Inverse Cumulative Distribution Function

Inverse Cumulative Distribution Function

Inverse Cumulative Distribution Function

Description

Inverse Cumulative Distribution Function (ICDF) is the inverse of Cumulative Distribution Function (CDF). It helps to learn about the distribution of data by calculating the value associated with a specific cumulative probability in the dataset.

Why to use

To determine the value of the variable or feature associated with a specific probability.

When to use

For numerical variables having positive integer values.

When not to use

For numerical variables having values less than 0.

Prerequisites

  • The values of data points should be in the range between 0 and 1.
  • The data should not contain any missing values.

Input

One numerical variable having values between 0 and 1.

Output

  • ICDF Curve
  • Quantile values predicted by the ICDF

Statistical Methods used

  • Quantile function
  • Probability

Limitations

It can be used only on numerical data.


The Inverse Cumulative Distribution Function determines the original value of the randomly selected variable for the given probability value from the dataset.

By default, the data is sorted and then sent to the algorithm. Also, in the output Data tab, the resultant data appears in a sorted manner.

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