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Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

copied from cf-post-staging / r-prophet
Type Size Name Uploaded Downloads Labels
conda 1.5 MB | osx-64/r-prophet-0.5-r36hf99fc2c_1.tar.bz2  6 years and 10 months ago 394 main cf202003
conda 3.3 MB | osx-64/r-prophet-0.5-r35hf99fc2c_1.tar.bz2  6 years and 10 months ago 390 main cf202003
conda 1.4 MB | linux-64/r-prophet-0.5-r36h0357c0b_1.tar.bz2  6 years and 10 months ago 5049 main cf202003
conda 1.4 MB | linux-64/r-prophet-0.5-r35h0357c0b_1.tar.bz2  6 years and 10 months ago 5070 main cf202003
conda 3.3 MB | osx-64/r-prophet-0.5-r35hf99fc2c_0.tar.bz2  6 years and 10 months ago 379 main cf202003
conda 1.4 MB | linux-64/r-prophet-0.5-r35h0357c0b_0.tar.bz2  6 years and 10 months ago 4832 main cf202003

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