Zobrazeno 1 - 10
of 833
pro vyhledávání: '"MURAKAMI, DAISUKE"'
Spatially and temporally varying coefficient (STVC) models are currently attracting attention as a flexible tool to explore the spatio-temporal patterns in regression coefficients. However, these models often struggle with balancing computational eff
Externí odkaz:
http://arxiv.org/abs/2410.07229
Autor:
Arandjelović, Aleksandar, Shevchenko, Pavel V., Matsui, Tomoko, Murakami, Daisuke, Myrvoll, Tor A.
Stochastic versions of recursive integrated climate-economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of stochastic shocks increases, solving these models as dynamic progra
Externí odkaz:
http://arxiv.org/abs/2408.09642
Autor:
Kuno, Hajime, Murakami, Daisuke
Although Bayesian skew-normal models are useful for flexibly modeling spatio-temporal processes, they still have difficulty in computation cost and interpretability in their mean and variance parameters, including regression coefficients. To address
Externí odkaz:
http://arxiv.org/abs/2407.05288
This study proposes a method for aggregating/synthesizing global and local sub-models for fast and flexible spatial regression modeling. Eigenvector spatial filtering (ESF) was used to model spatially varying coefficients and spatial dependence in th
Externí odkaz:
http://arxiv.org/abs/2401.12776
We have devised a data-driven framework for uncovering hidden control strategies used by an evolutionary system described by an evolutionary probability distribution. This innovative framework enables deciphering of the concealed mechanisms that cont
Externí odkaz:
http://arxiv.org/abs/2309.15844
Autor:
Murakami, Daisuke, Tsutsumida, Narumasa, Yoshida, Takahiro, Nakaya, Tomoki, Lu, Binbin, Harris, Paul
Although geographically weighted Poisson regression (GWPR) is a popular regression for spatially indexed count data, its development is relatively limited compared to that found for linear geographically weighted regression (GWR), where many extensio
Externí odkaz:
http://arxiv.org/abs/2305.08443
Although spatial prediction is widely used for urban and environmental monitoring, its accuracy is often unsatisfactory if only a small number of samples are available in the study area. The objective of this study was to improve the prediction accur
Externí odkaz:
http://arxiv.org/abs/2211.10693
Publikováno v:
Environmental Economics and Policy Studies 24, pp. 459-476 (2022)
The classical DICE model is a widely accepted integrated assessment model for the joint modeling of economic and climate systems, where all model state variables evolve over time deterministically. We reformulate and solve the DICE model as an optima
Externí odkaz:
http://arxiv.org/abs/2111.00835
Publikováno v:
In Journal of Choice Modelling September 2024 52
Publikováno v:
In Advanced Powder Technology August 2024 35(8)