Skip to contents

NNS CDF

Source: R/Partial_Moments.R
NNS.CDF.Rd

This function generates an empirical CDF using partial moment ratios LPM.ratio, and resulting survival, hazard and cumulative hazard functions.

Usage

NNS.CDF(variable, degree = 0, target = NULL, type = "CDF", plot = TRUE)

Arguments

variable

a numeric vector or data.frame of >= 2 variables for joint CDF.

degree

numeric; (degree = 0) (default) is frequency, (degree = 1) is area.

target

numeric; NULL (default) Must lie within support of each variable.

type

options("CDF", "survival", "hazard", "cumulative hazard"); "CDF" (default) Selects type of function to return for bi-variate analysis. Multivariate analysis is restricted to "CDF".

plot

logical; plots CDF.

Value

Returns:

  • "Function" a data.table containing the observations and resulting CDF of the variable.

  • "target.value" value from the target argument.

References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" (ISBN: 1490523995)

Viole, F. (2017) "Continuous CDFs and ANOVA with NNS" doi:10.2139/ssrn.3007373

Author

Fred Viole, OVVO Financial Systems

Examples

if (FALSE) { # \dontrun{
set.seed(123)
x <- rnorm(100)
NNS.CDF(x)

## Empirical CDF (degree = 0)
NNS.CDF(x)

## Continuous CDF (degree = 1)
NNS.CDF(x, 1)

## Joint CDF
x <- rnorm(5000) ; y <- rnorm(5000)
A <- cbind(x,y)

NNS.CDF(A, 0)

## Joint CDF with target
NNS.CDF(A, 0, target = rep(0, ncol(A)))
} # }