dataCopDis: Simulated Dataset with One Endogenous Discrete Regressor
In REndo: Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
dataCopDis R Documentation
Simulated Dataset with One Endogenous Discrete Regressor
Description
A dataset with two exogenous regressors,
X1,X2, and one endogenous, discrete (Poisson distributed) regressor,
P.
An intercept and a dependent variable, y, are also included.
The true parameter values for the coefficients are: b0 = 2, b1 = 1.5,
b2 = -3 and the coefficient of the endogenous regressor, P, is equal to a1 = -1.
Usage
data("dataCopDis")
Format
A data frame with 2500 observations on 4 variables:
ya numeric vector representing the dependent variable.
X1a numeric vector, normally distributed and exogenous.
X2a numeric vector, normally distributed and exogenous.
Pa numeric vector, continuous and endogenous having T-distribution with 3 degrees of freedom.
Author(s)
Raluca Gui raluca.gui@business.uzh.ch
REndo documentation built on July 3, 2024, 1:06 a.m.
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| dataCopDis | R Documentation |
Simulated Dataset with One Endogenous Discrete Regressor
Description
A dataset with two exogenous regressors,
X1,X2, and one endogenous, discrete (Poisson distributed) regressor,
P.
An intercept and a dependent variable, y, are also included.
The true parameter values for the coefficients are: b0 = 2, b1 = 1.5,
b2 = -3 and the coefficient of the endogenous regressor, P, is equal to a1 = -1.
Usage
data("dataCopDis")
Format
A data frame with 2500 observations on 4 variables:
ya numeric vector representing the dependent variable.
X1a numeric vector, normally distributed and exogenous.
X2a numeric vector, normally distributed and exogenous.
Pa numeric vector, continuous and endogenous having T-distribution with 3 degrees of freedom.
Author(s)
Raluca Gui raluca.gui@business.uzh.ch
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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