[R-SIG-Finance] Help understanding how nls parses the formula argument to estimate the model
Joe Byers
joe-byers at utulsa.edu
Thu Sep 21 19:50:19 CEST 2006
I could use some help understanding how nls parses the formula argument
to a model.frame and estimates the model. I am trying to utilize the
functionality of the nls formula argument to modify garchFit() to handle
other variables in the mean equation besides just an arma(u,v)
specification.
My nonlinear model is
y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,
start=list(w=.5,a=.1,p=.5,b=init.y$coef[2],int=init.y$coef[1] ),
control=list(maxiter=1000000,minFactor=1e-18))
where t is change in daily temperatures, id is just a time trend and the
a*sin is a one year fourier series.
I have tried to debug the nls code using the following code
t1<-data.frame(t=as.vector(x),id=index(x))
data=t1;
formula <- as.formula(t ~ a *sin(w *2* pi/365 * id + p) + b * id + int);
varNames <- all.vars(formula)
algorithm<-'default';
mf <- match.call(definition=nls,expand.dots=FALSE,
call('nls',formula, data=parent.frame(),start,control = nls.control(),
algorithm = "default", trace = FALSE,
subset, weights, na.action, model = FALSE, lower = -Inf,
upper = Inf));
mWeights<-F;#missing(weights);
start=list(w=.5,a=.1,p=.5,b=init.y$coef[2],int=init.y$coef[1] );
pnames <- names(start);
varNames <- varNames[is.na(match(varNames, pnames, nomatch = NA))]
varIndex <- sapply(varNames,
function(varName, data, respLength) {
length(eval(as.name(varName), data))%%respLength == 0},
data, length(eval(formula[[2]], data))
);
mf$formula <- as.formula(paste("~", paste(varNames[varIndex],
collapse = "+")), env = environment(formula));
mf$start <- NULL;mf$control <- NULL;mf$algorithm <- NULL;
mf$trace <- NULL;mf$model <- NULL;
mf$lower <- NULL;mf$upper <- NULL;
mf[[1]] <- as.name("model.frame");
mf<-evalq(mf,data);
n<-nrow(mf)
mf<-as.list(mf);
wts <- if (!mWeights)
model.weights(mf)
else rep(1, n)
if (any(wts < 0 | is.na(wts)))
stop("missing or negative weights not allowed")
m <- switch(algorithm,
plinear = nlsModel.plinear(formula, mf, start, wts),
port = nlsModel(formula, mf, start, wts, upper),
nlsModel(formula, mf, start, wts));
I am struggling with the environment issues associated with performing
these model.frame operations with the eval functions.
thank you
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