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Delta convergence is a reduction of a country distance from the best performing Member State. There is convergence if there is a decrease in the period considered.
For each year, the above summaries are calculated to assess if a reduction in
the amplitude on the took place.
## already set at start resDelta <- delta_conv(wkDF2, timeName = timeName, indiType = params$indiType,# "highBest","lowBest", #params$indiType time_0 = NA, time_t = NA, extended = TRUE) lastRowAveragesDel <- nrow(resDelta$res$delta_conv) plot2de <- qplot( resDelta$res$delta_conv$time, resDelta$res$delta_conv$delta, xlab= paste("Years "), ylab= paste("Delta (",aggregation,")")) + geom_line() + ggplot2::scale_x_continuous( breaks = seq(ptime_0,ptime_t), labels = seq(ptime_0,ptime_t)) + ggplot2::theme( axis.text.x=ggplot2::element_text( angle = 45, vjust = 1, hjust = 1)) delta_gr1 <- grid.arrange( plot2de, ncol=1) # export out_packed_list$delta_gr1 <- delta_gr1 invisible(delta_gr1)
Delta summary list:
r params$indiType
Change in average:
r ptime_0
, average: r as.numeric(outMed[1,aggregation])
r ptime_t
, average: r as.numeric(outMed[lastRowAverages,aggregation])
r as.numeric(outMed[lastRowAverages,aggregation])-as.numeric(outMed[1,aggregation])
Change in delta values:
Year r ptime_0
, delta: r as.numeric(resDelta$res$delta_conv[1,'delta'])
r ptime_t
, delta: r as.numeric(resDelta$res$delta_conv[lastRowAveragesDel,'delta'])
r resDelta$res$diffe_delta
r resDelta$res$label_strict
r resDelta$res$label_conver
out_packed_list$deltaSummary <- list( indicatorType= params$indiType, startingYear = ptime_0, endingYear = ptime_t, startingAverage = as.numeric(outMed[1,aggregation]), endingAverage = as.numeric(outMed[lastRowAverages,aggregation]), DeltaAverage = as.numeric(outMed[lastRowAverages,aggregation])- as.numeric(outMed[1,aggregation]), # delta_conv_output= resDelta$res )
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