Description Usage Arguments Value Note Author(s) References See Also Examples
Predicted values from a local polynomials of degree less than 2.
Missing values are not allowed.
1 2 |
x |
A numeric vector of explanatory variable of length n. |
y |
A numeric vector of variable to be explained of length n. |
criterion |
Character string. If the bandwidth
( |
bandwidth |
The kernel bandwidth smoothing parameter (a numeric vector of either length 1). |
kernel |
Character string which allows to choose between gaussian kernel
( |
control.par |
A named list that control optional parameters. The
two components are |
cv.options |
A named list which controls the way to do cross
validation with component |
Returns an object of class npregress
which is a list including:
bandwidth |
The kernel bandwidth smoothing parameter. |
residuals |
Vector of residuals. |
fitted |
Vector of fitted values. |
df |
The effective degree of freedom of the smoother. |
call |
A list containing four components: |
criteria |
either a named list containing the bandwidth search
grid and all the criteria ( |
See locpoly
for fast binned implementation
over an equally-spaced grid of local polynomial. See ibr
for univariate and multivariate smoothing.
Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.
Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.
predict.npregress
,
summary.npregress
,
locpoly
, ibr
1 2 3 4 5 6 7 8 9 10 11 12 |
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-20. For overview type 'help("mgcv-package")'.
Residuals:
Min 1Q Median 3Q Max
-0.32219 -0.09171 0.01530 0.09731 0.27988
Residual standard error: 0.1453 on 80.4 degrees of freedom
user
"No Informative Criterion"
Kernel: gaussian (with 19.6 df)
Bandwidth: 0.02 chosen by user
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.