Lasso Regression in R Called by F#

A lasso regression analysis was conducted to identify a subset of variables from a pool of 6 quantitative predictor variables that best predicted a quantitative response variable measuring the number of people employed. Quantitative predictor variables include Gross National Product (GNP), GNP implicit price deflator (1954=100), number of unemployed, number of people in the armed forces, ‘noninstitutionalized’ population ≥ 14 years of age, and the year (time). Because of the small size of the data set (N=16), data were not split into training and test sets.