In InstitutoInvestigacionesEconomicasPUCE/geortsBeta: Reconstruction of Geographical Time Series

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(knitr)

Overview

The GeoRTS package provides a set of tools for reconstruction (by interpolation) of geographical time series

Installation

Install the stable version from CRAN:

install.packages("GeoRTS")

or install the development version from Github:

# install.packages("devtools")
devtools::install_github("InstitutoInvestigacionesEconomicasPUCE/GeoRTS")

Key Features

Cleaning of time series

First we need to carge the data, so we use:

library(GeoRTS)
library(gridExtra)
data(rts)

Then we have in our environment five new objects: TS , positions.TS , weights.TS , positions.RTS , weights.RTS

library(stlplus)
library(dplyr)
library(ggplot2)
library(reshape2)
library(gridExtra)
library(leaflet)
library(highcharter)
load(file="func_borr.RData")
load(file="rts.RData")

Where TS is a multivariate "ts" object, which has missing values:

kable(TS[10:25,])

Then applyinng rts_clean function to TS, by consider the parameter of seasonality 12:

TS_clean = rts_clean(TS,seasonality = 12)
kable(TS_clean[10:25,])

Using the rts_plotClean we can plot the original and cleaned function:

pl = list()
for (i in seq(dim(TS)[2])) {
  pl[[i]] = rts_plotClean(TS,i)
}

grid.arrange(grobs=pl,nrow=dim(TS)[2])

Reconstruction of time series

To reconstruct (by IDW) unknownn data of time series associated to positions.RTS (latitude and longitud in meters) we use geoRTS function, that consider an aproximation based in convex combination of original time series in TS, considering the distance between TS given by positions.TS, also it could be consider some factors as weight.TS related with the local geographical influence of time series.

RTS = geoRts(TS_clean,positions.TS,weights.TS,positions.RTS,weights.RTS)
kable(RTS[10:25,])

Plot the RTS data

Then we could plot both series (original and reconstructed) with the function rts_plotGroup

rts_plotGroup(TS_clean,RTS)

Finally we could represent the date in a map with function rts_map

rts_map(positions.TS,positions.RTS,scale=10^4,weights.TS,weights.RTS)

InstitutoInvestigacionesEconomicasPUCE/geortsBeta documentation built on June 17, 2020, 7:06 a.m.