stls.fit: Function for fitting STLS

In truncSP: Semi-parametric estimators of truncated regression models

Description

Function that utilizes optim to find STLS estimates of the regression coefficients for regression models with truncated response variables. Intended to be called through stls, not on its own, since stls also transforms data into the correct form etc.

Usage

stls.fit(formula,mf, point, direction, bet, ...)

Arguments

formula	a symbolic description of the model to be estimated
mf	the model.frame containing the variables to be used when fitting the model. stls transforms the model frame to the correct form before calling stls.fit. If stls.fit is called on its own the model frame needs to be transformed manually.
point	point of truncation
direction	direction of truncation
bet	starting values to be used by optim. Column matrix with p rows.
...	additional arguments to be passed to optim (see the documentation for stls for further details).

Value

a list with components:

startcoef	the starting values of the regression coefficients used by optim
coefficients	the named vector of coefficients
counts	number of iterations used by optim. See the documentation for optim for further details
convergence	from optim. An integer code. 0 indicates successful completion. Possible error codes are 1 indicating that the iteration limit maxit had been reached. 10 indicating degeneracy of the Nelder–Mead simplex.
message	from optim. A character string giving any additional information returned by the optimizer, or NULL.
residuals	the residuals of the model
df.residual	the residual degrees of freedom
fitted.values	the fitted values

Author(s)

Anita Lindmark and Maria Karlsson

See Also

stls

Examples

require(utils)
##Model frame
n <- 10000
x <- rnorm(n,0,2)
y <- 2+x+4*rnorm(n)
d <- data.frame(y=y, x=x)
dl0 <- subset(d, y>0)
mf <- model.frame(y~x, data=dl0)


##Starting values
lmmod <- lm(data=mf)
bet <- lmmod$coef
bet <- matrix(bet)

str(stls. <- stls.fit(y~x,mf,point=0,direction="left",bet))

truncSP documentation built on May 1, 2019, 8:46 p.m.