Gaku IGARASHI(イガラシ ガク)Associate Professor

Gaku IGARASHI

Associate Professor
Department of Economics:Statistics

Brief personal history

2010: Graduated from Department of Economics, Faculty of Economics and Business Administration, Hokkaido University
2015: Obtained Ph.D. (Economics) from Graduate School of Economics and Business Administration, Hokkaido University
2015: Assistant Professor, Department of Policy and Planning Sciences, Faculty of Engineering, Information and Systems, University of Tsukuba
2021: Associate Professor, Faculty of Economics, Gakushuin University

Main results

(Papers)
"Re-formulation of inverse Gaussian, reciprocal inverse Gaussian, and Birnbaum─Saunders kernel estimators" (with Kakizawa, Y.), Statistics and Probability Letters, Vol.84, pp. 235-246, 2014.
"On improving convergence rate of Bernstein polynomial density estimator" (with Kakizawa, Y.), Journal of Nonparametric Statistics, Vol.26, Issue 1, pp.61-84, 2014.
"Bias corrections for some asymmetric kernel estimators" (with Kakizawa, Y.), Journal of Statistical Planning and Inference, Vol.159, pp. 37-63, 2015.
"Bias reductions for beta kernel estimation", Journal of Nonparametric Statistics, Vol.28, Issue 1, pp.1-30, 2016.
"Weighted log-normal kernel density estimation", Communications in Statistics-Theory and Methods, Vol.45, pp. 6670-6687, 2016.
"Inverse gamma kernel density estimation for nonnegative data" (with Kakizawa, Y.), Journal of the Korean Statistical Society, Vol.46, Issue 2, pp. 194-207, 2017.
"Generalized gamma kernel density estimation for nonnegative data and its bias reduction" (with Kakizawa, Y.), Journal of Nonparametric Statistics, Vol.30, Issue 3, pp. 598-639, 2018.
"Multivariate density estimation using a multivariate weighted log-normal kernel", Sankhya A, Vol.80, Issue 2, pp.247-266, 2018.
"Limiting bias-reduced Amoroso kernel density estimators for non-negative data" (with Kakizawa, Y.), Communications in Statistics-Theory and Methods, Vol.47, Issue 20, pp. 4905-4937, 2018.
"Multiplicative bias correction for asymmetric kernel density estimators revisited" (with Kakizawa, Y.), Computational Statistics and Data Analysis, Vol.141, pp.40-61, 2020.
"Nonparametric direct density ratio estimation using beta kernel", Statistics, Vol.54, Issue 2, pp.257-280, 2020.

Message

When you want to assert something, the data and statistical analysis that support that claim provide important evidence to make it more convincing. Currently, because statistical analysis software is so good, it seems that once you learn how to use the software, you can perform statistical analysis easily. However, statistical analysis is built under a unique concept based on probability and logic, and it is not simple to determine which statistical analysis method to use for data and how to interpret statistical analysis results. In recent years, there has been a proliferation of data and tables and graphs based upon them, but without correct statistical knowledge, there is a danger they will be misinterpreted. Apart from "Statistics," the Economics Department of Gakushuin University's Faculty of Economics has classes dealing with statistical analysis such as "Introduction to Statistics I," "Introduction to Statistics II" and "Econometrics." Please take these classes to acquire correct knowledge of statistics and make use of it in the future.

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