Two-Steps Benchmarks for Time Series Disaggregation


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Documentation for package ‘disaggR’ version 1.0.5.2

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annualBenchmark Regress and bends a time series with a lower frequency one
autoplot.threeRuleSmooth Plotting disaggR objects
autoplot.tscomparison Plotting disaggR objects
autoplot.twoStepsBenchmark Plotting disaggR objects
bflSmooth Smooth a time series
distance Distance computation for disaggregations
in_disaggr Comparing a disaggregation with the high-frequency input
in_revisions Comparing two disaggregations together
in_sample Producing the in sample predictions of a prais-lm regression
in_scatter Comparing the inputs of a praislm regression
plot.threeRuleSmooth Plotting disaggR objects
plot.tscomparison Plotting disaggR objects
plot.twoStepsBenchmark Plotting disaggR objects
rePort Producing a report
reUseBenchmark Using an estimated benchmark model on another time series
reView A shiny app to reView and modify twoStepsBenchmarks
threeRuleSmooth Bends a time series with a lower frequency one by smoothing their rate
twoStepsBenchmark Regress and bends a time series with a lower frequency one