Tag: exploratory model analysis

By Riya Jain & Priya Chetty on September 24, 2019 32 Comments

The test found the presence of correlation, with most significant independent variables being education and promotion of illegal activities. Now, the next step is to perform a regression test.

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The previous article (Pooled panel data regression in STATA) showed how to conduct pooled regression analysis with dummies of 30 American companies. The results revealed that the joint hypothesis of dummies reject the null hypothesis that these companies do not have any alternative or joint effects. Therefore pooled regression is not a favourable technique for […]

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The underlying assumption in pooled regression is that space and time dimensions do not create any distinction within the observations and there are no set of fixed effects in the data.

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In multivariate time series, the prominent method of regression analysis is Vector Auto-Regression (VAR). It is important to understand VAR for more clarity.

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By Prateek Sharma & Priya Chetty on April 3, 2018 1 Comment

In statistics, to increase the prediction accuracy and interpret-ability of the model, LASSO (Least Absolute Shrinkage and Selection Operator) is extremely popular. It is a regression procedure that involves selection and regularisation and was developed in 1989. Lasso regression is an extension of linear regression that uses shrinkage. The lasso imposes a constraint on the sum of the absolute values of the model parameters. Here the sum has a specific constant as an upper bound.

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