fsdaR (version 0.4-9)

mmreg.object: Description of mmreg Objects

Description

An object of class mmreg.object holds information about the result of a call to fsreg with method="MM".

Value

The object itself is basically a list with the following components:

beta

p-by-1 vector containing the MM estimate of regression coefficients.

auxscale

scalar, S estimate of the scale (or supplied external estimate of scale, if option InitialEst is not empty).

residuals

residuals.

fittedvalues

fitted values.

weights

n x 1 vector. Weights assigned to each observation.

Sbeta

p x 1 vector containing S estimate of regression coefficients (or supplied initial external estimate of regression coefficients, if option InitialEst is not empty)

Ssingsub

Number of subsets without full rank in the S preliminary part. Notice that out.singsub > 0.1*(number of subsamples) produces a warning.

outliers

kx1 vector containing the list of the k units declared as outliers or NULL if the sample is homogeneous.

conflev

Confidence level which is used to declare units as outliers. Usually conflev=0.95, 0.975, 0.99 (individual alpha) or conflev=1-0.05/n, 1-0.025/n, 1-0.01/n (simultaneous alpha). Default value is 0.975

rhofunc

Specifies the rho function which has been used to weight the residuals. If a different rho function is specified for S and MM loop then insted of rhofunc we will have rhofuncS and rhofuncMM.

rhofuncparam

Vector which contains the additional parameters for the specified rho function which has been used. For hyperbolic rho function the value of k =sup CVC. For Hampel rho function the parameters a, b and c. If a different rho function is specified for S and MM loop then insted of rhofuncparam we will have rhofuncparamS and rhofuncparamMM.

X

the data matrix X

y

the response vector y

The object has class "mmreg".

Examples

# NOT RUN {
    (out <- fsreg(Y~., data=hbk, method="MM"))
    class(out)
    summary(out)
# }