NNS.CDF: NNS CDF

In NNS: Nonlinear Nonparametric Statistics

NNS CDF

Description

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	integer; (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.

Author(s)

Fred Viole, OVVO Financial Systems

References

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

Viole, F. (2017) "Continuous CDFs and ANOVA with NNS" \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2139/ssrn.3007373")}

Examples

## Not run: 
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 = c(0,0))

## End(Not run)

NNS documentation built on Oct. 14, 2024, 5:09 p.m.