Description Usage Arguments Value
Interpolate population/inverse-distance-weighted measures for each x coordinate using measures taken at surrounding y coordinates. Ending measures are double weighted by population and distance so that surrounding measures taken in nearby areas and those with greater populations are given more weight in final average.
1 2 3 4 | popdist_weighted_mean(x_df, y_df, measure_col, x_id = "id",
x_lon_col = "lon", x_lat_col = "lat", y_lon_col = "lon",
y_lat_col = "lat", pop_col = "pop", dist_function = "Haversine",
dist_transform = "level", decay = 2)
|
x_df |
DataFrame with coordinates that need weighted measures |
y_df |
DataFrame with coordinates at which measures were taken |
measure_col |
String name of measure column in y_df |
x_id |
String name of unique identifer column in x_df |
x_lon_col |
String name of column in x_df with longitude values |
x_lat_col |
String name of column in x_df with latitude values |
y_lon_col |
String name of column in y_df with longitude values |
y_lat_col |
String name of column in y_df with latitude values |
pop_col |
String name of column in x_df with population values |
dist_function |
String name of distance function: "Haversine" (default) or "Vincenty" |
dist_transform |
String value of distance weight transform: "level" (default) or "log" |
decay |
Numeric value of distance weight decay: 2 (default) |
Dataframe of population/distance-weighted values
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