get_all_neib_vals: Get the spatio-temporal neighbourhoods of all observations

In mrfoliveira/Evaluation-procedures-for-forecasting-with-spatio-temporal-data: Evaluation procedures for forecasting with spatio-temporal data

Description

Get the spatio-temporal neighbourhoods of all observations

Usage

get_all_neib_vals(df, max_radius, t_dist_mat, s_dist_mat, alpha, vars,
  time_id, site_id, parallel = FALSE, nsplits = 4)

Arguments

df	a data frame of observations
max_radius	the maximum spatio-temporal distance allowed to be included in a neighbourhood
t_dist_mat	a matrix of normalized temporal distances between time-stamps (rownames and colnames should be a concatenation of "TIME_" and the time-stamp)
s_dist_mat	a matrix of normalized spatial distances between locations (rownames and colnames should be a concatenation of "SITE_" and the location IDs)
alpha	a weighting factor for the spatio-temporal distance
vars	Vector of character strings indicating the columns whose values should be retrieved
time_id	the name of the column containing time-stamps
site_id	the name of the column containing location IDs
parallel	Boolean indicating whether the code should run in parallel. Default is FALSE
nsplits	Number of subsets of rows to split the data frame into so they can be processed in parallel

Details

The spatio-temporal distance is defined as

D_{i,j} = d_{i,j} x α + t_{i,j} x (1-α)

where d_i,j is the spatial distance between locations, t_i,j is the temporal distance between time-stapms and α is a weighting factor. Note that the radius should always be a number between zero and min(alpha, alpha-1). Also note that if alpha is set to 1, then instead of a cone, the neighbourhood will have the shape of a cylinder.

Value

A data frame where each row describes a neighbour, with the first two columns containing the location ID and time-stamp of the central observation, followed by two columns with the neighbouring location ID and time-stamp, a colunm containing the spatio-temporal distance between the two, and a final column containing the values of the variables in df at the neighbouring time and location.

References

Ohashi, Orlando, and Luis Torgo. "Wind speed forecasting using spatio-temporal indicators." ECAI. 2012.

See Also

get_st_neighbours

mrfoliveira/Evaluation-procedures-for-forecasting-with-spatio-temporal-data documentation built on April 11, 2021, 10:50 a.m.