mle-utils: Utility Methods for S3 class triangle_mle

In triangle: Distribution Functions and Parameter Estimates for the Triangle Distribution

Utility Methods for S3 class triangle_mle

Description

Utility Methods for S3 class triangle_mle

Usage

## S3 method for class 'triangle_mle'
summary(object, ...)

## S3 method for class 'triangle_mle'
print(x, ...)

## S3 method for class 'triangle_mle'
coef(object, ...)

## S3 method for class 'triangle_mle'
logLik(object, ...)

## S3 method for class 'triangle_mle'
AIC(object, ..., k = 2)

## S3 method for class 'triangle_mle'
BIC(object, ...)

## S3 method for class 'triangle_mle'
vcov(object, ...)

## S3 method for class 'triangle_mle'
profile(fitted, ...)

## S3 method for class 'triangle_mle'
confint(object, parm, level = 0.95, ...)

Arguments

object	class triangle_mle from a call to triangle_mle()
...	not used except for print (other arguments passed to printCoefmat)
x	the triangle_mle object
k	the penalty per parameter to be used; the default k = 2
fitted	an object of class triangle_mle
parm	parameters
level	confidence interval level

Value

an object of class summary.mle

x invisibly

a vector of coefficients

an object of class logLik

the AIC

the BIC

the variance co-variance matrix

an object of class profile.mle

an object of class profile.mle

Examples

set.seed(1234)
x <- rtriangle(100, 0, 1, 0.5)
mle1 <- triangle_mle(x)
summary(mle1)
print(mle1)
coef(mle1)
logLik(mle1)
AIC(mle1)
BIC(mle1)
vcov(mle1)
## Not run: 
  prof <- profile(mle1)
  stats4::plot(prof)
  confint(mle1, 1:3, level = 0.95)

## End(Not run)

triangle documentation built on Dec. 28, 2022, 2:09 a.m.