LRMDE: Performs minimum distance estimation in linear regression...

In LinearRegressionMDE: Minimum Distance Estimation in Linear Regression Model

Description

Performs minimum distance estimation in linear regression model: Y=Xb + error

Usage

LRMDE(Y, X)

Arguments

Y	- Response variable in linear regression model
X	- Explanatory variable in linear regression model

Value

Returns betahat - Minimum distance estimator of b

References

[1] Koul, H. L (1985). Minimum distance estimation in linear regression with unknown error distributions. Statist. Probab. Lett., 3 1-8.

[2] Koul, H. L (1986). Minimum distance estimation and goodness-of-fit tests in first-order autoregression. Ann. Statist., 14 1194-1213.

[3] Koul, H. L (2002). Weighted empirical process in nonlinear dynamic models. Springer, Berlin, Vol. 166

See Also

ARMDE

Examples

X <- matrix(c(1,1,3,4, 4,2), nrow=3, ncol=2)
Y <- c(1,-5, 8)
bhat <- LRMDE(Y,X)

Example output

Dimension of X does not match dimension of Y

LinearRegressionMDE documentation built on May 2, 2019, 5:54 a.m.