A cost-effective algorithm for calibrating multiscale geographically weighted regression models

Wu, Bo; Yan, Jinbiao; Lin, Hui

doi:10.1080/13658816.2021.1999457

Cited by 9 publications

(3 citation statements)

References 24 publications

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“…Ŷ = SY (A20) MATLAB R2022b was used for the calculations. The code used in the calculations was a heavily modified and appended version of the MATLAB code found in the supplementary material of Wu et al [77].…”

Section: Appendix Amentioning

confidence: 99%

Mapmaking Process Reading from Local Distortions in Historical Maps: A Geographically Weighted Bidimensional Regression Analysis of a Japanese Castle Map

Yabe

2024

IJGI

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Shoho Castle Maps are maps of castle towns throughout Japan drawn by Kano School painters on the order of the shogun in 1644. The Shoho Castle Map of Takada, Joetsu City, Niigata Prefecture was used to visualize local distortions in historical maps and to scrutinize the mapmaking process. A novel method, geographically weighted bidimensional regression, was developed and applied to visualize the local distortions of the map. Exaggerated expressions by mapmakers that have not been identified in previous studies were revealed. That is, in addition to the castle being drawn enlarged, the town where the merchants and artisans lived was drawn larger than the castle. Therefore, the Takada Shoho Castle Map reflects mapmakers’ intentions, besides enlarging military facilities, which appear to have emphasized the pictorial composition of the map by placing the main gate to the castle at the center and drawing the map area evenly from the center in a well-balanced layout.

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Section: Appendix Amentioning

confidence: 99%

Mapmaking Process Reading from Local Distortions in Historical Maps: A Geographically Weighted Bidimensional Regression Analysis of a Japanese Castle Map

Yabe

2024

IJGI

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“…Recent developments in spatial heterogeneity analyses suggest the use of Multi-scale GWR (MGWR) which extends the bandwidth construction by computing individual bandwidths for each variable (Fotheringham et al 2017). It has been discussed that MGWR model captures the spatial heterogeneity in a more accurate way, by minimizing over-fitting, mitigating concurvity and reducing potential parameter estimate biases (Wolf et al 2018;Yu et al 2020;Wu et al 2019Wu et al , 2022. We define the MWGR in equation (3).…”

Section: Empirical Setupmentioning

confidence: 99%

Do New Firms Boost Local Innovation? Evidence From Turkey

Karahasan

2023

International Regional Science Review

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New firms have been regarded as one of the key elements for local development. Existing studies focus on the direct impact of new firms via labour markets and job creation. However, the impact of new firms on regional innovation is less investigated. Our analyses are conducted for a developing country, Turkey. Findings of the study show that new firms are crucial for the regional differences in innovation. Results are robust to spatial dependence, an alternative firm formation measure, various regional controls and endogeneity issues. Additionally, impact of the new firms is spatially non-homogenous reminding the ineffectiveness of one-size-fits-all type policies.

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“…where bwj in B bwj indicates the bandwidth used for the calibration of the jth conditional relationship [81,82].…”

Section: Geostatistical Analysismentioning

confidence: 99%

Modeling the Potential for Rural Tourism Development via GWR and MGWR in the Context of the Analysis of the Rural Lodging Supply in Extremadura, Spain

Sánchez-Martín,

Hernández-Carretero,

Rengifo-Gallego

et al. 2023

Systems

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The harmonious development of tourism activity in rural areas must be based on effective tourism plans adapted to the territory. To achieve this, it is necessary that the tourist potential of the area be taken into consideration. However, the tourist attraction capacity is not always considered, which has led to a significant increase in the number of rural lodgings. This has caused strong imbalances in Extremadura, Spain. On the basis of this premise, in this research study, we aim to determine whether there is an adjustment between the main factors that attract rural tourists to the study area. To determine this, we make use of different geostatistical procedures based on spatially weighted regression models (GWR and MGWR). A comparative study is conducted using these models, on the basis of which it is deduced that one type of regression offers advantages over the other. However, the results show that neither regression models can explain the presence of rural accommodation in places that do not meet the requirements demanded by tourists. This fact shows that the increase in the supply of rural accommodation follows unsuitable patterns in some cases, which translates into numerous problems, such as low occupancy levels. In this study, it is concluded that there is no strong relationship between the attractiveness of a territory and its volume of supply, highlighting the need to rethink tourism plans in order to adjust them relative to reality.

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A cost-effective algorithm for calibrating multiscale geographically weighted regression models

Cited by 9 publications

References 24 publications

Mapmaking Process Reading from Local Distortions in Historical Maps: A Geographically Weighted Bidimensional Regression Analysis of a Japanese Castle Map

Mapmaking Process Reading from Local Distortions in Historical Maps: A Geographically Weighted Bidimensional Regression Analysis of a Japanese Castle Map

Do New Firms Boost Local Innovation? Evidence From Turkey

Modeling the Potential for Rural Tourism Development via GWR and MGWR in the Context of the Analysis of the Rural Lodging Supply in Extremadura, Spain

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