activity
20042014
most citedSurrogate Test to Distinguish between Chaotic and Pseudoperiodic Time Series

36 citations · 57 across the 5 of their papers we have counts for

collaborators

5 papers

q-fin.TR2014★ 2 cited

On possible origins of trends in financial market price changes

Ryo Murakami, Tomomichi Nakamura, Shin Kimura +2

We investigate possible origins of trends using a deterministic threshold model, where we refer to long-term variabilities of price changes (price movements) in financial markets a…

physics.data-an2014

Constructing directed networks from multivariate time series using linear modelling technique

Toshihiro Tanizawa, Tomomichi Nakamura, Fumihiko Taya +1

We describe a method to construct directed networks from multivariate time series which has several advantages over the widely accepted methods. This method is based on an informat…

stat.OT2012★ 16 cited

Networks with time structure from time series

Tomomichi Nakamura, Toshihiro Tanizawa

We propose a method of constructing a network, in which its time structure is directly incorporated, based on a deterministic model from a time series. To construct such a network,…

nlin.CD2006★ 3 cited

Surrogate data method applied to nonlinear time series

Xiaodong Luo, Tomomichi Nakamura, Michael Small

The surrogate data method is widely applied as a data dependent technique to test observed time series against a barrage of hypotheses. However, often the hypotheses one is able to…

nlin.CD2004★ 36 cited

Surrogate Test to Distinguish between Chaotic and Pseudoperiodic Time Series

Xiaodong Luo, Tomomichi Nakamura, Michael Small

In this communication a new algorithm is proposed to produce surrogates for pseudoperiodic time series. By imposing a few constraints on the noise components of pseudoperiodic data…