# 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 Nonparametric Correlation (Bivariate)

 cum_prob R Documentation

## Estimates the cumulative probability at one or more x values

### 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

cum_prob(h_est_obj, x, clipped, accelerate_series = TRUE)


### Arguments

 h_est_obj 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

## Not run:
hermite_est <- hermite_estimator(N = 10, standardize = TRUE,
est_type="univariate", observations = rnorm(30))
cdf_est <- cum_prob(hermite_est, c(0, 0.5, 1))
hermite_est <- hermite_estimator(N = 10, standardize = TRUE,
est_type="bivariate", observations = 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))

## End(Not run)


hermiter documentation built on May 31, 2023, 6:30 p.m.