Function reference • predx

All functions
`import_aedes_csv()` `export_aedes_csv()` `aedes_expected()`	Tools for working with Aedes challenge forecasts
`aedesdemo`	Example Aedes forecast
`Binary()` `is.Binary()` `predx_to_json(<Binary>)` `as.data.frame(<Binary>)` `transform_predx(<Binary>)`	Binary class: Binary predictions
`BinCat()` `is.BinCat()` `predx_to_json(<BinCat>)` `as.data.frame(<BinCat>)` `transform_predx(<BinCat>)`	BinCat class: Binned predictions with categorical bins
`BinLwr()` `is.BinLwr()` `predx_to_json(<BinLwr>)` `as.data.frame(<BinLwr>)` `transform_predx(<BinLwr>)`	BinLwr class: Binned predictions with sequential numeric bins
`check_bins_ascend()`	Title
`check_conversion_errors()` `collect_error()`	Title
`check_no_NAs()`	Check for NA entries
`check_probs_bins_length_match()`	Check that number of forecast bins matches number of probabilties.
`check_probs_gt0()`	Check that all probabilities are positive
`check_probs_lt1()`	Check that all probabilities are positive
`check_probs_sum_to_one()`	Check that probabilities sum to 1 (or approximately 1)
`check_single_value()`	Check that all probabilities are positive
`check_uniform_bin_size()`	Check that all bins have the same width.
`export_csv()`	Export a `predx` data frame as a `predx`-formatted CSV file
`export_json()`	Export a `predx` data frame as a `predx`-formatted JSON file
`import_flusight_csv()` `export_flusight_csv()` `to_flusight_pkg_format()` `prep_flusight()` `flusight_ilinet_expected()` `flusight_state_ilinet_expected()` `flusight_hospitalization_expected()` `recode_flusight_bin_end_notincl()`	Tools for working with FluSight forecasts
`flusightdemo`	Example FluSight forecast
`get_cats()`	Get vector of categories for a BinCat or SampleCat class predx object
`get_predx_colnames()`	Internal function returns the names of columns used for conversion to predx objects
`import_csv()`	Import a `predx`-formatted CSV file as a `predx` data frame
`import_json()`	Import a `predx`-formatted JSON file as a `predx` data frame
`Point()` `is.Point()` `predx_to_json(<Point>)` `as.data.frame(<Point>)` `transform_predx(<Point>)` `predx_to_json(<PointCat>)`	Point class: Point predictions
`PointCat()` `is.PointCat()` `as.data.frame(<PointCat>)` `transform_predx(<PointCat>)`	PointCat class: Point predictions for categorical variables
`validate_predx_df()` `is.predx_df()` `as.predx_df()`	Tools to check the `predx` data frames contain valid `predx_class` and `predx` columns and created them if needed.
`predx_to_json()`	Internal code to convert `predx` to JSON friendly representation.
`Sample()` `is.Sample()` `predx_to_json(<Sample>)` `as.data.frame(<Sample>)` `transform_predx(<Sample>)`	Sample class: Samples from a pdistribution
`SampleCat()` `is.SampleCat()` `predx_to_json(<SampleCat>)` `as.data.frame(<SampleCat>)` `transform_predx(<SampleCat>)`	SampleCat class: Samples from a distribution of categories or classifications.
`to_predx()`	Helper function for creating lists of `predx` objects (e.g. a column in a data frame containing a variety of `predx` objects)
`transform_predx()`	Transform a `predx` objects to a target predx class.
`verify_expected()`	Verify inclusion of expected predictions

Reference

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