Description Usage Arguments Value Author(s) Examples

This function perform F test in each regression based on different subsamples

1 2 |

`formula` |
The regression formula: : Y ~ X1 + ... + Xk |

`data` |
A data.frame for the Panel data. |

`index` |
A vector of the two indexes: (c("ID", "Time")). |

`SDF` |
Spatial*DataFrame on which is based the data, with the "ID" in the index. |

`bw` |
The optimal bandwidth, either adaptive or fixed distance. |

`adaptive` |
If TRUE, adaptive distance bandwidth is used, otherwise, fixed distance bandwidth. |

`p` |
The power of the Minkowski distance, default is 2, i.e. the Euclidean distance |

`effect` |
The effects introduced in the fixed effects model, one of "individual" (default) , "time", "twoways" |

`kernel` |
bisquare: wgt = (1-(vdist/bw)^2)^2 if vdist < bw, wgt=0 otherwise (default); gaussian: wgt = exp(-.5*(vdist/bw)^2); exponential: wgt = exp(-vdist/bw); tricube: wgt = (1-(vdist/bw)^3)^3 if vdist < bw, wgt=0 otherwise; boxcar: wgt=1 if dist < bw, wgt=0 otherwise |

`longlat` |
If TRUE, great circle distances will be calculated |

A list of result:

- GW.arguments
a list class object including the model fitting parameters for generating the report file

- SDF
a Spatial*DataFrame (either Points or Polygons, see sp) integrated with fit.points, test value, p value, df1, df2

Chao Li <chaoli0394@gmail.com> Shunsuke Managi

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
data(TransAirPolCalif)
data(California)
formula.GWPR <- pm25 ~ co2_mean + Developed_Open_Space_perc + Developed_Low_Intensity_perc +
Developed_Medium_Intensity_perc + Developed_High_Intensity_perc +
Open_Water_perc + Woody_Wetlands_perc + Emergent_Herbaceous_Wetlands_perc +
Deciduous_Forest_perc + Evergreen_Forest_perc + Mixed_Forest_perc +
Shrub_perc + Grassland_perc + Pasture_perc + Cultivated_Crops_perc +
pop_density + summer_tmmx + winter_tmmx + summer_rmax + winter_rmax
#precomputed bandwidth
bw.AIC.Fix <- 2.010529
GWPR.pFtest.resu.F <- GWPR.pFtest(formula = formula.GWPR, data = TransAirPolCalif,
index = c("GEOID", "year"),
SDF = California, bw = bw.AIC.Fix, adaptive = FALSE, p = 2,
effect = "individual", kernel = "bisquare",
longlat = FALSE)
library(tmap)
tm_shape(GWPR.pFtest.resu.F$SDF) +
tm_polygons(col = "p.value", breaks = c(0, 0.05, 1))
``` |

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