Skip to main content

Table 2 Interpolation errors for neighborhood attributes

From: Detecting social media users based on pedestrian networks and neighborhood attributes: an observational study

Neighborhood attributeRMSERMSERMSERMSERMSE
 p=1p=2p=3p=4p=5
Age-PC1978×10−3738×10−3*0.770798×10−3812×10−3
Age-PC20.610555×10−3*581×10−3609×10−3631×10−3
ICT-PC11.34986×10−3*992×10−31.021.04
ICT-PC2227×10−3195×10−3*208×10−3219×10−3225×10−3
Education-PC11.04768×10−3*794×10−3818×10−30.830
Education-PC2609×10−3475×10−3*483×10−30.500516×10−3
Dwelling-PC11.04949×10−3*981×10−31.041.09
Dwelling-PC2903×10−3872×10−3*0.9801.031.07
Population density-PC11.04949×10−3*981×10−31.041.09
Population density-PC2562×10−3414×10−3*431×10−3447×10−3455×10−3
  1. Note: “*” denotes the lowest RMSE value found