# loclin: Multivariate local linear regression estimator at one point In regpro: Nonparametric Regression

## Description

Computes the value of a multivariate local linear regression estimator at one point.

## Usage

 `1` ```loclin(arg, x, y, h=1, kernel="gauss", type=0) ```

## Arguments

 `arg` d-vector; the point where the estimate is evaluated `x` n*d data matrix; the matrix of the values of the explanatory variables `y` n vector; the values of the response variable `h` a positive real number; the smoothing parameter of the kernel estimate `kernel` a character; determines the kernel function; either "gauss" or "uniform"; in the univariate case can also be "exp" `type` integer 0,...,d; if type=0, then the regression function is estimated, otherwise the first partial derivative of the variable indicated by type is estimated

a real number

## Author(s)

Jussi Klemela

`pcf.loclin`,

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```set.seed(1) n<-100 d<-2 x<-8*matrix(runif(n*d),n,d)-3 C<-(2*pi)^(-d/2) phi<-function(x){ return( C*exp(-sum(x^2)/2) ) } D<-3; c1<-c(0,0); c2<-D*c(1,0); c3<-D*c(1/2,sqrt(3)/2) func<-function(x){phi(x-c1)+phi(x-c2)+phi(x-c3)} y<-matrix(0,n,1) for (i in 1:n) y[i]<-func(x[i,])+0.01*rnorm(1) arg<-c(0,0) loclin(arg,x,y,h=0.5) ```

### Example output

```Loading required package: denpro
 0.1409435
```

regpro documentation built on May 1, 2019, 10:21 p.m.