How do I handle a dependent variable with lot of zero in regression?
How do I handle a dependent variable with lot of zero in regression analysis?
When do I use regression analysis? How can I do non-linear regression analysis? For example, when the shape of data distribution is curved. What is regression? What are the best applications of linear regression? What is model in regression? How does one interpret coefficients from regularized linear regression, considering multicollinearity present between independent variables? What is a dependent variable? How is diminished value calculated? Can I log-transform a variable whose values are expressed as percentages/indexes ranging 0 to 1 to make it significant in a linear probability model? How does one determine the standard error for regression coefficients yielded by sparse regression methods (e.g. Ridge Regression, LASSO, Elastic Net, etc.)? In a simple regression model that I ran, R-square differs from the adjusted R-square. How can this happen? If R-square= 0.765 and standard error = 0.038 with standard deviation=0.465, How do I find the number of observation in the regression? How can I deal with missing values in a predictive model? What are the pros and cons of using an experimental variable? What are the negatives of the S-curve analysis? Why do we need the data to have zero mean in neural networks? In population calculation why is 2.1 considered as optimal replacement ratio and not 2? Economics: A small slope (a number close to zero) means that a demand curve is relatively flat and that a change in one variable greatly correlates with a change in another. Is that true? How can I choose the best model from LARS and LASSO regression? Why does Negative sampling use a margin of 1 in loss function?(it is about Neural network) How can I apply discriminant analysis (multivariate) if my data is not normally distributed? What are the limitations of ratio analysis? What is the difference between linear regression and least squares? How does the expression simplify when the transmission coefficient is much less than 1? How does one interpret coefficients returned by l2 regularized logistic regression, assuming multicollinearity between independent variables? Let x assumes the value 0,1,2 and 3 with respective probabilities 0.51, 0.38, 0.10 and 0.01 the variance of distribution is? What is the LASSO technique for regression? How do I deal with missing values in a predictive model when there is no obvious value? How many zeroes are in 100 factorial? How do you evaluate [math]\int_0^1\frac{x-1}{\ln x}\, dx[/math]?