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)

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.