Lasso Tobit Principal Component Regression With An Application

Hameedah Naeem Melik
International Journal of Science and Mathematics E... 📅 2024 Vol 1, No 4 🔗 DOI: 10.62951/ijsme.v1i4.32
Abstract
One of the most crucial subjects in the analysis of statistical models  is the identification of important variables. Therefore, the search for best variable selection methods is a good in obtaining best estimators. The Lasso method is considered the most effective approach for variable selection and parameter estimation in building statistical models with high explanatory power in representing the studied phenomenon. Therefore, using the Lasso method to estimate the parameters of a regression model that contains a dependent variable with data that is censored at zero can be achieved through the use of    Lasso tobit principal component regression, it has attractive properties in estimating the parameters of this model. The our proposed method is illustrated via simulation scenario and a new real data .
Keywords
Lasso ; component selection ; tobit principal component regression; variable selection
How to Cite

Hameedah Naeem Melik (2024). Lasso Tobit Principal Component Regression With An Application. International Journal of Science and Mathematics Education, 1(4). https://doi.org/10.62951/ijsme.v1i4.32

Hameedah Naeem Melik, "Lasso Tobit Principal Component Regression With An Application," International Journal of Science and Mathematics Education, vol. 1, no. 4, 2024.

Hameedah Naeem Melik. "Lasso Tobit Principal Component Regression With An Application." International Journal of Science and Mathematics Education, vol. 1, no. 4, 2024.

Hameedah Naeem Melik. "Lasso Tobit Principal Component Regression With An Application." International Journal of Science and Mathematics Education 1, no. 4 (2024).

Hameedah Naeem Melik (2024) 'Lasso Tobit Principal Component Regression With An Application', International Journal of Science and Mathematics Education, 1(4). doi: 10.62951/ijsme.v1i4.32.

Hameedah Naeem Melik. Lasso Tobit Principal Component Regression With An Application. International Journal of Science and Mathematics Education. 2024;1(4).

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