emg-package: Exponentially Modified Gaussian (EMG) Distribution

In emg: Exponentially Modified Gaussian (EMG) Distribution

Description

Provide basic functions for a mixture of gaussian and exponential distributions.

Details

Package:	emg
Type:	Package
Date:	2012-01-03
License:	GPL 2.0
LazyLoad:	yes

Provides basic distribution functions for the EMG model, pemg, demg, qemg and remg. As well as an MLE estimation routine emg.mle.

Author(s)

Shawn Garbett, Mark Kozdoba, Maintainer: Shawn Garbett <[e-mail]>

References

Gladney H.M., B.F. Dowden, J.D. Swalen. Computer-Assisted Gas-Liquid Chromatography. Anal. Chem., 1969, 41(7):883-8.

Golubev A. Exponentially modified Gaussian (EMG) relevance to distributions related to cell proliferation and differentiation. J Theor Biol. 2010 Jan 21;262(2):257-66.

Grushka E. Charaterization of Exponentially Modified Peaks in Chromatography. Anal. Chem., 1972, 44(11):1733-38.

See Also

EMG emg.mle Normal Exponential

Examples

  y <- remg(200)
  hist(y, freq=FALSE, ylim=c(0, 0.35), breaks=20)
  x <- 1:100/100 * 11 - 3
  lines(x, demg(x))
  m <- emg.mle(y)
  sqrt(diag(m@vcov)) # Show stderr in estimate
  ks.test(y, "pemg", 0, 1, 1)

Example output

Loading required package: stats4
       mu     sigma    lambda 
0.1688484 0.1039208 0.1712347 

	One-sample Kolmogorov-Smirnov test

data:  y
D = 0.062531, p-value = 0.4147
alternative hypothesis: two-sided

emg documentation built on July 1, 2020, 10:25 p.m.