Estimation methods

Standard estimation methods

These functions perform paramter estimation, diagnostics and print reports.

glm

Solves the generalized linear model problems.

gmmFit

Estimate parameters using generalized method of moments.

gmmFitIV

Estimate instrumental variables model using the generalized method of moments.

olsmt

Computes a least squares regression.

quantileFit

Perform linear quantile regression.

quantileFitLoc

Perform local linear or quadratic quantile regression.

Standard error methods

clusterSE

Computes the White cluster-robust standard errors.

robustSE

Computes the Huber-White heteroscedastic robust standard errors. The procedure uses the “sandwich” variance-covariance estimator with a small sample correction of \((n)/(n−1)\).

Lower level estimation

Note

For most cases, the slash operator b_hat = y / X or olsqr() are the preferred methods to compute least-squares estimates.

ldlsol

Computes the solution to a system of linear equations given a factorized matrix returned by the function ldlp and one or more right hand sides.

lusol

Computes the solution of \(LUx=b\) where \(L\) and \(U\) are matrix factors returned by lu.

olsqr

Computes OLS coefficients using \(QR\) decomposition.

olsqr2

Computes OLS coefficients, residuals, and predicted values using the \(QR\) decomposition.

solpd

Solves a set of positive definite linear equations.