Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/dfr_robhetroLS.R
Robust Generalized Multistage Estimate (RGME) for heteroscedastic error case, robust form of CLsME (See dfr.hetroLS
)
1 2 3 | dfr.robhetroLS(formula, data, start = getInitial(formula, data), control =
nlr.control(tolerance = 0.001, minlanda = 1/2^10,
maxiter = 25 * length(start)), robfunc, varmodel, tau = varmodel$par, method = "NM", ...)
|
formula |
|
data |
list of data include responce and predictor. |
start |
list of parameter values of nonlinear model function (θ. in f(x,θ)). |
control |
list of |
robfunc |
nl.form object of robust function used for downgrading. |
varmodel |
|
tau |
list of initial values for variance model function |
method |
="NLM" means using |
... |
extra arguments to nonlinear regression model, heteroscedastic variance function, robust loss function or its tuning constants. |
Robustified form of Least square based estimate for nonlinear regression with hetroscedastic error when variance is a general function of unkown parameters.
return object nl.fitt.rgn
for nonlinear regression wuth heterogeneous error.
parameters |
nonlinear regression parameter estimate of θ. |
correlation |
of fited model. |
form |
|
response |
computed response. |
predictor |
computed (right side of formula) at estimated parameter with gradient and hessian attributes. |
curvature |
list of curvatures, see |
history |
matrix of convergence history, collumns include: convergence index, parameters, minimized objective function, convergence criterion values, or other values. These values will be used in |
method |
|
data |
list of called data. |
sourcefnc |
Object of class |
Fault |
|
htheta |
robust loss value including gradient and hessain attributes. |
rho |
computed robust rho function, including gradient and hessain attributes. |
ri |
estimated residuals, including gradient and hessain attributes. |
curvrob |
curvature |
robform |
|
vm |
covariance matrix, diagonal of variance model predicted values. |
rm |
cholesky decomposition of vm. |
gresponse |
transformed of response by rm, include gradinet and hessian attributes. |
gpredictor |
transformed of predictor by rm, include gradinet and hessian attributes. |
hetro |
|
Heteroscedastic variance can have several cases, this function assume variance is parameteric function of predictor (H(t;τ)). If data does not include the predictor variable of varmodel
(t), the predicted of function model f(x;\hat θ) will replace for (t), otherwise user have to defin (t) or (x) as predictor variable of (H).
This function is derivative free form of nl.robhetroLS
and robust form of dfr.hetroLS
. Since it is slow algorithm it is recomneded to use larger values for maximum number of iterations in nlr.control
options.
Hossein Riazoshams, May 2014. Email: riazihosein@gmail.com URL http://www.riazoshams.com/nlr/
Riazoshams, H. (2012), Robustifying the Least Squares estimate of parameters of variance model function in nonlinear regression with heteroscedastic variance, Poster Presentation, Royal Statistical Society Conference (RSS) 2012, Telford, UK.
dfr.hetro
, nlr.control
, fittmethod
, nl.form
, nl.fitt.rob
, nl.fitt.rgn
, nlr.control
, nl.robhetroLS
, dfr.hetroLS
1 | "dfr.robhetroLS"
|
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