# cum_prob: Estimates the cumulative probability at one or more x values In hermiter: Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Spearman's Correlation (Bivariate)

## Description

This method calculates the cumulative probability at a vector of x values in the univariate case. In the bivariate case, the method calculates the probability density values for a matrix of x values, each row of which represents a 2-d point.

## Usage

 1 cum_prob(this, x, clipped, accelerate_series = TRUE)

## Arguments

 this A hermite_estimator_univar or hermite_estimator_bivar object. x A numeric vector (univariate) or a numeric matrix (bivariate). Values at which to calculate the cumulative probability. clipped A boolean value. This value determines whether cumulative probabilities are clipped to lie between 0 and 1. accelerate_series A boolean value. This value determines whether Hermite series acceleration is applied.

## Details

The object must be updated with observations prior to the use of the method.

## Value

A numeric vector of cumulative probability values.

## Examples

 1 2 3 4 5 6 7 8 9 10 hermite_est <- hermite_estimator(N = 10, standardize = TRUE, est_type="univariate") hermite_est <- update_batch(hermite_est, rnorm(30)) cdf_est <- cum_prob(hermite_est, c(0, 0.5, 1)) hermite_est <- hermite_estimator(N = 10, standardize = TRUE, est_type="bivariate") hermite_est <- update_batch(hermite_est, x = matrix(rnorm(60), nrow=30, ncol=2,byrow=TRUE)) cdf_est <- cum_prob(hermite_est, matrix(c(0,0,0.5,0.5,1,1),nrow=3, ncol=2,byrow=TRUE))

hermiter documentation built on Nov. 17, 2021, 1:07 a.m.