Fitting finite mixture of scale mixture of skew-normal
distributions.
Aldo Garay <amedina@ime.usp.br>, Marcos Prates
<marcosop@est.ufmg.br> and Victor Lachos
<hlachos@ime.unicamp.br>
Fit univariate non-linear scale mixture of
skew-normal(NL-SMSN) regression.

Fitting nonlinear models with scale mixture of skew-normal
distributions.

Fitting Nonlinear Models with Scale Mixture of Skew-Normal
Distributions
c(person("Marcos", "Prates", role=c("aut","cre","trl"),
email="marcosop@est.ufmg.br"),
person("Victor", "Lachos", role="aut"),
person("Aldo", "Garay", role="aut"))
Fit univariate non-linear scale mixture of skew-normal(NL-SMSN) regression, details in Garay, Lachos and Abanto-Valle (2011) <doi.org/10.1016/j.jkss.2010.08.003> and Lachos, Bandyopadhyay and Garay (2011) <doi.org/10.1016/j.spl.2011.03.019>.
Marcos Prates [aut, cre, trl],
Victor Lachos [aut],
Aldo Garay [aut]

Fit univariate non-linear scale mixture of skew-normal(NL-SMSN) regression, details in Garay, Lachos and Abanto-Valle (2011) <doi:10.1016/j.jkss.2010.08.003> and Lachos, Bandyopadhyay and Garay (2011) <doi:10.1016/j.spl.2011.03.019>.

c( person(given = c("John", "C"), family = "Nash", role =
c("aut", "cre"), email = "nashjc@uottawa.ca"),
person(given = "Duncan", family =
"Murdoch", role = "aut", email =
"murdoch.duncan@gmail.com") )
Provides tools for working with nonlinear least squares problems.
It is intended to eventually supersede the nls() function in the R distribution.
For example, nls() specifically does NOT deal with small or zero
residual problems as its Gauss-Newton method frequently stops with 'singular
gradient' messages. nlsr is based on the now-deprecated package nlmrt,
and has refactored functions and R-language symbolic derivative features.
minpack.lm, optimr, Rvmmin, Rcgmin, numDeriv, knitr,
rmarkdown, Ryacas, Deriv
John C Nash [aut, cre],
Duncan Murdoch [aut]

Provides tools for working with nonlinear least squares problems.
It is intended to eventually supersede the nls() function in the R distribution.
For example, nls() specifically does NOT deal with small or zero
residual problems. Its Gauss-Newton method frequently stops with 'singular
gradient' messages.
minpack.lm, optimr, Rvmmin, Rcgmin, numDeriv, knitr,
rmarkdown, Ryacas, Deriv, nlmrt