query: How to get R to deal with a 0 value in your dependent variable when you want to log your distribution
positive_passages.docid: 150717
positive_passages.text: How to avoid log(0) term in regression
negative_passages.docid: 93575
negative_passages.text: How to express "inequality" of a distribution in one number?
negative_passages.docid: 21836
negative_passages.text: Good methods for density plots of non-negative variables in R?
negative_passages.docid: 64805
negative_passages.text: How to calculate relative error when true value is zero?
negative_passages.docid: 156962
negative_passages.text: Logscale plots with zero values in matplotlib
negative_passages.docid: 31788
negative_passages.text: How do I make a log plot where the plot is logarithmic in the distance from the X-Axis (including negative values)?
negative_passages.docid: 130815
negative_passages.text: interpreting level-log model that has a percentage variable
negative_passages.docid: 38471
negative_passages.text: Is it possible to interpret regression output omitting the intercept?
negative_passages.docid: 113833
negative_passages.text: How do I deal with NAs in residuals in a regression in R?
negative_passages.docid: 154939
negative_passages.text: How can I handle autocorrelated residuals?
negative_passages.docid: 132799
negative_passages.text: Constrained Regression in R: coefficients positive, sum to 1 and non-zero intercept
negative_passages.docid: 28984
negative_passages.text: Normality of dependent variable = normality of residuals?
negative_passages.docid: 144971
negative_passages.text: Why exactly can't beta regression deal with 0s and 1s in the response variable?
negative_passages.docid: 2138
negative_passages.text: Modelling when the dependent variable has a "cut-off"
negative_passages.docid: 15529
negative_passages.text: How to interpret p-values of 0 or 1?
negative_passages.docid: 123929
negative_passages.text: What is the correlation if the standard deviation of one variable is 0?
negative_passages.docid: 53308
negative_passages.text: Back transforming regression results when modeling log(y)