A simple test for spatial heteroscedasticity in spatially varying coefficient models

Shen, Si-Lian; Cui, Jian-Ling; Xin-qian, WU

doi:10.1080/00949655.2020.1862112

Cited by 2 publications

(1 citation statement)

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“…Heterogeneity in the data occurs when the distribution is not the same. It means the parameters estimated are different across the entire location [17]. In the Breusch-Pagan test, rejection of 𝐻 0 occurs when the value of 𝐵𝑃 > 𝜒 (𝛼;𝑝) 2 with p being the number of independent variables or when 𝑝 − 𝑣𝑎𝑙𝑢𝑒 < 𝛼 [18].…”

Section: Resultsmentioning

confidence: 99%

Spatial Heterogeneity Models of Undernourished Toddlers in Java Island, Indonesia

As’adi,

Setia Dewi,

Tirta

2023

SAR Journal

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The percentage of undernourished toddlers on Java Island averages 8.5 %. This number is relatively high compared to the average incidence of undernutrition in toddlers in Sumatra, 3.3%. This study uses OLS, GWR, and GWANN to explore undernutrition in toddlers data on Java Island. We use cross-validation to determine the optimum bandwidth in GWR and GWANN methods. GWANN uses a single hidden layer with several hidden neurons where the number of hidden neurons is selected based on RMSE. We use indicators RMSE, MAE, and MAPE to determine the best method for modeling data on undernourished toddlers in Java. By comparing the final results, the best method for modeling data on undernourished toddlers in Java is GWR. There is a relationship between regions on the influence factor of undernutrition. Most adjacent areas, ranging from East Java to DKI Jakarta, have the same influence factor: the percentage of skinny toddlers.

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Section: Resultsmentioning

confidence: 99%