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This paper deals with certain estimation problems involving the covariance matrix in large dimensions. Due to the breakdown of finite-dimensional asymptotic theory when the dimension is not negligible with respect to the sample size, it is necessary to resort to an alternative framework known as...
Persistent link: https://www.econbiz.de/10011414533
Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallel-lines assumption). This view neglects possible heterogeneous effects of some explaining factors. This paper describes the use of an...
Persistent link: https://www.econbiz.de/10011524774
Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare...
Persistent link: https://www.econbiz.de/10011528967
In multinomial processing tree (MPT) models, individual differences between the participants in a study lead to heterogeneity of the model parameters. While subject covariates may explain these differences, it is often unknown in advance how the parameters depend on the available covariates,...
Persistent link: https://www.econbiz.de/10011530631
Recursive partitioning techniques are established and frequently applied for exploring unknown structures in complex and possibly high-dimensional data sets. The methods can be used to detect interactions and nonlinear structures in a data-driven way by recursively splitting the predictor space...
Persistent link: https://www.econbiz.de/10011472153
This article presents the eqregsel command for implementing the estimation and bootstrap inference of sample selection models via extremal quantile regression. The command estimates a semiparametric sample selection model without instrument or large support regressor, and outputs the point...
Persistent link: https://www.econbiz.de/10012037854
pdynmc is an R-package for GMM estimation of linear dynamic panel data models that are based on linear and nonlinear moment conditions as proposed by Anderson and Hsiao (1982), Holtz-Eakin, Newey, and Rosen (1988), Arellano and Bover (1995), and Ahn and Schmidt (1995). This paper describes the...
Persistent link: https://www.econbiz.de/10012104784
With the development of large and long panel databases, the theory surrounding panel causality evolves at a fast pace and empirical researchers may sometimes find it difficult to run the most recent techniques developed in the literature. This article presents the Stata user-written command...
Persistent link: https://www.econbiz.de/10011622694