dist-distCheck: Distribution Check In fBasics: Rmetrics - Markets and Basic Statistics

Description

Tests properties of an R implementation of a distribution, i.e. of all four of its “dpqr” functions.

Usage

 1 distCheck(fun = "norm", n = 1000, robust = TRUE, subdivisions = 100, ...)

Arguments

 fun a character string denoting the name of the distribution. n an integer specifying the number of random variates to be generated. robust logical flag, should robust estimates be used? By default TRUE. subdivisions integer specifying the numbers of subdivisions in integration. ... the distributional parameters.

Examples

 1 2 3 4 5 distCheck("norm", mean = 1, sd = 1) distCheck("lnorm", meanlog = 0.5, sdlog = 2, robust=FALSE) ## here, true E(X) = exp(mu + 1/2 sigma^2) = exp(.5 + 2) = exp(2.5) = 12.182 ## and Var(X) = exp(2*mu + sigma^2)*(exp(sigma^2) - 1) = 7954.67

Example output

Distribution Check for: norm
Call: distCheck(fun = "norm", mean = 1, sd = 1)

1. Normalization Check:
NORM 1 with absolute error < 1.6e-05

2. [p-pfun(qfun(p))]^2 Check:
[,1] [,2] [,3] [,4] [,5] [,6]  [,7]
p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
RMSE
2.205081e-17

3. r(1000) Check:
MEAN   VAR
SAMPLE 1.01 0.841
X   1 with absolute error < 4.4e-07
X^2 2 with absolute error < 7.9e-07
MEAN VAR
EXACT     1   1

normCheck    rmseCheck meanvarCheck
TRUE         TRUE        FALSE

Distribution Check for: lnorm
Call: distCheck(fun = "lnorm", robust = FALSE, meanlog = 0.5, sdlog = 2)

1. Normalization Check:
NORM 0.9999976 with absolute error < 7.6e-05

2. [p-pfun(qfun(p))]^2 Check:
[,1] [,2] [,3] [,4] [,5] [,6]  [,7]
p 0.001 0.01  0.1  0.5  0.9 0.99 0.999
P 0.001 0.01  0.1  0.5  0.9 0.99 0.999
RMSE
2.205081e-17

3. r(1000) Check:
MEAN  VAR
SAMPLE 15.6 9290
X   12.18247 with absolute error < 0.0012
X^2 8103.065 with absolute error < 0.64
MEAN  VAR
EXACT  12.2 7950

normCheck    rmseCheck meanvarCheck
TRUE         TRUE        FALSE

fBasics documentation built on March 13, 2020, 9:09 a.m.