Vargas Sepulveda M (2024). capybara: Fast and Memory Efficient Fitting of Linear Models With High-Dimensional Fixed Effects. -R package version 0.3.5, https://github.com/pachadotdev/capybara, https://pacha.dev/capybara/. +R package version 0.4, https://github.com/pachadotdev/capybara, https://pacha.dev/capybara/.
@Manual{,
title = {capybara: Fast and Memory Efficient Fitting of Linear Models With High-Dimensional
Fixed Effects},
author = {Mauricio {Vargas Sepulveda}},
year = {2024},
- note = {R package version 0.3.5, https://github.com/pachadotdev/capybara},
+ note = {R package version 0.4, https://github.com/pachadotdev/capybara},
url = {https://pacha.dev/capybara/},
}
diff --git a/docs/index.html b/docs/index.html
index fa71a2e..d22ec93 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -46,7 +46,7 @@
diff --git a/docs/news/index.html b/docs/news/index.html
index 0419980..ad13881 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -17,7 +17,7 @@
@@ -57,6 +57,9 @@ NEWS.md
+
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 17fa80f..2b54fe9 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -3,5 +3,5 @@ pkgdown: 2.0.7
pkgdown_sha: ~
articles:
intro: intro.html
-last_built: 2024-03-04T01:22Z
+last_built: 2024-03-04T05:22Z
diff --git a/docs/reference/apes.html b/docs/reference/apes.html
index 6f0e2f0..90061c4 100644
--- a/docs/reference/apes.html
+++ b/docs/reference/apes.html
@@ -1,14 +1,14 @@
R/apes.R
apes.Rdapes is a post-estimation routine that can be used
- to estimate average partial effects with respect to all covariates in the
- model and the corresponding covariance matrix. The estimation of the
- covariance is based on a linear approximation (delta method) plus an
- optional finite population correction. Note that the command automatically
- determines which of the regressors are binary or non-binary.
Remark: The routine currently does not allow to compute average - partial effects based on functional forms like interactions and polynomials.
+partial effects based on functional forms like interactions and polynomials.The function apes returns a named list of class
"apes".
The function apes returns a named list of class
+"apes".
Cruz-Gonzalez, M., I. Fernández-Val, and M. Weidner (2017). "Bias - corrections for probit and logit models with two-way fixed effects". The - Stata Journal, 17(3), 517-545.
+corrections for probit and logit models with two-way fixed effects". The +Stata Journal, 17(3), 517-545.Czarnowske, D. and A. Stammann (2020). "Fixed Effects Binary - Choice Models: Estimation and Inference with Long Panels". ArXiv e-prints.
+Choice Models: Estimation and Inference with Long Panels". ArXiv e-prints.Fernández-Val, I. and M. Weidner (2016). "Individual and time - effects in nonlinear panel models with large N, T". Journal of Econometrics, - 192(1), 291-312.
+effects in nonlinear panel models with large N, T". Journal of Econometrics, +192(1), 291-312.Fernández-Val, I. and M. Weidner (2018). "Fixed effects - estimation of large-t panel data models". Annual Review of Economics, 10, - 109-138.
+estimation of large-t panel data models". Annual Review of Economics, 10, +109-138.Hinz, J., A. Stammann, and J. Wanner (2020). "State Dependence - and Unobserved Heterogeneity in the Extensive Margin of Trade". ArXiv - e-prints.
+and Unobserved Heterogeneity in the Extensive Margin of Trade". ArXiv +e-prints.Neyman, J. and E. L. Scott (1948). "Consistent estimates based on - partially consistent observations". Econometrica, 16(1), 1-32.
+partially consistent observations". Econometrica, 16(1), 1-32.R/bias_corr.R
bias_corr.RdPost-estimation routine to substantially reduce the incidental
- parameter bias problem. Applies the analytical bias correction derived by
- Fernández-Val and Weidner (2016) and Hinz, Stammann, and Wanner (2020) to
- obtain bias-corrected estimates of the structural parameters and is
- currently restricted to binomial with 1,2,3-way fixed
- effects.
binomial with 1,2,3-way fixed
+effects.
Czarnowske, D. and A. Stammann (2020). "Fixed Effects Binary - Choice Models: Estimation and Inference with Long Panels". ArXiv e-prints.
+Choice Models: Estimation and Inference with Long Panels". ArXiv e-prints.Fernández-Val, I. and M. Weidner (2016). "Individual and time - effects in nonlinear panel models with large N, T". Journal of Econometrics, - 192(1), 291-312.
+effects in nonlinear panel models with large N, T". Journal of Econometrics, +192(1), 291-312.Fernández-Val, I. and M. Weidner (2018). "Fixed effects - estimation of large-t panel data models". Annual Review of Economics, 10, - 109-138.
+estimation of large-t panel data models". Annual Review of Economics, 10, +109-138.Hahn, J. and G. Kuersteiner (2011). "Bias reduction for dynamic - nonlinear panel models with fixed effects". Econometric Theory, 27(6), - 1152-1191.
+nonlinear panel models with fixed effects". Econometric Theory, 27(6), +1152-1191.Hinz, J., A. Stammann, and J. Wanner (2020). "State Dependence - and Unobserved Heterogeneity in the Extensive Margin of Trade". ArXiv - e-prints.
+and Unobserved Heterogeneity in the Extensive Margin of Trade". ArXiv +e-prints.Neyman, J. and E. L. Scott (1948). "Consistent estimates based on - partially consistent observations". Econometrica, 16(1), 1-32.
+partially consistent observations". Econometrica, 16(1), 1-32.R/capybara-package.R
capybara-package.Rdfeglm can be used to fit generalized linear models
- with many high-dimensional fixed effects. The estimation procedure is based
- on unconditional maximum likelihood and can be interpreted as a
- “weighted demeaning” approach.
Remark: The term fixed effect is used in econometrician's sense of - having intercepts for each level in each category.
+having intercepts for each level in each category.If feglm does not converge this is often a sign of
- linear dependence between one or more regressors and a fixed effects
- category. In this case, you should carefully inspect your model
- specification.
Gaure, S. (2013). "OLS with Multiple High Dimensional Category - Variables". Computational Statistics and Data Analysis, 66.
+Variables". Computational Statistics and Data Analysis, 66.Marschner, I. (2011). "glm2: Fitting generalized linear models - with convergence problems". The R Journal, 3(2).
+with convergence problems". The R Journal, 3(2).Stammann, A., F. Heiss, and D. McFadden (2016). "Estimating Fixed - Effects Logit Models with Large Panel Data". Working paper.
+Effects Logit Models with Large Panel Data". Working paper.Stammann, A. (2018). "Fast and Feasible Estimation of Generalized - Linear Models with High-Dimensional k-Way Fixed Effects". ArXiv e-prints.
+Linear Models with High-Dimensional k-Way Fixed Effects". ArXiv e-prints.feglm Control ParametersSet and change parameters used for fitting feglm.
- Termination conditions are similar to glm.
glm.
A wrapper for feglm with
- family = gaussian().
family = gaussian().
The function felm returns a named list of class
"felm".
The function felm returns a named list of class
+"felm".
Gaure, S. (2013). "OLS with Multiple High Dimensional Category - Variables". Computational Statistics and Data Analysis, 66.
+Variables". Computational Statistics and Data Analysis, 66.Marschner, I. (2011). "glm2: Fitting generalized linear models - with convergence problems". The R Journal, 3(2).
+with convergence problems". The R Journal, 3(2).Stammann, A., F. Heiss, and D. McFadden (2016). "Estimating Fixed - Effects Logit Models with Large Panel Data". Working paper.
+Effects Logit Models with Large Panel Data". Working paper.Stammann, A. (2018). "Fast and Feasible Estimation of Generalized - Linear Models with High-Dimensional k-Way Fixed Effects". ArXiv e-prints.
+Linear Models with High-Dimensional k-Way Fixed Effects". ArXiv e-prints.R/fenegbin.R
fenegbin.RdA wrapper for feglm with
- family = poisson().
family = poisson().
The system might not have a unique solution since we do not take - collinearity into account. If the solution is not unique, an estimable - function has to be applied to our solution to get meaningful estimates of - the fixed effects.
+collinearity into account. If the solution is not unique, an estimable +function has to be applied to our solution to get meaningful estimates of +the fixed effects.tolerance level for the stopping condition. The algorithm is
stopped at iteration \(i\) if \(||\boldsymbol{\alpha}_{i} -
-\boldsymbol{\alpha}_{i - 1}||_{2} < tol ||\boldsymbol{\alpha}_{i - 1}||
-{2}\). Default is 1.0e-08.
1.0e-08.
Stammann, A. (2018). "Fast and Feasible Estimation of Generalized - Linear Models with High-Dimensional k-way Fixed Effects". ArXiv e-prints.
+Linear Models with High-Dimensional k-way Fixed Effects". ArXiv e-prints.Gaure, S. (n. d.). "Multicollinearity, identification, and - estimable functions". Unpublished.
+estimable functions". Unpublished.apes()
Compute average partial effects after fitting binary choice models - with a 1,2,3-way error component
Asymptotic bias correction after fitting binary choice models with a - 1,2,3-way error component
Generalized Linear Models (GLMs) with high-dimensional k-way fixed - effects
fenegbin()
Negative Binomial model fitting with high-dimensional k-way fixed - effects
Covariance matrix for the estimator of the
- average partial effects from objects returned by apes.
apes.
Covariance matrix for the estimator of the
- average partial effects from objects returned by apes.
apes.