codeberg-pchausse.r-universe.dev

[pchausse] malp 1.2

pchausse@uwaterloo.ca (Pierre Chausse) — Mon, 02 Nov 2026 19:27:13 GMT

Provides tools for estimation and prediction using Maximum Agreement Linear Predictors (MALPs). MALPs provide an alternative to least squares linear predictors when agreement between predicted and observed values, as measured by Lin's Concordance Correlation Coefficient (CCC), is of primary interest. Applications include missing value imputation and calibration studies. The package includes functions for model estimation, prediction, statistical inference, cross-validation, and model diagnostics. The implemented methodology is described in Kim et al. (2026) .

[pchausse] causalSLSE 0.4-2

pchausse@uwaterloo.ca (Pierre Chausse Developer) — Fri, 16 Oct 2026 15:02:31 GMT

Several causal effects are measured using least squares regressions and basis function approximations. Backward and forward selection methods based on different criteria are used to select the basis functions.

[pchausse] numericalecon 0.0-1

pchausse@uwaterloo.ca (Pierre Chausse) — Fri, 25 Sep 2026 16:59:01 GMT

This package includes tools and functions used in the numerical course offered at the University of Waterloo

[pchausse] SEIR 0.1-0

pchausse@uwaterloo.ca (Pierre Chausse) — Fri, 25 Sep 2026 14:23:59 GMT

This is a simple model for the spread of a virus. It is the solution to a system of differential equations with plot methods to visualize the solution.

[pchausse] funcreg 0.0-1

pchausse@uwaterloo.ca (Pierre Chausse) — Fri, 25 Sep 2026 14:10:37 GMT

This package is complementary to the fda package. It includes function to choose smoothing parameters and to estimate models with multiple functional regressors.

[pchausse] momentfit 1.0-1

pchausse@uwaterloo.ca (Pierre Chausse) — Tue, 22 Sep 2026 15:04:49 GMT

Several classes for moment-based models are defined. The classes are defined for moment conditions derived from a single equation or a system of equations. The conditions can also be expressed as functions or formulas. Several methods are also offered to facilitate the development of different estimation techniques. The methods that are currently provided are the Generalized method of moments (Hansen 1982; ), for single equations and systems of equation, and the Generalized Empirical Likelihood (Smith 1997; , Kitamura 1997; , Newey and Smith 2004; , and Anatolyev 2005 ). Some work is being done to add tools to deal with weak and/or many instruments. This includes K-Class estimators (Limited Information Maximum Likelihood and Fuller), Anderson and Rubin statistic test, etc.

[pchausse] gmm 1.9-2

pchausse@uwaterloo.ca (Pierre Chausse) — Tue, 22 Sep 2026 14:55:21 GMT

It is a complete suite to estimate models based on moment conditions. It includes the two step Generalized method of moments (Hansen 1982; ), the iterated GMM and continuous updated estimator (Hansen, Eaton and Yaron 1996; ) and several methods that belong to the Generalized Empirical Likelihood family of estimators (Smith 1997; , Kitamura 1997; , Newey and Smith 2004; , and Anatolyev 2005 ).

[pchausse] metricsUW 0.2-0

pchausse@uwaterloo.ca (Pierre Chausse) — Tue, 22 Sep 2026 14:12:55 GMT

Functions used in my econometrics courses to generate solutions, print results and generate data.