wheat: Wheat Data
In Brq: Bayesian Analysis of Quantile Regression Models
Description
Usage
Format
References
Description
This is a regression subsample data set consisting of 113 observations on 6 variables is taken from the national program for the development of wheat cultivation in Iraq - Qadisiyah governorate branch (2017). The complete data set was first analyzed by Hilali (2019). The outcome of interest in this dataset is the percentage increase in wheat yield per dunam (2500 square meters).
Usage
1
data("wheat")
Format
A data frame with 113 observations on the following 6 variables.
ya numeric vector
Ua numeric vector
Qsa numeric vector
Ha numeric vector
Ka numeric vector
MEa numeric vector
References
Abbas, H. K. and Taher, R. J. (2019). Bayesian adaptive lasso tobit regression. Journal of Al-Qadisiyah for Computer Science and Mathematics, 110 (1). <doi:10.29304/jqcm.2019.11.1.471>
Brq documentation built on July 1, 2020, 7:07 p.m.
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Description Usage Format References
Description
This is a regression subsample data set consisting of 113 observations on 6 variables is taken from the national program for the development of wheat cultivation in Iraq - Qadisiyah governorate branch (2017). The complete data set was first analyzed by Hilali (2019). The outcome of interest in this dataset is the percentage increase in wheat yield per dunam (2500 square meters).
Usage
1 | data("wheat")
|
Format
A data frame with 113 observations on the following 6 variables.
ya numeric vector
Ua numeric vector
Qsa numeric vector
Ha numeric vector
Ka numeric vector
MEa numeric vector
References
Abbas, H. K. and Taher, R. J. (2019). Bayesian adaptive lasso tobit regression. Journal of Al-Qadisiyah for Computer Science and Mathematics, 110 (1). <doi:10.29304/jqcm.2019.11.1.471>
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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