R programmer to finish code for CausalImpact

I need to run causal impact on every 5-dma combo to determine which 5-dmas constitute the best control group for the remaining 204 dmas (test group). The data provided is for all of 2019 and will determine the control/test group for a 2020 marketing campaign. Ive included the R code Ive been working with which allows me to choose one DMA and the best five DMAs for a control group.

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## R Code Below
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install.packages(devtools) library(devtools) install.packages(dtw) install_github(google/CausalImpact) install_github(klarsen1/MarketMatching, build_vignettes=TRUE) install.packages(knitr) library(knitr) library(MarketMatching) mydata = read.csv(file = radio_date_dma_kpi_20200106.csv, header=TRUE) mydata$date <- as.Date(mydata$date) mydata$dma <- as.character(mydata$dma) mydata$kpi <- as.numeric(mydata$kpi) mm <- best_matches(data=mydata, id_variable=dma, date_variable=date, matching_variable=kpi, parallel=FALSE, markets_to_be_matched= ATLANTA, ### can we introduce a function here to run through every combination of 204 dmas? warping_limit=1, # warping limit=1 dtw_emphasis=1, # rely only on dtw for pre-screening matches=5)
About the recuiter
Member since May 20, 2018
Puneet K.
from Calarasi, Romania

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