# Exporting Marginal Distributions

# Obtaining Marginal Distributions

Marginal distributions should first be obtained using the `get_marginal_distributions()` function.

To obtain the marginal distributions for all variables you should only specify the dataset:

    library(RESIDE)
    marginals <- get_marginal_distributions(IST)

To obtain marginal distributions for select variables, you should specify the variables using the variables parameter:

    library(RESIDE)
    marginals <- get_marginal_distributions(
      IST,
      variables = c(
        "SEX",
        "AGE",
        "ID14",
        "RSBP",
        "RATRIAL",
        "SET14D",
        "DSIDED"
      )
    )

# Printing the Marginal Distributions Prior to Export

Marginal distributions can be printed when generating marginal distributions using the print parameter:

    library(RESIDE)
    marginals <- get_marginal_distributions(
      IST,
      print = TRUE
    )

Or from a stored marginals object:

    library(RESIDE)
    marginals <- get_marginal_distributions(IST)
    print(marginals)

# Exporting Marginal Distributions

Marginal distributions can be exported using the `export_marginal_distributions()` function, specifying the marginal distributions (generated by `get_marginal_distributions()’) and a folder path:

    library(RESIDE)
    marginals <- get_marginal_distributions(IST)
    export_marginal_distributions(
      marginals,
      folder_path = "/Users/ryan/marginals"
    )

This folder should exist and not contain any previously exported marginal distributions. You can create the folder automatically using the create_folder parameter:

    library(RESIDE)
    marginals <- get_marginal_distributions(IST)
    export_marginal_distributions(
      marginals,
      folder_path = "/Users/ryan/marginals",
      create_folder = TRUE
    )

## Files created by `export_marginal_distributions()`

The following files will be created by the `export_marginal_distributions()` function:

- binary_variables.csv - Contains the marginal distributions for binary variables including:
  - Variable Name
    - Mean
    - Number of Missing Observations
- categorical_variables.csv Contains the marginal distributions for categorical variables including:
  - Variable Name & Category Name
  - Number of Observations in Each Category
  - NB Missing Observations are coded as a separate category labelled missing.
- continuous_variables.csv - Contains the marginal distributions for continuous variables including:
  - Variable Name
  - Transformed Mean
  - Transformed Standard Deviation
  - Number of Missing Observations
  - Number of Decimal Places
- continuous_quantiles.csv - Contains the Quantile mapping to allow for back transformation. For each continuous variable this contains:
  - The original quantile value
  - The transformed quantile value
  - An epsilon value to indicate the amount of thinning applied
- summary.csv - Contains and overall summary of the dataset including:
  - Number of Rows
  - Number of Columns
  - Variable Names (for validation)

These files should then be sent to the user.

NB If there are no variables of a certain type the corresponding file will not be created.