get_full_indicators: Get time series embeds and spatio-temporal indicators

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

Description

Get time series embeds and spatio-temporal indicators

Usage

get_full_indicators(df, stations, k, betas, alpha = 0.5, var = "value",
  stats = c("mean", "weighted.mean", "sd"), ratios2add = c(TRUE, TRUE,
  FALSE), neib_type = "cone", parallel = FALSE, nsplits = 1,
  time_id = "time", site_id = "station")

Arguments

df	A data frame containing spatio-temporal information
stations	An sf object containing geographical information on the location of df
k	A numeric indicating the temporal embed size \(number\)
betas	A vector of values defining the maximum spatio-temporal distance allowed for an observation to be considered within a spatio-temporal neighbourhood
alpha	a weighting factor for the spatio-temporal distance
var	The name of the variable to summarize into indicators
stats	A vector containing the names of functions that are to be used to calculate summarizing statistics
ratios2add	A vector of Boolean values indicating, for each statistic in stats whether ratios between neighorhoods of subsequent sizes should be included as extra columns
neib_type	the type of neighborhood to consider. Can be cone (default) - a cone with the center of its base at the observation (spatial radius growing with time) reversed - a cone with its peak at the observation (spatial radius shrinking with time)
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
time_id	The name of the column containing time-stamps in df
site_id	The name of the column containing location IDs in df

Value

A data frame that contains extra columns <var>_Tm1, <var>_Tm2, ..., <var>_Tm<k-1> with previous observations for each location, summary statistics of the values of var found within the spatio-temporal neighbourhoods of the one or more radiuses of each pair (location ID, time-stamp) and ratios between them

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