# 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.