Summary
Functions
Forecasts how many time periods are needed to complete size items
Returns a function for forecasting the duration to complete a number of items.
Returns a function for forecasting the number of completed items in a number periods.
Basic Monte Carlo simulation to repeatedly run a simulation multiple times.
Performs a nested bootstrap on sample data.
Functions
@spec forecast( fun :: (-> non_neg_integer()), size :: pos_integer(), tries :: pos_integer(), update :: (-> number()) ) :: number()
Forecasts how many time periods are needed to complete size items
Related functions: forecast_duration/2 and forecast_items/2.
@spec forecast_duration(data :: [number()] | (-> number()), size :: pos_integer()) :: (-> number())
Returns a function for forecasting the duration to complete a number of items.
This function is a wrapper for forecast/4.
Arguments
`data` - either a data set to base the forecasting on, or a function that returns (random) numbers
`size` - the number of items to complete
@spec forecast_items(data :: [number()] | (-> number()), periods :: pos_integer()) :: (-> number())
Returns a function for forecasting the number of completed items in a number periods.
This function is a wrapper for forecast/4.
Arguments
`data` - either a data set to base the forecasting on, or a function that returns (random) numbers
`periods` - the number of periods to forecast the number of completed items for
@spec get_percentile(list(), non_neg_integer()) :: float()
@spec mc( iterations :: pos_integer(), fun :: (pos_integer() -> float()), options :: Keyword.t() ) :: {avg :: float(), sd :: float(), tries :: [float()]} | {avg :: float(), sd :: float()}
Basic Monte Carlo simulation to repeatedly run a simulation multiple times.
Options
`:collect_all?` - If true, collects data from each individual simulation run and returns this an the third element of the result tuple
Performs a nested bootstrap on sample data.