Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Tetsuji Tonda"'
Autor:
Tetsuji Tonda1, Kenichi Satoh2
Publikováno v:
Journal of the Japan Statistical Society. 2017, Vol. 47 Issue 1, p1-12. 12p.
Autor:
Tetsuji Tonda
Publikováno v:
Journal of Epidemiology, Vol 25, Iss 10, Pp 639-646 (2015)
Background: Cancer mortality is increasing with the aging of the population in Japan. Cancer information obtained through feasible methods is therefore becoming the basis for planning effective cancer control programs. There are three time-related fa
Externí odkaz:
https://doaj.org/article/97f3d6371cce4da1a14d81b4b89dfe83
Publikováno v:
International Journal of Networked and Distributed Computing (IJNDC), Vol 5, Iss 4 (2017)
We propose a method to estimate and visualize effects of a binary covariate on the longitudinally observed text data. Our method consists of series of analytical methods: extracting keywords through a morphological analysis, estimating the time-varyi
Externí odkaz:
https://doaj.org/article/1ec28113891d45dbb6f1dfaf4efa7f22
Autor:
Kenichi Satoh1, Tetsuji Tonda2
Publikováno v:
Journal of the Japan Statistical Society. 2014, Vol. 44 Issue 1, p25-41. 17p.
Publikováno v:
FORMATH. 20
Publikováno v:
FORMATH. 16:12-21
Publikováno v:
American Journal of Mathematical and Management Sciences. 35:353-360
SYNOPTIC ABSTRACTIn epidemiological studies, odds ratios are widely used for quantifying the relative risk. The odds ratio can be estimated from background factors, using logistic regression. In th...
Autor:
Tetsuji Tonda, Kenichi Satoh
Publikováno v:
American Journal of Mathematical and Management Sciences. 35:183-193
SYNOPTIC ABSTRACTThis article presents a method for estimating the regression coefficients for a growth curve model when the time trend of the baseline has not been specified. The concept of this method is similar to that of the Cox proportional haza
Publikováno v:
Hiroshima Math. J. 47, no. 1 (2017), 43-62
In this paper we obtain a higher order asymptotic unbiased estimator for the expected probability of misclassification (EPMC) of the linear discriminant function when both the dimension and the sample size are large. Moreover, we evaluate the mean sq
Autor:
Tetsuji Tonda, Kenichi Satoh
Publikováno v:
JOURNAL OF THE JAPAN STATISTICAL SOCIETY. 44:25-41
A geographical weighted regression model can be used for visualizing or interpreting the covariate effects that vary with location. This model is usually estimated by a locally weighted regression or a kernel smoothing method, but we can regard the r