h 
Vector of q elements, where q is the number of
rows in newdata , i.e. the number of query points. The element
in position i is the estimate of the value of the unknown function
in the query point newdata[i,] . The component h is
always returned.

t 
Matrix of z*q elements, where z=z2 i.e., number of
parameters of a quadratic model if at least one model of degree 2
was identified (see quaIdPar in lazy.control ),
otherwise z=z1 i.e.,
number of parameters of a linear model if at least one model of
degree 1 was identified (see linIdPar in
lazy.control ), or z=1 if only
models of degree 0 where considered. In the general case,
the elements of the vector t[,j]=c(a0, a1,..., an, a11,
a12,..., a22, a23,..., a33, a34,..., ann) are
the parameters of the local model used for estimating
the function in the j th query point: the crossterms terms
a11,a12,...,ann wil be missing if no quadratic model is
identified and the terms a1,...,an , will be missing if
no linear model is identified. If, according to cmbPar (see
lazy.control ), estimations are to be performed by a
combination of models, the elements of t[,j] are a weighted
average of the parameters
of the selected models where the weight of each model is the
inverse of the a leaveoneout estimate of the variances of the
model itself. REMARK: a translation of the axes is considered
which centers all the local models in the respective query point.

k 
Vector of q elements. Selected number of neighbors
for each query point. If, according to cmbPar (see
lazy.control ), a local
combination of models is considered, k[j] is the largest
value among the number of neighbors used by the selected models
for estimating the value in the j th query point.

S 
List of up to 3 components: Each component is a matrix
containing an estimate, obtained through a leaveoneout
crossvalication, of the variance of local models.
con Matrix of idM0*q elements, where
idM0 is the maximum number of neighbors used to fit local
polynomial models of degree 0 (see lazy.control ):
Estimated
variance of all the constant
models identified for each query point. If no constant model
is identified (see conIdPar and cmbPar in
lazy.control ) S$con is not returned.
lin Matrix of idM1*q elements, where
idM1 is the maximum number of neighbors used to fit local
polynomial models of degree 1 (see lazy.control ):
Estimated
variance of all the linear
models identified for each query point. If no linear model
is identified (see linIdPar and cmbPar in
lazy.control ) S$lin is not returned.
qua Matrix of idM2*q elements, where
idM1 is the maximum number of neighbors used to fit local
polynomial models of degree 1 (see lazy.control ):
Estimated variance of all the quadratic
models identified for each query point. If no quadratic model
is identified (see quaIdPar and cmbPar in
lazy.control ) S$qua is not returned.
The component S is returned only if S.out=TRUE in
the function call.

T 
List of up to 3 components:
con Array of z0*idM0*q elements, where
z0=1 is the number of parameters of a model of degree
0. The element T$con[1,i,j]=a0 is the single parameter of
the local model identified on i neighbors of the
q th query point.
lin Array of z1*idM1*q elements where, if
n is the dimensionality of the input space,
z1=n+1 is the number of parameter of a model of degree
1. The vector T$lin[,i,j]=c(a0,a1,...,an) is the
vector of parameters of
the local model identified on i neighbors of the
q th query point. In particular, a0 is the
constant term, a1 is the parameter associated with the
first input variable and so on.
qua Array of z2*idM2*q elements where, if
n is the dimensionality of the input space,
z2=(n+1)*(n+2)/2 is the number of parameter of a model
of degree 2. The vector
T$qua[,i,j]=c(a0, a1,..., an, a11,
a12,..., a22, a23,..., a33, a34,..., ann)
is the vector of parameters of the local quadratic model
identified on i neighbors of the q th query
point. In particular, a0,...,a1 are the constant and
liner parameters as in T$lin , while
a11,a12,...,ann are the quadratic ones: a11
is associated with the quadratic term x1^2 , a12
with the crossterm x1*x2 , and so on.
REMARK: a translation of the axes is considered
which centers all the local models in the respective query
point. The component T is returned only if
T.out=TRUE in the function call.

I 
Matrix of idM*q elements, where idM is the
largest of idM0 , idM1 , and idM2 . Contains the
index of the neighbors of each query point in newdata .
In particular, I[i,j] is the i th nearest neighbor of
the q th query point.
