smsn.nl: Fit univariate NL-SMSN regression

In nlsmsn: Fitting Nonlinear Models with Scale Mixture of Skew-Normal Distributions

Description

Return EM algorithm output for NL-SMSN regression for both "Homoscedastic" and "Heteroscedastic" (univaritate case, p=1).

Usage

smsn.nl(y, x = NULL, z = NULL, betas = NULL, sigma2 = NULL, 
shape = NULL, rho = NULL, 
nu = NULL, nlf = NULL, rho.func = 1, 
reg.type = "Homoscedastic", criteria = FALSE, 
family = "Skew.t", error = 1e-05, iter.max = 100)

Arguments

y	the response vector
x	the independent covariates
z	the independent covariates for sigma2. "Heteroscedastic" model ONLY!
betas	regression coefficient(s) vector
sigma2	initial value for the scale parameter
shape	initial value for the skewness parameter
rho	initial value for "Heteroscedastic" coefficient rho. "Heteroscedastic" model ONLY!
nu	the parameter of the scale variable (vector or scalar) of the SMSN family (kurtosis parameter). For the "Skew.cn" must be a vector of length 2 and values in (0,1)
nlf	non linear function for the regression
rho.func	Choose the type of heteroscedasticity for sigma2. If rho.func == 1 ( f(z,rho) = exp(z*rho) ) and rho.func == 2 ( f(z,rho) = z^rho ).
reg.type	the type of possible regression: "Homoscedastic" or "Ho"; "Heteroscedastic" or "He".
criteria	if TRUE, loglik, AIC, BIC will be calculated
family	distribution famility to be used in fitting ("t", "Skew.t", "Skew.cn", "Skew.slash", "Skew.normal", "Normal")
error	the covergence maximum error
iter.max	maximum iterations of the EM algorithm

Value

Estimated values of the location, scale, skewness, regression coefficients and "Heteroscedastic" coefficient (when reg.type = "He").

Author(s)

Aldo Garay [e-mail], Marcos Prates [e-mail] and Victor Lachos [e-mail]

References

Aldo M. Garay, Victor H. Lachos, Carlos A. Abanto-Valle (2011). "Nonlinear regression models based on scale mixture of skew-normal distributions". Journal of the Korean Stastical Society, 40, 115-124.\

Victor H. Lachos, Dipankar Bandyopadhyay and Aldo M. Garay (2011). "Heteroscedastic nonlinear regression models based on scale mixture of skew-normal distributions". Statistics -and Probability Letters, 81, 1208-1217.

Examples

 ##see examples in \code{\link{Oil}} and \code{\link{Ultrasonic}} 

nlsmsn documentation built on Jan. 21, 2021, 1:07 a.m.