational Statistics. 22:121-131
Confidence intervals for all of the characteristic roots of a sample covariance matrix are derived. Using a perturbation expansion, we obtain a new confidence interval for these roots. Then, we propose another confidence interval based on the results
Publikováno v:
JOURNAL OF THE JAPAN STATISTICAL SOCIETY. 37:239-251
We consider two sets of variables with a joint distribution and analyze the canonical correlations between the variables in the two sets. One of the analyses used is the canonical correlation analysis, which finds linear combinations of variables in
Autor:
Fumitake Sakaori
Publikováno v:
Communications in Statistics: Simulation and Computation. 31:641-651
The purpose of this paper is to investigate the permutation tests for equality of correlation coefficients among two independent populations. We discuss how to apply permutation test to this problem and its asymptotic suitability. We also show some s