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gets (version 0.4)

ols: OLS estimation

Description

OLS estimation with the QR decomposition and, for some options, computation of variance-covariance matrices

Usage

ols(y, x, tol=1e-07, LAPACK=FALSE, method=1, user.fun=NULL, user.options=NULL)

Arguments

y
numeric vector, the regressand
x
numeric matrix, the regressors
tol
numeric value. The tolerance for detecting linear dependencies in the columns of the regressors, see qr function. Only used if LAPACK is FALSE
LAPACK
logical, TRUE or FALSE (default). If true use LAPACK otherwise use LINPACK, see qr function
method
1 (default) or 2. Method 2 returns slightly more information, which means it is slightly slower. However, the information returned can be used to speed up the computation of variance-covariance matrices
user.fun
the name of the user-function (a character)
user.options
a list with arguments (entries) that are passed on to the user-function

Value

  • A list with some or all of the following elements:
  • qr
  • rank
  • qraux
  • pivot
  • xtxinv
  • xtx
  • xty
  • coefficients
  • fitted
  • residuals
  • resids2
  • rss
  • df
  • sigma2
  • omegahat
  • vcov

Details

method=1 or 2 only returns the OLS coefficient estimates together with the QR-information. method=1 is slightly faster than method=2. method=3 returns in addition the ordinary variance-covariance matrix of the OLS estimator. method=4 returns the White (1980) heteroscedasticity robust variance-covariance matrix in addition to the information returned by method=3, whereas method=5 does the same except that the variance-covariance matrix now is that of Newey and West (1987).

References

H. White (1980): 'A Heteroskedasticity-Consistent Covariance Matrix and a Direct Test for Heteroskedasticity', Econometrica 48, pp. 817-838. W. Newey and K. West (1987): 'A Simple Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix', Econometrica 55, pp. 703-708.

See Also

qr, solve.qr