Rnorm.exp {groHMM} | R Documentation |
Distrubtion function devined by: alpha*Normal(mean, varience)+(1-alpha) *Exponential(lambda).
Rnorm.exp(xi, wi = rep(1, NROW(xi)), guess = c(0.5, 0, 1, 1), tol = sqrt(.Machine$double.eps), maxit = 10000)
xi |
A vector of observations, assumed to be real numbers in the inveraval (-Inf,+Inf). |
wi |
A vector of weights. Default: vector of repeating 1; indicating all observations are weighted equally. (Are these normalized internally?! Or do they have to be [0,1]?) |
guess |
Initial guess for paremeters. Default: c(0.5, 0, 1, 1). |
tol |
Convergence tolerance. Default: sqrt(.Machine$double.eps). |
maxit |
Maximum number of iterations. Default: 10,000. |
Fits nicely with data types that look normal overall, but have a long tail starting for positive values.
Returns a list of parameters for the best-fit normal distribution (alpha, mean, varience, and lambda).
Charles G. Danko